Device and method for performing entanglement distillation procedure on basis of error-correcting code using ancilla bits in quantum communication system

Abstract

The objective of the present disclosure is to reduce measurement errors in an entanglement distillation procedure of a quantum communication system. This method of operating a first device may comprise the steps of: performing a connection establishment procedure with a second device; receiving configuration information from the second device; generating a first signal and a second signal; transmitting the second signal to the second device; and performing the entanglement distillation procedure of the first signal and the second signal on the basis of an error-correcting code.

Description

Device and method for performing an entanglement distillation procedure based on an error correction code using ancilla bits in a quantum communication system

[0001] The present disclosure relates to a quantum communication system, and to a device and method for performing an entanglement distillation protocol (EDP) based on an error correcting code using ancilla bits in a quantum communication system.

[0002] Wireless access systems are widely deployed to provide various types of communication services, such as voice and data. Typically, wireless access systems are multiple access systems that support communications with multiple users by sharing available system resources (e.g., bandwidth, transmission power). Examples of multiple access systems include code division multiple access (CDMA), frequency division multiple access (FDMA), time division multiple access (TDMA), orthogonal frequency division multiple access (OFDMA), and single-carrier frequency division multiple access (SC-FDMA).

[0003] In particular, as numerous communication devices demand greater communication capacity, enhanced mobile broadband (eMBB) communication technologies are being proposed, improving upon existing radio access technology (RAT). Furthermore, massive machine type communications (mMTC), which connects multiple devices and objects to provide diverse services anytime and anywhere, as well as communication systems that consider reliability and latency-sensitive services / user equipment (UE), are being proposed. Various technological configurations are being proposed for these solutions.

[0004] The present disclosure relates to a device and method for performing a quantum entanglement distillation protocol (EDP) based on an error correcting code in a quantum communication system.

[0005] The present disclosure relates to a device and method for correcting measurement errors in a quantum communication system.

[0006] The present disclosure relates to a device and method for increasing the fidelity of an entangled quantum pair using an error correcting code in a quantum communication system.

[0007] The present disclosure relates to a device and method for encoding measurement target qubits of an entanglement distillation protocol in a quantum communication system based on an error correction code.

[0008] The present disclosure relates to a device and method for decoding based on an error correction code to remove measurement errors of measurement target qubits of an entanglement distillation protocol in a quantum communication system.

[0009] The present disclosure relates to a device and method for measuring target qubits based on different error correction codes by a transmitting device and a receiving device in a quantum communication system.

[0010] The present disclosure relates to a device and method for determining whether to discard a plurality of control qubits based on whether decoding is successful or not in a quantum communication system.

[0011] The present disclosure relates to a device and method for determining which qubits to preserve among a plurality of control qubits by comparing classical bits that have been successfully decoded in a quantum communication system.

[0012] The present disclosure relates to a device and method for correcting measurement errors using a small number of ancilla bits in a quantum communication system.

[0013] The present disclosure relates to a device and method for performing entanglement distillation based on an error correction code having a different number of information bits in a quantum communication system.

[0014] The technical objectives to be achieved in the present disclosure are not limited to those mentioned above, and other technical tasks not mentioned can be considered by a person having ordinary skill in the technical field to which the technical configuration of the present disclosure is applied from the embodiments of the present disclosure described below.

[0015] As an example of the present disclosure, a method performed by a first device in a quantum communication system includes the steps of performing a connection establishment procedure with a second device, receiving configuration information from the second device, generating a first signal and a second signal, transmitting the second signal to the second device, and performing an entanglement distillation procedure of the first signal and the second signal based on an error correction code using a plurality of measurement target qubits and at least one ancilla qubit, wherein a first qubit included in the first signal may be in a quantum entangled state with a second qubit included in the second signal.

[0016] As an example of the present disclosure, a method performed by a second device in a quantum communication system includes the steps of performing a connection establishment procedure with a first device, transmitting configuration information to the first device, receiving a second signal from among a first signal and a second signal generated by the first device from the first device, and performing an entanglement distillation procedure of the first signal and the second signal based on an error correction code using a plurality of measurement target qubits and at least one ancilla qubit, wherein a first qubit included in the first signal may be in a quantum entanglement state with a second qubit included in the second signal.

[0017] As an example of the present disclosure, in a quantum communication system, a first device includes a transceiver, and a processor coupled to the transceiver, wherein the processor is configured to perform a connection establishment procedure with a second device, receive configuration information from the second device, generate a first signal and a second signal, transmit the second signal to the second device, and perform an entanglement distillation procedure of the first signal and the second signal based on an error correction code using a plurality of measurement target qubits and at least one ancilla qubit, wherein a first qubit included in the first signal may be in a quantum entanglement state with a second qubit included in the second signal.

[0018] As an example of the present disclosure, in a quantum communication system, a second device includes a transceiver, and a processor connected to the transceiver, wherein the processor performs a connection establishment procedure with a first device, transmits setup information to the first device, receives a second signal from among a first signal and a second signal generated by the first device from the first device, and controls to perform an entanglement distillation procedure of the first signal and the second signal based on an error correction code using a plurality of measurement target qubits and at least one ancilla qubit, wherein the first qubit included in the first signal may be in a quantum entanglement state with the second qubit included in the second signal.

[0019] As an example of the present disclosure, a communication device includes at least one processor, and at least one computer memory connected to the at least one processor and storing instructions that, when executed by the at least one processor, direct operations, the operations including: performing a connection establishment procedure with a second device, receiving configuration information from the second device, generating a first signal and a second signal, transmitting the second signal to the second device, and performing an entanglement distillation procedure of the first signal and the second signal based on an error correction code using a plurality of measurement target qubits and at least one ancilla qubit, wherein a first qubit included in the first signal may be in a quantum entangled state with a second qubit included in the second signal.

[0020] As an example of the present disclosure, a non-transitory computer-readable medium storing at least one instruction includes at least one instruction executable by a processor, the at least one instruction configuring a first device to perform a connection establishment procedure with a second device, receive configuration information from the second device, generate a first signal and a second signal, transmit the second signal to the second device, and perform an entanglement distillation procedure of the first signal and the second signal based on an error correction code using a plurality of measurement target qubits and at least one ancilla qubit, wherein a first qubit included in the first signal may be in a quantum entangled state with a second qubit included in the second signal.

[0021] The above-described aspects of the present disclosure are only some of the preferred embodiments of the present disclosure, and various embodiments reflecting the technical features of the present disclosure can be derived and understood by a person having ordinary skill in the art based on the detailed description of the present disclosure to be described below.

[0022] The following effects may be achieved by embodiments based on the present disclosure.

[0023] According to the present disclosure, measurement errors can be efficiently corrected using ancilla bits in a quantum communication system.

[0024] The effects that can be obtained from the embodiments of the present disclosure are not limited to the effects mentioned above, and other effects not mentioned can be clearly derived and understood by those skilled in the art to which the technical configuration of the present disclosure is applied, from the description of the embodiments of the present disclosure below. In other words, unintended effects resulting from implementing the configuration described in the present disclosure can also be derived from the embodiments of the present disclosure by those skilled in the art.

[0025] The accompanying drawings are intended to aid understanding of the present disclosure and, together with detailed descriptions, may provide embodiments of the present disclosure. However, the technical features of the present disclosure are not limited to specific drawings, and the features disclosed in each drawing may be combined with each other to form new embodiments. Reference numerals in each drawing may indicate structural elements.

[0026] Figure 1 illustrates an example of a communication system applicable to the present disclosure.

[0027] FIG. 2 illustrates an example of a wireless device applicable to the present disclosure.

[0028] FIG. 3 illustrates a method for processing a transmission signal applicable to the present disclosure.

[0029] Figure 4 illustrates a communication procedure between a terminal and a base station applicable to the present disclosure.

[0030] FIG. 5 illustrates an example of a communication structure that can be provided in a 6G (6th generation) system applicable to the present disclosure.

[0031] Figure 6 illustrates an electromagnetic spectrum applicable to the present disclosure.

[0032] Figure 7 illustrates a transmitter structure applicable to the present disclosure.

[0033] Figure 8 illustrates an example of a functional framework for application of artificial intelligence technology applicable to the present disclosure.

[0034] Figure 9 illustrates an example of a procedure for utilizing an artificial intelligence model applicable to the present disclosure.

[0035] Figure 10 illustrates a communication procedure based on AI (artificial intelligence) technology applicable to the present disclosure.

[0036] FIG. 11 illustrates an example of a quantum channel model based on environmental decoherence in a system applicable to the present disclosure.

[0037] FIG. 12 illustrates an example of an encoding circuit and a safety operator syndrome measurement circuit in a system applicable to the present disclosure.

[0038] FIG. 13 illustrates an example of Alice and Bob performing a quantum privacy amplification (QPA) protocol according to one embodiment of the present disclosure.

[0039] Figure 14 illustrates an example of the success probability of the QPA protocol in a system applicable to the present disclosure.

[0040] Figure 15 illustrates an example of the fidelity performance of the QPA protocol in a system applicable to the present disclosure.

[0041] FIG. 16 illustrates an example of the fidelity performance of the QPA protocol according to measurement error in a system applicable to the present disclosure.

[0042] FIG. 17 illustrates an example of the success probability of the QPA protocol according to measurement error in a system applicable to the present disclosure.

[0043] FIG. 18 illustrates an example of an entanglement distillation protocol using measurement error filtering utilizing local ancilla qubits according to one embodiment of the present disclosure.

[0044] FIG. 19 illustrates an example of the structure of a dual selection protocol according to one embodiment of the present disclosure.

[0045] FIG. 20 illustrates an example of maximum and minimum fidelity performance according to error rates of a CNOT (controlled NOT operation) operator and a measurement operator in a dual-selection or single-selection circuit according to one embodiment of the present disclosure.

[0046] FIG. 21 illustrates examples of gate operation ranges of a dual-selection protocol and a single-selection protocol according to one embodiment of the present disclosure.

[0047] FIG. 22 illustrates an example of output fidelity corresponding to input fidelity in an environment where a gate error exists according to one embodiment of the present disclosure.

[0048] FIG. 23 illustrates the fidelity according to the measurement results in a dual selection protocol according to one embodiment of the present disclosure.

[0049] FIG. 24 illustrates an example of one round in a procedure in which a first device and a second device determine reuse based on a dual-selection quantum entanglement distillation protocol (EDP) according to one embodiment of the present disclosure.

[0050] FIG. 25 illustrates an example of a quantum error correcting codes (QECCs) based hashing protocol according to one embodiment of the present disclosure.

[0051] FIG. 26 illustrates an example of the structure of a single round of a bidirectional EDP technique according to one embodiment of the present disclosure.

[0052] FIG. 27 illustrates an example of a process in which a transmitter and a receiver measure a qubit according to one embodiment of the present disclosure.

[0053] FIG. 28 is a diagram illustrating an example of the structure of a unidirectional EDP technique in a system applicable to the present disclosure.

[0054] FIG. 29 illustrates an example of the basic structure of an adaptive mode EDP technique according to one embodiment of the present disclosure.

[0055] FIG. 30 illustrates an example of a block diagram of a QECCs-based bidirectional EDP technique according to one embodiment of the present disclosure.

[0056] FIG. 31 illustrates an example of output fidelity when [[7,1,3]] QECCs are utilized bidirectionally according to one embodiment of the present disclosure.

[0057] FIG. 32 illustrates an example of the success probability when [[7,1,3]] QECCs are used bidirectionally according to one embodiment of the present disclosure.

[0058] FIG. 33 illustrates an example of output fidelity when [[5,1,3]] QECCs are utilized bidirectionally according to one embodiment of the present disclosure.

[0059] FIG. 34 illustrates an example of the success probability when [[5,1,3]] QECCs are used in both directions according to one embodiment of the present disclosure.

[0060] FIG. 35 illustrates an example of fidelity estimation of an adaptive mode EDP based on [[7,1,3]] QECCs according to one embodiment of the present disclosure.

[0061] FIG. 36 illustrates an example of fidelity estimation of an adaptive mode EDP based on [[5,1,3]] QECCs according to one embodiment of the present disclosure.

[0062] FIG. 37 illustrates an example of estimation of success probability of an adaptive mode EDP based on [[7,1,3]] QECCs according to one embodiment of the present disclosure.

[0063] FIG. 38 illustrates an example of estimation of the success probability of an adaptive mode EDP based on [[5,1,3]] QECCs according to one embodiment of the present disclosure.

[0064] FIG. 39 illustrates an example of the overall procedure of the adaptive mode EDP technique according to one embodiment of the present disclosure.

[0065] FIG. 40 illustrates an example of average and minimum fidelity performance of a bidirectional EDP according to one embodiment of the present disclosure.

[0066] FIG. 41 illustrates an example of an adaptive mode-based EDP technique procedure considering minimum fidelity according to one embodiment of the present disclosure.

[0067] FIG. 42 illustrates an example of minimum fidelity estimation performance when utilizing a [[7,1,3]] error correction code in two-way in a system according to one embodiment of the present disclosure.

[0068] FIG. 43 illustrates an example of minimum fidelity estimation performance when utilizing a [[5,1,3]] error correcting code in both directions according to one embodiment of the present disclosure.

[0069] FIG. 44 illustrates an example of the overall process of a minimum fidelity-based parameter estimation and adaptive mode-based EDP technique according to one embodiment of the present disclosure.

[0070] FIG. 45 illustrates an example of the overall process of a bidirectional QECCs EDP protocol for reusing entangled qubits according to one embodiment of the present disclosure.

[0071] FIG. 46 illustrates the fidelity F' of the entanglement state when errors are corrected and preserved for α syndromes among syndromes of errors having weight t_corr+1=1 in a bidirectional QECCs EDP according to one embodiment of the present disclosure.

[0072] FIG. 47 illustrates the success probability p_succ of an entanglement state when errors are corrected and preserved for α syndromes among syndromes of errors having weight t_corr+1=1 in a bidirectional QECCs EDP according to one embodiment of the present disclosure.

[0073] FIG. 48 illustrates an example of a procedure for additional resource reduction in a bidirectional QECCs EDP according to one embodiment of the present disclosure.

[0074] FIG. 49 illustrates an example of a process in which a sender and a receiver measure qubits in an EDP utilizing computational adaptation according to one embodiment of the present disclosure.

[0075] FIG. 50 illustrates an example of a process in which a sender and a receiver measure qubits in an EDP utilizing computational adaptation to perform twirling according to one embodiment of the present disclosure.

[0076] FIG. 51 illustrates an example of a 2-1 EDP protocol utilizing an operational adaptation technique according to one embodiment of the present disclosure.

[0077] FIG. 52 illustrates an example of a quantum transmission protocol according to one embodiment of the present disclosure.

[0078] FIG. 53 illustrates an example of a procedure for transmitting quantum information in a two-step quantum secure direct communication according to one embodiment of the present disclosure.

[0079] FIG. 54a illustrates an example of a procedure for independently performing four QPA protocols according to one embodiment of the present disclosure.

[0080] FIG. 54b illustrates an example of a procedure for measuring target qubits by utilizing an extended hamming code according to one embodiment of the present disclosure.

[0081] FIG. 54c illustrates examples of measurement target qubits to be encoded via error correction codes in a dual-selection EDP according to one embodiment of the present disclosure.

[0082] FIG. 55 illustrates an example of a communication device performing an entanglement distillation procedure using an error correction code according to one embodiment of the present disclosure.

[0083] FIG. 56 illustrates an example in which a first device according to one embodiment of the present disclosure corrects a measurement error based on an error correction code.

[0084] FIG. 57 illustrates an example of a procedure diagram of an entanglement distillation protocol based on an error correction code according to one embodiment of the present disclosure.

[0085] FIG. 58 illustrates a first example of signaling performed in an entanglement distillation protocol based on an error correction code according to one embodiment of the present disclosure.

[0086] FIG. 59 illustrates a second example of signaling performed in an entanglement distillation protocol based on an error correction code according to one embodiment of the present disclosure.

[0087] Figures 60a and 60b illustrate gate errors according to one embodiment of the present disclosure. m When =0.05, the performance of output fidelity and success probability for input fidelity is shown.

[0088] Figures 61a and 61b illustrate gate errors according to one embodiment of the present disclosure. m When =0.1, it shows the performance of output fidelity and success probability for input fidelity.

[0089] Figures 62a and 62b illustrate gate errors according to one embodiment of the present disclosure. mWhen =0.164, the performance of output fidelity and success probability for input fidelity is shown.

[0090] Figures 63a to 63d illustrate gate errors according to one embodiment of the present disclosure. m When =0.05, the performance of output fidelity and success probability for input fidelity is shown.

[0091] Figures 64a and 64d illustrate gate errors according to one embodiment of the present disclosure. m When =0.1, it shows the performance of output fidelity and success probability for input fidelity.

[0092] Figures 65a and 65c illustrate gate errors according to one embodiment of the present disclosure. m When =0.164, the performance of output fidelity and success probability for input fidelity is shown.

[0093] Figure 66 illustrates an example of a wireless device applicable to the present disclosure.

[0094] Figure 67 illustrates an example of a portable device applicable to the present disclosure.

[0095] Figure 68 illustrates an example of a vehicle or autonomous vehicle applicable to the present disclosure.

[0096] Figure 69 illustrates an example of a vehicle applicable to the present disclosure.

[0097] FIG. 70 illustrates an example of an extended reality (XR) device applicable to the present disclosure.

[0098] Figure 71 illustrates an example of a robot applicable to the present disclosure.

[0099] Figure 72 illustrates an example of an AI device applicable to the present disclosure.

[0100] Figure 73 illustrates an example of a quantum communication device applicable to the present disclosure.

[0101] The following embodiments combine the components and features of the present disclosure in a predetermined form. Each component or feature may be considered optional unless explicitly stated otherwise. Each component or feature may be implemented without being combined with other components or features. Furthermore, some components and / or features may be combined to form embodiments of the present disclosure. The order of operations described in the embodiments of the present disclosure may be changed. Some components or features of one embodiment may be included in another embodiment or may be replaced with corresponding components or features of another embodiment.

[0102] In the description of the drawings, procedures or steps that may obscure the gist of the present disclosure are not described, and procedures or steps that can be understood by a person skilled in the art are also not described.

[0103] Throughout the specification, when a part is said to "comprising" or "including" a component, this does not mean that other components may be included, but rather that other components may be excluded, unless otherwise specifically stated. In addition, terms such as "...part," "...unit," and "module" described in the specification mean a unit that processes at least one function or operation, which may be implemented by hardware, software, or a combination of hardware and software. In addition, the words "a" or "an," "one," "the," and similar related words may be used in the context of describing the present disclosure (especially in the context of the claims below) to include both the singular and the plural, unless otherwise indicated herein or clearly contradicted by context.

[0104] Embodiments of the present disclosure described herein focus on the data transmission and reception relationship between a base station and a mobile station. Here, the base station is understood as a terminal node of a network that directly communicates with the mobile station. Certain operations described herein as being performed by the base station may, in some cases, be performed by an upper node of the base station.

[0105] That is, in a network consisting of multiple network nodes including a base station, various operations performed for communication with a mobile station may be performed by the base station or other network nodes other than the base station. In this case, the term 'base station' may be replaced by terms such as fixed station, Node B, eNB (eNode B), gNB (gNode B), ng-eNB, advanced base station (ABS), or access point.

[0106] Additionally, in the embodiments of the present disclosure, the term terminal may be replaced with terms such as user equipment (UE), mobile station (MS), subscriber station (SS), mobile subscriber station (MSS), mobile terminal, or advanced mobile station (AMS).

[0107] Additionally, a transmitter refers to a fixed and / or mobile node that provides data or voice services, and a receiver refers to a fixed and / or mobile node that receives data or voice services. Therefore, for uplink, a mobile station can be the transmitter, and a base station can be the receiver. Similarly, for downlink, a mobile station can be the receiver, and a base station can be the transmitter.

[0108] Embodiments of the present disclosure may be supported by standard documents disclosed in at least one of wireless access systems, such as IEEE 802.xx system, 3rd Generation Partnership Project (3GPP) system, 3GPP Long Term Evolution (LTE) system, 3GPP 5th generation (5G) NR (New Radio) system and 3GPP2 system, and in particular, embodiments of the present disclosure may be supported by 3GPP TS (technical specification) 38.211, 3GPP TS 38.212, 3GPP TS 38.213, 3GPP TS 38.321 and 3GPP TS 38.331 documents.

[0109] Furthermore, the embodiments of the present disclosure can be applied to other wireless access systems and are not limited to the systems described above. For example, they can be applied to systems implemented after the 3GPP 5G NR system and are not limited to a specific system.

[0110] That is, obvious steps or parts not described in the embodiments of the present disclosure can be explained by referring to the above documents. In addition, all terms disclosed in this document can be explained by the above standard documents.

[0111] Hereinafter, preferred embodiments according to the present disclosure will be described in detail with reference to the accompanying drawings. The detailed description set forth below, together with the accompanying drawings, is intended to illustrate exemplary embodiments of the present disclosure and is not intended to represent the only embodiments in which the technical configurations of the present disclosure may be implemented.

[0112] Additionally, specific terms used in the embodiments of the present disclosure are provided to aid in understanding of the present disclosure, and the use of such specific terms may be changed to other forms without departing from the technical spirit of the present disclosure.

[0113] The following technology can be applied to various wireless access systems such as CDMA (code division multiple access), FDMA (frequency division multiple access), TDMA (time division multiple access), OFDMA (orthogonal frequency division multiple access), and SC-FDMA (single carrier frequency division multiple access).

[0114] For clarity, the following description is based on 3GPP communication systems (e.g., LTE, NR, etc.), but the technical spirit of the present disclosure is not limited thereto. LTE may refer to technology after 3GPP TS 36.xxx Release 8. Specifically, LTE technology after 3GPP TS 36.xxx Release 10 may be referred to as LTE-A, and LTE technology after 3GPP TS 36.xxx Release 13 may be referred to as LTE-A pro. 3GPP NR may refer to technology after TS 38.xxx Release 15. 3GPP 6G may refer to technology after TS Release 17 and / or Release 18. "xxx" refers to a standard document detail number. LTE / NR / 6G may be collectively referred to as a 3GPP system.

[0115] For background information, terms, abbreviations, etc. used in this disclosure, reference may be made to standard documents published prior to this disclosure. For example, reference may be made to standard documents 36.xxx and 38.xxx.

[0116] Communication system applicable to the present disclosure

[0117] Although not limited thereto, the various descriptions, functions, procedures, proposals, methods and / or operational flowcharts of the present disclosure disclosed in this document may be applied to various fields requiring wireless communication / connectivity (e.g., 5G) between devices.

[0118] Hereinafter, more specific examples will be provided with reference to the drawings. In the drawings / descriptions below, the same drawing reference numerals may represent identical or corresponding hardware blocks, software blocks, or functional blocks, unless otherwise described.

[0119] Figure 1 illustrates an example of a communication system applied to the present disclosure.

[0120] Referring to FIG. 1, a communication system (100) applied to the present disclosure includes a wireless device, a base station, and a network. Here, the wireless device refers to a device that performs communication using a wireless access technology (e.g., LTE, LTE-A, LTE-A pro, NR, 5G, 5G-A, 6G) and may be referred to as a communication / wireless / 5G device. Although not limited thereto, the wireless device may include a robot (100a), a vehicle (100b-1, 100b-2), an XR (extended reality) device (100c), a hand-held device (100d), a home appliance (100e), an IoT (Internet of Things) device (100f), and an AI (artificial intelligence) device / server (100g). For example, the vehicle may include a vehicle equipped with a wireless communication function, an autonomous vehicle, a vehicle capable of performing vehicle-to-vehicle communication, etc. Here, the vehicles (100b-1, 100b-2) may include unmanned aerial vehicles (UAVs) (e.g., drones). The XR devices (100c) include augmented reality (AR) / virtual reality (VR) / mixed reality (MR) devices, and may be implemented in the form of head-mounted devices (HMDs), head-up displays (HUDs) installed in vehicles, televisions, smartphones, computers, wearable devices, home appliances, digital signage, vehicles, robots, etc. The portable devices (100d) may include smartphones, smart pads, wearable devices (e.g., smartwatches, smart glasses), computers (e.g., laptops, etc.), etc. The home appliances (100e) may include TVs, refrigerators, washing machines, etc. The IoT devices (100f) may include sensors, smart meters, etc.For example, the base station (120) and the network (130) may also be implemented as wireless devices, and a specific wireless device (120a) may act as a base station / network node to other wireless devices.

[0121] Wireless devices (100a to 100f) can be connected to a network (130) via a base station (120). AI technology can be applied to the wireless devices (100a to 100f), and the wireless devices (100a to 100f) can be connected to an AI server (100g) via a network (130). The network (130) can be configured using a 3G network, a 4G (e.g., LTE) network, a 5G (e.g., NR), or a 6G network. The wireless devices (100a to 100f) can communicate with each other via the base station (120) / network (130), but can also communicate directly (e.g., sidelink communication) without going through the base station (120) / network (130). For example, vehicles (100b-1, 100b-2) can communicate directly (e.g., V2V (vehicle to vehicle) / V2X (vehicle to everything) communication). Additionally, an IoT device (100f) (e.g., a sensor) can communicate directly with another IoT device (e.g., a sensor) or another wireless device (100a to 100f).

[0122] Wireless communication / connection (150a, 150b, 150c) can be established between wireless devices (100a to 100f) / base stations (120), and base stations (120) / base stations (120). Here, the wireless communication / connection can be established through various wireless access technologies such as uplink / downlink communication (150a), sidelink communication (150b) (or D2D communication), and base station-to-base station communication (150c) (e.g., relay, IAB (integrated access backhaul)). Through the wireless communication / connection (150a, 150b, 150c), the wireless device and base station / wireless device, and base stations and base stations can transmit / receive wireless signals to / from each other. For example, the wireless communication / connection (150a, 150b, 150c) can transmit / receive signals through various physical channels. To this end, based on various proposals of the present disclosure, at least some of various configuration information setting processes for transmitting / receiving wireless signals, various signal processing processes (e.g., channel encoding / decoding, modulation / demodulation, resource mapping / demapping, etc.), resource allocation processes, etc. may be performed.

[0123] Devices applicable to the present disclosure

[0124] FIG. 2 illustrates an example of a wireless device applicable to the present disclosure.

[0125] Referring to FIG. 2, the wireless device (200) can transmit and receive wireless signals via various wireless access technologies (e.g., LTE, LTE-A, LTE-A pro, NR, 5G, 5G-A, 6G). The wireless device (200) includes at least one processor (202) and at least one memory (204), and may additionally include at least one transceiver (206) and / or at least one antenna (208).

[0126] The processor (202) controls the memory (204) and / or the transceiver (206), and may be configured to implement the descriptions, functions, procedures, proposals, methods, and / or operational flowcharts disclosed in this document. For example, the processor (202) may process information in the memory (204) to generate first information / signal, and then transmit a wireless signal including the first information / signal via the transceiver (206). In addition, the processor (202) may receive a wireless signal including second information / signal via the transceiver (206), and then store information obtained from signal processing of the second information / signal in the memory (204). The memory (204) may be connected to the processor (202) and may store various information related to the operation of the processor (202). For example, the memory (204) may store software code including instructions for performing some or all of the processes controlled by the processor (202), or for performing the descriptions, functions, procedures, proposals, methods, and / or operational flowcharts disclosed herein. Here, the processor (202) and the memory (204) may be part of a communication modem / circuit / chip designed to implement wireless communication technology. The transceiver (206) may be connected to the processor (202) and may transmit and / or receive wireless signals via at least one antenna (208). The transceiver (206) may include a transmitter and / or a receiver. The transceiver (206) may be used interchangeably with an RF (radio frequency) unit. In the present disclosure, a wireless device may also mean a communication modem / circuit / chip.

[0127] Hereinafter, the hardware elements of the wireless device (200) will be described in more detail. Although not limited thereto, at least one protocol layer may be implemented by at least one processor (202). For example, at least one processor (202) may implement at least one layer (e.g., a functional layer such as physical (PHY), media access control (MAC), radio link control (RLC), packet data convergence protocol (PDCP), radio resource control (RRC), and service data adaptation protocol (SDAP)). At least one processor (202) may generate at least one Protocol Data Unit (PDU) and / or at least one Service Data Unit (SDU) according to the descriptions, functions, procedures, proposals, methods, and / or operation flowcharts disclosed in this document. At least one processor (202) may generate a message, control information, data, or information according to the descriptions, functions, procedures, proposals, methods, and / or operation flowcharts disclosed in this document. At least one processor (202) can generate a signal (e.g., a baseband signal) including a PDU, an SDU, a message, control information, data or information according to the functions, procedures, proposals and / or methods disclosed in this document, and provide the signal to at least one transceiver (206). At least one processor (202) can receive a signal (e.g., a baseband signal) from at least one transceiver (206) and obtain the PDU, SDU, message, control information, data or information according to the descriptions, functions, procedures, proposals, methods and / or operational flowcharts disclosed in this document.

[0128] At least one processor (202) may be referred to as a controller, a microcontroller, a microprocessor, or a microcomputer. The at least one processor (202) may be implemented by hardware, firmware, software, or a combination thereof. For example, at least one application specific integrated circuit (ASIC), at least one digital signal processor (DSP), at least one digital signal processing device (DSPD), at least one programmable logic device (PLD), or at least one field programmable gate array (FPGA) may be included in the at least one processor (202). The descriptions, functions, procedures, proposals, methods, and / or operation flowcharts disclosed in this document may be implemented using firmware or software, and the firmware or software may be implemented to include modules, procedures, functions, etc. The descriptions, functions, procedures, proposals, methods, and / or operation flowcharts disclosed in this document may be included in the at least one processor (202), or may be stored in at least one memory (204) and executed by the at least one processor (202). The descriptions, functions, procedures, suggestions, methods and / or flowcharts disclosed in this document may be implemented using firmware or software in the form of code, instructions and / or sets of instructions.

[0129] At least one memory (204) can be connected to at least one processor (202) and can store various forms of data, signals, messages, information, programs, codes, instructions and / or commands. The at least one memory (204) can be configured as a read only memory (ROM), a random access memory (RAM), an erasable programmable read only memory (EPROM), a flash memory, a hard drive, a register, a cache memory, a computer readable storage medium and / or a combination thereof. The at least one memory (204) can be located internally and / or externally to the at least one processor (202). In addition, the at least one memory (204) can be connected to the at least one processor (202) via various technologies such as a wired or wireless connection.

[0130] At least one transceiver (206) can transmit user data, control information, wireless signals / channels, etc., mentioned in the methods and / or flowcharts of this document to at least one other device. At least one transceiver (206) can receive user data, control information, wireless signals / channels, etc. mentioned in the descriptions, functions, procedures, proposals, methods and / or flowcharts disclosed in this document from at least one other device. For example, at least one transceiver (206) can be connected to at least one processor (202) and can transmit and receive wireless signals. For example, at least one processor (202) can control at least one transceiver (206) to transmit user data, control information, or wireless signals to at least one other device. Furthermore, at least one processor (202) can control at least one transceiver (206) to receive user data, control information, or wireless signals from at least one other device. In addition, at least one transceiver (206) may be connected to at least one antenna (208), and at least one transceiver (206) may be configured to transmit and receive user data, control information, wireless signals / channels, etc. mentioned in the descriptions, functions, procedures, proposals, methods and / or operation flowcharts disclosed in this document through at least one antenna (208). In this document, at least one antenna may be a plurality of physical antennas or a plurality of logical antennas (e.g., antenna ports). At least one transceiver (206) may convert the received wireless signals / channels, etc. from RF band signals to baseband signals in order to process the received user data, control information, wireless signals / channels, etc. using at least one processor (202). At least one transceiver (206) may convert the processed user data, control information, wireless signals / channels, etc. from baseband signals to RF band signals using at least one processor (202).For this purpose, at least one transceiver (206) may include an (analog) oscillator and / or filter.

[0131] The components of the wireless device described with reference to FIG. 2 may be referred to by different terms in terms of functionality. For example, the processor (202) may be referred to as a control unit, the transceiver (206) as a communication unit, and the memory (204) as a storage unit. In some cases, the communication unit may be used to mean at least a portion of the processor (202) and the transceiver (206).

[0132] The structure of the wireless device described with reference to FIG. 2 can be understood as the structure of at least a portion of various devices. For example, the structure of the wireless device illustrated in FIG. 2 can be at least a portion of various devices described with reference to FIG. 1 (e.g., a robot (100a), a vehicle (100b-1, 100b-2), an XR device (100c), a portable device (100d), a home appliance (100e), an IoT device (100f), an AI device / server (100g)). Furthermore, according to various embodiments, in addition to the components illustrated in FIG. 2, the device may further include other components.

[0133] For example, the device may be a portable device such as a smartphone, a smart pad, a wearable device (e.g., a smart watch, smart glasses), or a portable computer (e.g., a laptop, etc.). In this case, the device may further include at least one of a power supply unit that supplies power and includes a wired / wireless charging circuit, a battery, etc., an interface unit that includes at least one port for connection with another device (e.g., an audio input / output port, a video input / output port), and an input / output unit for inputting and outputting image information / signals, audio information / signals, data, and / or information input from a user.

[0134] For example, the device may be a mobile device such as a mobile robot, a vehicle, a train, an aerial vehicle (AV), a ship, etc. In this case, the device may further include at least one of a driving unit including at least one of an engine, a motor, a power train, wheels, brakes, and a steering unit of the device, a power supply unit including a wired / wireless charging circuit, a battery, etc. that supplies power, a sensor unit that senses status information, environmental information, and user information of the device or its surroundings, an autonomous driving unit that performs functions such as path maintenance, speed control, and destination setting, and a position measurement unit that obtains location information of the mobile device through a global positioning system (GPS) and various sensors.

[0135] For example, the device may be an XR device such as an HMD, a head-up display (HUD) installed in a vehicle, a television, a smartphone, a computer, a wearable device, a home appliance, a digital signage, a vehicle, a robot, etc. In this case, the device may further include at least one of a power supply unit that supplies power and includes a wired / wireless charging circuit, a battery, etc., an input / output unit that obtains control information, data, etc. from the outside and outputs the generated XR object, and a sensor unit that senses status information, environmental information, and user information of the device or the surroundings of the device.

[0136] For example, the device may be a robot that can be classified into industrial, medical, household, military, etc. types depending on the purpose or field of use. In this case, the device may further include at least one of a sensor unit that senses status information, environmental information, and user information of the device or its surroundings, and a driving unit that performs various physical actions, such as moving the robot joints.

[0137] For example, the device may be an AI device such as a TV, a projector, a smartphone, a PC, a laptop, a digital broadcasting terminal, a tablet PC, a wearable device, a set-top box (STB), a radio, a washing machine, a refrigerator, digital signage, a robot, a vehicle, etc. In this case, the device may further include at least one of an input unit that acquires various types of data from the outside, an output unit that generates output related to sight, hearing, or touch, a sensor unit that senses status information, environmental information, and user information of the device or its surroundings, and a training unit that trains a model composed of an artificial neural network using learning data.

[0138] The structure of the wireless device illustrated in FIG. 2 may be understood as a part of a RAN node (e.g., a base station, DU, RU, RRH, etc.). That is, the device illustrated in FIG. 2 may be a RAN node. In this case, the device may further include a wired transceiver for front haul and / or back haul communications. However, if the front haul and / or back haul communications are based on wireless communications, at least one transceiver (206) illustrated in FIG. 2 may be used for front haul and / or back haul communications, and a wired transceiver may not be included.

[0139] FIG. 3 illustrates a method for processing a transmission signal applicable to the present disclosure. For example, the transmission signal may be processed by a signal processing circuit. At this time, the signal processing circuit (300) may include scramblers (310), modulators (320), a layer mapper (330), a precoder (340), resource mappers (350), and signal generators (360). At this time, for example, the operation / function of FIG. 3 may be performed in the processor (202) and / or the transceiver (206) of FIG. 2. Furthermore, for example, the hardware elements of FIG. 3 may be implemented in the processor (202) and / or the transceiver (206) of FIG. 2. For example, blocks 310 to 360 may be implemented in the processor (202) of FIG. 2. Additionally, blocks 310 to 350 may be implemented in the processor (202) of FIG. 2, and block 360 may be implemented in the transceiver (206) of FIG. 2, and are not limited to the above-described embodiment.

[0140] The codeword can be converted into a wireless signal through the signal processing circuit (300) of FIG. 3. Here, the codeword is an encoded bit sequence of an information block. The information block may include a transport block (e.g., a UL-SCH transport block, a DL-SCH transport block). Here, the information block may include data related to AI (e.g., training data, AI model data, input data, output data, etc.), and the codeword may be an encoded bit sequence corresponding to the data related to AI. The wireless signal may be transmitted through various physical channels (e.g., a PUSCH, a PDSCH). Specifically, the codeword may be converted into a bit sequence scrambled by scramblers (310). The scramble sequence used for scrambling is generated based on an initialization value, and the initialization value may include ID information of the wireless device, etc. The scrambled bit sequence may be modulated into a modulation symbol sequence by modulators (320). Modulation schemes may include pi / 2-BPSK (pi / 2-binary phase shift keying), m-PSK (m-phase shift keying), m-QAM (m-quadrature amplitude modulation), etc.

[0141] A complex modulation symbol sequence can be mapped to at least one transport layer by a layer mapper (330). Here, a transport layer is a logical resource unit for mapping a signal or data transmitted through spatial resources to antenna ports, and one transport layer can correspond to one stream or one antenna port. Each of the complex modulation symbols included in the complex modulation symbol sequence is mapped to at least one transport layer, thereby determining which antenna port it will be transmitted through. The modulation symbols of each transport layer can be mapped to the corresponding antenna port(s) by a precoder (340). The output z of the precoder (340) can be obtained by multiplying the output y of the layer mapper (330) by a precoding matrix W of NM. Here, N is the number of antenna ports, and M is the number of transport layers. Here, the precoder (340) may perform precoding after performing transform precoding (e.g., discrete Fourier transform (DFT) transform) on complex modulation symbols. Additionally, the precoder (340) may perform precoding without performing transform precoding.

[0142] Resource mappers (350) can map modulation symbols of each antenna port to time-frequency resources. The time-frequency resources may include a plurality of symbols (e.g., CP-OFDMA symbols, DFT-s-OFDMA symbols) in the time domain and a plurality of subcarriers in the frequency domain. Signal generators (360) generate wireless signals from the mapped modulation symbols, and the generated wireless signals can be transmitted to other devices through each antenna. To this end, each of the signal generators (360) may include an inverse fast Fourier transform (IFFT) module, a cyclic prefix (CP) inserter, a digital-to-analog converter (DAC), a frequency uplink converter, etc.

[0143] The signal processing process for a received signal in a wireless device may be configured in reverse order of the signal processing process (310 to 360) of FIG. 3. For example, a wireless device (e.g., 200 of FIG. 2) may receive a wireless signal from the outside through an antenna port / transceiver. The received wireless signal may be converted into a baseband signal through a signal restorer. For this purpose, the signal restorer may include a frequency downlink converter, an analog-to-digital converter (ADC), a CP remover, and a fast Fourier transform (FFT) module. Thereafter, the baseband signal may be restored to a codeword through a resource demapper process, a postcoding process, a demodulation process, and a descrambling process. The codeword may be restored to the original information block through decoding. Therefore, a signal processing circuit (not shown) for a received signal may include a signal restorer, a resource demapper, a postcoder, a demodulator, a descrambler, and a decoder.

[0144] The signal processing circuit (300) described with reference to FIG. 3 is exemplified as including a plurality of scramblers (310), modulators (320), a plurality of resource mappers (350), and a plurality of signal generators (360). However, at least one of the scramblers, modulators, resource mappers, and signal generators may be implemented as a single integrated structure. That is, the number of at least one of the scramblers, modulators, resource mappers, and signal generators may be smaller than the number of layers. Furthermore, at least one of the components exemplified in FIG. 3 may be omitted.

[0145] Figure 4 illustrates a communication procedure between a terminal and a base station applicable to the present disclosure. Figure 4 illustrates operations of a terminal (410) and a base station (420) transmitting and / or receiving data and operations performed prior thereto.

[0146] Referring to FIG. 4, in step 401, the terminal (410) and the base station (420) perform synchronization. For example, the terminal (410) performs an initial cell search operation. Specifically, the terminal (410) can detect at least one synchronization signal transmitted from the base station (420) according to a predefined rule. Here, the synchronization signal can include multiple synchronization signals classified according to structure or purpose (e.g., primary synchronization signal, secondary synchronization signal). Through this, the terminal (410) can check the boundary of the frame, subframe, slot, and / or symbol of the base station (420) and obtain information about the base station (420) (e.g., cell identifier).

[0147] In step 403, the terminal (410) obtains system information transmitted from the base station (420). The system information is information related to the properties, characteristics, and / or capabilities of the base station (420) required to access the base station (420) and use the service, and may be classified by content (e.g., whether it is essential for access), transmission structure (e.g., channel used, whether provided on-demand), etc., and may be classified into, for example, a master information block (MIB) and a system information block (SIB). If necessary, the terminal (410) may transmit a signal requesting system information before receiving the system information. The system information may include information related to an AI function. For example, the system information may include at least one of information related to an AI model, information related to training, and information related to inference / prediction, as information required for operations performed based on AI. However, the request and provision of the system information may be performed after a random access procedure described below.

[0148] In step 405, the terminal (410) and the base station (420) perform a random access procedure. The terminal (410) may transmit and / or receive at least one message (e.g., a random access preamble, a random access response (RAR) message, etc.) for the random access procedure based on information related to the random access channel of the base station (420) obtained through system information (e.g., channel position, channel structure, supported preamble structure, etc.). For example, the terminal (410) may transmit a preamble (e.g., MSG1) through the random access channel, receive an RAR message (e.g., MSG2), transmit a message (e.g., MSG3) including information related to the terminal (410) (e.g., identification information) to the base station (420) using scheduling information included in the RAR message, and receive a message (e.g., MSG4) for contention resolution and / or connection establishment. As another example, MSG1 and MSG3 may be sent and received as one message, or MSG2 and MSG4 may be sent and received as one message.

[0149] In step 407, the terminal (410) and the base station (420) perform signaling of control information. Here, the control information may be defined in various layers, such as a layer that controls a connection (e.g., a radio resource control (RRC) layer), a layer that handles mapping between logical channels and transport channels (e.g., a media access control (MAC) layer), and a layer that handles physical channels (e.g., a physical (PHY) layer). For example, the terminal (410) and the base station (420) may perform at least one of signaling for establishing a connection, signaling for determining settings related to communication, and signaling for indicating allocated resources. In addition, the signaling of the control information may be performed to convey information related to an AI function. For example, the information related to an AI function is information necessary for an operation performed based on AI, and may include at least one of information related to an AI model, information related to training, and information related to inference / prediction. More specifically, information related to the AI ​​function signaled in step 407 may be combined and / or linked with information related to the AI ​​function signaled in step 403, and the two may be defined in a hierarchical, mutually complementary, or substitutive structure.

[0150] In step 409, the terminal (410) and the base station (420) transmit and / or receive data. In other words, the terminal (410) and the base station (420) can process, transmit, and / or receive data based on the signaling of the control information. For example, when transmitting data, the terminal (410) or the base station (420) can perform at least one of channel encoding, rate matching, scrambling, constellation mapping, layer mapping, waveform modulation, antenna mapping, and resource mapping on the information bits. Conversely, when receiving data, the terminal (410) or the base station (420) can perform at least one of signal extraction from resources, waveform demodulation for each antenna, signal arrangement considering layer mapping, constellation demapping, descrambling, and channel decoding. Here, the transmitted data is data related to AI, and may include, for example, data for AI-based operations or data generated by AI-based operations.

[0151] Steps 401 to 409 illustrated with reference to FIG. 4 do not necessarily have to be performed in the order illustrated in FIG. 4, and the order of at least some of the steps may vary. Furthermore, at least some of steps 401 to 409 may be combined into a single step or omitted. That is, the steps illustrated in FIG. 4 may be performed in various modified forms.

[0152] 6G communication systems and core implementation technologies of 6G systems

[0153] The 5G system defines various operating bands within FR1 (frequency range 1), which covers 410 MHz to 7125 MHz, and FR2 (frequency range 2), which covers 24,250 MHz to 71,000 MHz. Various frequencies are being discussed as operating bands for the subsequent 6G system, and the use of higher frequencies than 5G systems is also being considered for wider bandwidth and higher transmission speeds. One such band is the THz (terahertz) frequency band, which covers approximately 100 GHz to 10 THz. The THz frequency band is a band that has both the transparency of radio waves and the straightness of light waves, and communications using the THz frequency band are expected to play a transitional role from existing radio-centered communications to lightwave-based communications.

[0154] 6G systems utilizing the THz frequency band are aimed at i) very high data rates per device, ii) a very large number of connected devices, iii) global connectivity, iv) very low latency, v) reducing energy consumption of battery-free IoT devices, vi) ultra-reliable connectivity, and vii) connected intelligence with machine learning capabilities. The vision of the 6G system can be divided into four aspects: “intelligent connectivity,” “deep connectivity,” “holographic connectivity,” and “ubiquitous connectivity,” and the 6G system can be designed to satisfy the requirements as shown in [Table 1] below.

[0155] Per device peak data rate1 TbpsE2E latency1 msMaximum spectral efficiency100 bps / HzMobility supportup to 1000 km / hrSatellite integrationFullyAIFullyAutonomous vehicleFullyXRFullyHaptic CommunicationFully

[0156] At this time, the 6G system may have key factors such as enhanced mobile broadband (eMBB), ultra-reliable low latency communications (URLLC), massive machine type communications (mMTC), AI integrated communication, tactile internet, high throughput, high network capacity, high energy efficiency, low backhaul and access network congestion, and enhanced data security. FIG. 5 illustrates an example of a communication structure that can be provided in a 6G system applicable to the present disclosure. Referring to FIG. 5, the 6G system is expected to have simultaneous wireless communication connectivity that is 50 times higher than that of a 5G wireless communication system. URLLC, a key feature of 5G, is expected to become an even more crucial technology in 6G communications, offering end-to-end latency of less than 1 ms. Furthermore, 6G systems will boast significantly higher volumetric spectral efficiency than the commonly used area spectral efficiency. 6G systems can offer extremely long battery life and advanced battery technologies for energy harvesting, eliminating the need for separate charging for mobile devices in 6G systems. New network characteristics in 6G may include:

[0157] - Satellite integrated network: 6G is expected to integrate with satellites to provide a global mobile network. The integration of terrestrial, satellite, and airborne networks into a single wireless communications system is crucial for 6G.

[0158] Connected Intelligence: Unlike previous generations of wireless communication systems, 6G is revolutionary, upgrading the wireless evolution from "connected objects" to "connected intelligence." AI can be applied at every stage of the communication process (or at every signal processing step, as described below).

[0159] - Seamless integration of wireless information and energy transfer: 6G wireless networks will transfer power to charge the batteries of devices such as smartphones and sensors. Therefore, wireless information and energy transfer (WIET) will be integrated.

[0160] - Ubiquitous super 3D connectivity: Access to networks and core network functions of drones and very low Earth orbit satellites will create super 3D connectivity in 6G ubiquitous.

[0161] Some general requirements for the new network characteristics of 6G, such as the above, may be as follows:

[0162] - Small cell networks: The concept of small cell networks was introduced to improve received signal quality in cellular systems by increasing throughput, energy efficiency, and spectral efficiency. Consequently, small cell networks are essential for 5G and beyond-5G (5GB) communication systems. Accordingly, 6G communication systems also adopt the characteristics of small cell networks.

[0163] Ultra-dense heterogeneous networks: Ultra-dense heterogeneous networks will be another key feature of 6G communication systems. Multi-tier networks comprised of heterogeneous networks improve overall QoS and reduce costs.

[0164] High-capacity backhaul: Backhaul connections are characterized by high-capacity backhaul networks to support high-volume traffic. High-speed fiber optics and free-space optics (FSO) systems may be potential solutions to this problem.

[0165] - Radar technology integrated with mobile technology: High-precision localization (or location-based services) through communications is a key feature of 6G wireless communication systems. Therefore, radar systems will be integrated with 6G networks.

[0166] - Softwarization and virtualization: Softwarization and virtualization are two critical features that form the foundation of the design process for 5GB networks to ensure flexibility, reconfigurability, and programmability. Furthermore, billions of devices can be shared on a shared physical infrastructure.

[0167] To satisfy the above-mentioned characteristics, the core implementation technologies of the 6G system may include artificial intelligence (AI), THz (terahertz) communication, optical wireless technology, FSO backhaul network, massive MIMO technology, blockchain, 3D networking, quantum communication, unmanned aerial vehicles, cell-free communication, wireless information and energy transfer (WIET), integration of sensing and communication, integration of access backhaul networks, holographic beamforming, big data analysis, and large intelligent surface (LIS).

[0168] For example, THz communication can be utilized in 6G systems. THz communication is a communication that utilizes a spectrum in a frequency band between 0.3 THz and 3 THz with a corresponding wavelength in the range of 0.1 mm to 1 mm, as shown in FIG. 6. Referring to FIG. 6, the frequency band of THz waves is located in the middle region between the infrared band and the millimeter wave band, and therefore, THz waves can be understood as radio waves with the shortest wavelength and light waves with the longest wavelength. Therefore, THz waves share some of the characteristics of infrared and microwave waves, and specifically, they can simultaneously have the transparency of electromagnetic waves and the straightness of light waves.

[0169] Figure 7 illustrates a transmitter structure applicable to the present disclosure.

[0170] Referring to Figure 7, in order to modulate data into an optical signal, an optical source of a laser can be passed through an optical wave guide to change the phase of the signal, etc. At this time, data is loaded by changing the electrical characteristics through a microwave contact, etc. Therefore, the optical modulator output is formed as a modulated waveform.

[0171] Data may be provided from a data signal generator. Here, the data may include various user data, configuration information, control information, etc. transmitted through a channel. Furthermore, the data may include data related to AI-based operations, such as information for configuring an AI model, input / output data for tasks of the AI ​​model, etc. To this end, components related to AI functions (e.g., an AI processing unit) may be included in the data signal generator or may be linked to the data signal generator.

[0172] An optical / electronic converter (O / E converter) can generate THz pulses by optical rectification using a nonlinear crystal, photoelectric conversion using a photoconductive antenna, or emission from a bunch of relativistic electrons. The THz pulse generated in the above manner can have a length in the range of femtoseconds to picoseconds. The optical / electronic converter (O / E converter) performs down conversion by utilizing the nonlinearity of the device.

[0173] Considering the THz spectrum usage, it is likely that multiple contiguous GHz bands will be used for THz systems, either fixed or for mobile services. For an outdoor scenario, the available bandwidth can be categorized based on an oxygen attenuation of 10^2 dB / km in the spectrum up to 1 THz. Accordingly, a framework in which the available bandwidth is divided into multiple band chunks can be considered. As an example of this framework, if the THz pulse length for a single carrier is set to 50 ps, ​​the bandwidth (BW) becomes approximately 20 GHz.

[0174] Effective down-conversion from the infrared band to the THz band depends on how to utilize the nonlinearity of the optical / electrical converter (O / E converter). In other words, to down-convert to the desired THz band, it is necessary to design an O / E converter with the most ideal non-linearity for transferring to the THz band. If an O / E converter that is not suitable for the target frequency band is used, errors in the amplitude and phase of the pulse are likely to occur.

[0175] A THz transmission and reception system can be implemented using a single optical-to-electrical converter in a single-carrier system. Depending on the channel environment, optical-to-electrical converters may be required as many as the number of carriers in a multi-carrier system. This phenomenon will be particularly noticeable in a multi-carrier system that utilizes multiple broadbands according to the aforementioned spectrum usage plan. In this regard, a frame structure for the multi-carrier system may be considered. A signal down-frequency converted based on an optical-to-electrical converter may be transmitted in a specific resource region (e.g., a specific frame). The frequency region of the specific resource region may include multiple chunks. Each chunk may be composed of at least one component carrier (CC).

[0176] 6G systems may introduce AI technology. Efficient resource management and optimization are necessary to maintain connectivity between various services and devices. AI technology may include technologies that perform data analysis, pattern recognition, and predictive modeling using AI / ML (artificial intelligence / machine learning) models. Here, an AI / ML model can be understood as a set of parameter values ​​and / or weight values ​​related to mathematical formulas or algorithms generated through learning to discover patterns in input data or make predictions. To create such an AI / ML model, an AI / ML model learning process is required, which builds an AI / ML model by learning the relationship between inputs and outputs in a data-driven manner. Various learning algorithms, such as supervised learning, unsupervised learning, and reinforcement learning, can be utilized as learning algorithms. To generate output, a user can input specific data into a trained AI / ML model, and the process of obtaining output data by inputting input data into an AI / ML model can be referred to as AI / ML "inference" or "prediction."

[0177] Network control parameters can be obtained as output through AI / ML inference using trained AI / ML models. Users can utilize the output parameter values ​​to improve network efficiency. For example, AI technology can be utilized in various fields, such as wireless network resource allocation, traffic management, fault prediction, and quality of service (QoS) management. In particular, machine learning can efficiently allocate resources even in dynamically changing network environments based on real-time data. Therefore, AI technology can be utilized to provide hyper-connectivity and ultra-low latency.

[0178] At this time, AI / ML inference can be performed based on a combination of various devices. For example, the UE and the network can jointly perform AI / ML inference, and such an AI / ML model can be referred to as a two-sided AI / ML model or a two-sided model. In this case, the UE can perform the first part of the inference first, and the base station can perform the remaining inference, or vice versa. Alternatively, inference can be performed entirely on the UE, and such an AI / ML model can be referred to as a UE-side AI / ML model or a UE-side model.

[0179] Additionally, life cycle management (LCM) can be performed for AI / ML models. Life cycle management can include model training, model deployment, model inference, model monitoring, and model updates. This may require support for data collection, model training, functional / model identification, model delivery / transfer, model inference operations, functional / model selection / activation / deactivation / fallback, functional / model monitoring, model updates, and UE capabilities.

[0180] For example, AI / ML technology can be operated based on a functional framework such as FIG. 8. FIG. 8 illustrates an example of a functional framework for application of AI / ML technology applicable to the present disclosure. First, a data collection function (810) performs data preparation on input data collected from objects (e.g., UE, RAN node, network node, etc.) to generate training data (801), monitoring data (803), and / or inference data (805) including processed input data. A model training function (820), which receives training data (801) from the data collection function (810), performs training on an AI / ML model using the training data (801) and provides a trained / updated model (813) to a model repository (840). The model repository (840) can store and retain the received trained / updated model (813).

[0181] A management function (830) may be used to control AI / ML model training. The management function (830) may control the operation of the AI / ML model or AI / ML functions, or supervise their performance. To this end, the management function (830) may receive monitoring data (830) from the data collection function (810) and inference output (809) from the inference function (840). The management function (830) manages the data received from the data collection function (810) and the inference function (840) so that the inference task can be performed efficiently. That is, the management function (830) may transmit performance feedback or a retraining request (807) to the model training function (820) to improve the inference task. Here, the performance feedback may be used to indicate a learning goal or as a reward for reinforcement learning. Additionally, the management function (830) can transmit management instructions (811) that instruct the inference function (840) to select AI / ML models or AL / ML-based functions to be used, activate / deactivate them, or switch to non-AI / ML operation.

[0182] The inference function (840) generates an inference output (809) by performing inference and / or prediction using the inference data (805) received by the data collection function (810). Here, the inference output (809) refers to the inference output of the AI / ML model used by the inference function (840), and the details of the inference output may vary depending on the use case. The AI / ML model used by the inference function (840) can be controlled by the management function (830). That is, the management function (830) can transmit a model transfer / forward request signal (815) to request a necessary AI / ML model to the model repository function (850), and the model repository function (850) can transmit the corresponding AI / ML model to the inference function (840) via a model transfer / forward signal (817). Therefore, the inference function (840) can perform inference using the AI / ML model (817) according to the received management instruction (811).

[0183] Additionally, the management function (830) may trigger or perform a designated task / action based on the inference output (809). Accordingly, the management function (830) may trigger a task / action for another entity (e.g., at least one UE, at least one RAN node, at least one network node, etc.) or for itself. Any one of the functions exemplified in FIG. 8 described above may be performed by two or more entities, including the RAN, the network node, the network operator's OAM, or the UE, in collaboration. This may be referred to as a split AI operation.

[0184] Not all of the functions (810 to 850) illustrated in FIG. 8 need to be used to utilize the AI / ML model, and the method of combining them is not limited to a specific method. Accordingly, the functions (810 to 850) may be operated in an integrated manner, or some functions may be omitted. Furthermore, the functions (810 to 850) illustrated in FIG. 8 are not necessarily limited to being implemented as separate devices or apparatuses. For example, some or all of the functions (810 to 850) may be included in the processor (202) of FIG. 2. Furthermore, the model storage function (850) may be included in the memory (204) of FIG. 2.

[0185] FIG. 9 illustrates an example of a procedure for utilizing an AI model applicable to the present disclosure. FIG. 9 illustrates a case where a model training function (820) is included in a network node and a model inference function (840) is included in a RAN node. Referring to FIG. 9, in step 1, RAN node 1 and RAN node 2 transmit input data (e.g., training data) for training an AI model to the network node. Here, RAN node 1 and RAN node 2 may transmit data collected from the UE (e.g., measurements of the UE related to RSRP, RSRQ, SINR of the serving cell and neighboring cells, the UE's position, speed, etc.) together to the network node. In step 2, the network node trains the AI ​​model using the received training data. In step 3, the network node distributes / updates the AI ​​model to RAN node 1 and / or RAN node 2. RAN node 1 and / or RAN node 2 may also continue model training based on the received AI model. In this procedure, it is assumed that the AI ​​model is deployed / updated only to RAN node 1. In step 4, RAN node 1 receives input data (e.g., inference data) for AI model inference from UE and RAN node 2. In step 5, RAN node 1 performs AI model-based inference using the received inference data to generate output data (e.g., prediction or decision). In step 6, if applicable, RAN node 1 may transmit model performance feedback to network nodes. In step 7, RAN node 1, RAN node 2, and UE (or 'RAN node 1 and UE', or 'RAN node 1 and RAN node 2') perform actions based on the output data. For example, in case of load balancing operation, the UE may move from RAN node 1 to RAN node 2. In step 8, RAN node 1 and RAN node 2 transmit feedback information to network nodes.

[0186] Network nodes can manage AI models based on feedback information regarding the AI ​​model's inference results. For example, the network node can perform additional training on the AI ​​model or generate additional information about the AI ​​model (e.g., performance information, accuracy information, etc.). If additional training is performed on the AI ​​model, the network node can distribute the updated AI model to RAN node 1.

[0187] As described with reference to Figure 9, model training can be performed by network nodes, and inference using the model can be performed by RAN node 1. In other words, the model training and inference functions can be distributed. Typically, model training requires significant computational resources because it utilizes large amounts of data and complex algorithms for optimization. In contrast, inference, which uses a trained model to derive conclusions about new data, requires relatively fewer computational resources compared to model training. Therefore, using the procedure of Figure 9, model training can be performed through network nodes when the computational resources of the UE or RAN node are insufficient. Furthermore, security can be ensured for the AI ​​model because the AI ​​model is not disclosed to the UE.

[0188] FIG. 9 illustrates a case where a model training function (820) is included in a network node and a model inference function (840) is included in a RAN node, but the present disclosure is not limited thereto. For example, if the computational resources of the RAN node are sufficient, both the model training function (820) and the model inference function (840) may be included in RAN node 1. In this case, RAN node 1 receives training data for training an AI model from the UE and RAN node 2. RAN node 1 trains the AI ​​model using the received training data. Thereafter, RAN node 1 receives inference data for AI model inference from the UE and RAN node 2. RAN node 1 performs inference based on the AI ​​model using the received inference data to generate output data. Based on the output data, the UE, RAN node 1, and RAN node 2 may perform operations related to communication (e.g., handover, cell change). Thereafter, the UE and RAN node 2 may transmit feedback regarding the operations to RAN node 1. Therefore, RAN node 1 can learn the AI ​​model and update its own AI model using feedback information regarding the AI ​​model's inference results. According to the aforementioned method, signaling with the network is not required for AI model learning and inference, thereby reducing network load and delays until the AI ​​model is trained or inference results are received. Furthermore, since the UE performs inference using the AI ​​model, its personal information is not transmitted to network nodes, etc., thereby enhancing the security of personal information.

[0189] As another example, the model training function (820) may be included in the RAN node, and the model inference function (840) may be included in the UE. The RAN node receives training data for training an AI model from the UE, and trains the AI ​​model using the received training data. The RAN node distributes the trained AI model to the UE. The UE may perform inference based on the received AI model to generate output data. At this time, the data for inference may be received from the RAN node, or the UE may use data acquired on its own. The UE and the RAN node may perform communication-related operations based on the output data generated by inference. Thereafter, the UE may transmit feedback regarding the operation to the RAN node. Therefore, the RAN node may train the AI ​​model and distribute the updated AI model to the UE through feedback information regarding the inference result of the AI ​​model. According to the above-described method, the model training function (820) may be included in the RAN node, and the model inference function (840) may be included in the UE to perform inference, thereby reducing the load on the RAN node. Additionally, if the UE uses data acquired on its own to make inferences, even if the UE loses connection with the RAN node after receiving the AI ​​model, the UE can continue to infer the distributed AI model and perform operations based on the inference results.

[0190] According to the framework and procedures described above, an AI model can be trained and utilized in a wireless communication system. The model training function (820) and the model inference function (840) can be combined in various ways and are not necessarily limited to the case of FIG. 9. In the framework and procedures described above, various types of data, such as input data, training data, and inference data, are introduced, and the specific content of the data described above may vary depending on the task for which the AI ​​model is utilized. For example, information used in various embodiments of the present disclosure described below may be included in the data described above.

[0191]

[0192] Figure 10 illustrates an AI technology-based communication procedure applicable to the present disclosure. The detailed procedures illustrated in Figure 10 can be combined with various embodiments of the present disclosure described below. For example, data generated according to various embodiments of the present disclosure can be used for operations (e.g., configuration, training, inference, and / or data transmission / reception) in at least one of the detailed procedures illustrated in Figure 10. As another example, the results of the inference illustrated in Figure 10 can be used to transmit and / or receive data according to various embodiments of the present disclosure.

[0193] Referring to FIG. 10, in step S1001, at least one of the UE (1010), the RAN node (1020), and the network node (1030) performs an initial access procedure. For example, in this step, at least one of an initial cell search operation, a system information acquisition operation, a random access operation, and a registration operation may be performed. In step S1003, at least one of the UE (1010), the RAN node (1020), and the network node (1030) performs a configuration procedure. Through the configuration procedure, parameters, resources, connections, and / or entities necessary for performing subsequent procedures in layers between the UE (1010) and the RAN node (1020) and / or in at least one layer between the UE (1010) and the network node (1030) may be determined and / or created. In this case, the configuration procedure may be performed based on information, status, and / or characteristics of an AI model used for subsequent training and inference.

[0194] In step S1005, at least one of the UE (1010), the RAN node (1020), and the network node (1030) performs a model training procedure. At least one of the UE (1010), the RAN node (1020), and the network node (1030) may collect training data and perform learning using the training data. For example, the model training procedure may be performed as described with reference to FIG. 9. If an offline-trained model is used, this step may be omitted.

[0195] In step S1007, at least one of the UE (1010), the RAN node (1020), and the network node (1030) performs a task using the trained model. That is, the task may be performed based on the results of inference and / or prediction using the trained model. For example, the task may be a procedure belonging to a communication protocol, and may be a preparatory operation for subsequent data transmission and / or reception, or may be related to data transmission and / or reception, or may be related to data processing (e.g., encoding, decoding, etc.).

[0196] In step S1009, at least one of the UE (1010), the RAN node (1020), and the network node (1030) transmits and / or receives data. At this time, the result of the task performed in step 1007 may be used. In some cases, the task performed in step 1007 may include transmitting and / or receiving data, in which case this step may be omitted as it is part of step 1007.

[0197] Specific embodiments of the present disclosure

[0198] The present disclosure relates to a technology for sharing entangled quantum pairs between quantum communication devices, for performing communication using quantum entanglement in a quantum communication system. To improve the fidelity of entangled quantum pairs, a quantum entanglement distillation protocol is required. If measurement errors occur in various quantum entanglement distillation protocols, the efficiency of the quantum entanglement distillation protocol may decrease. The present disclosure proposes a quantum entanglement distillation protocol using ancillar bits. In addition, a technique for correcting measurement errors is proposed by encoding and decoding the target qubits to be measured and the ancillar bits using error-correcting codes. Below, an overview of the entanglement distillation protocol and quantum communication applicable to the present disclosure will be described first.

[0199] Entanglement

[0200] Entanglement is a very important property that differentiates quantum systems from classical information. Entanglement refers to a state in which the results of different observations are closely related to each other. The entanglement state of a quantum system acts more strongly than any correlation that exists in classical mechanics. Two qubits can be represented as a superposition of four fundamental quantum states in Hilbert space. Here, the four fundamental quantum states are { , , , } is included. The basic quantum state of two qubits can be expressed through tensor operations on the basic states of individual qubits. If the state of two qubits cannot be expressed as a tensor product of a single qubit, such a qubit state is called an entangled state. There are four cases, which are representative examples of qubits in an entangled state and are called EPR (Einstein-Podolsky-Rosen) states, and the four cases are as shown in [Mathematical Formula 1] below.

[0201]

[0202]

[0203]

[0204]

[0205] In [Equation 1] can be used when transmitting classical information 00, can be expressed as, can be used to transmit classical information 10, can be expressed as, can be used when transmitting classic information 01, can be expressed as, can be used to transmit classical information 11, can be expressed as . The matching relationship between quantum states and classical information can be defined differently from the above.

[0206] The above EPR state is also called the Bell state, and the measurement result of the preceding qubit always affects the measurement of the succeeding qubit. In addition, all four of the above pure states are maximally entangled states and form the vertical basis of the two-qubit Hilbert space.

[0207] For entangled qubits with M>2 qubits or more, the GHZ state is as follows [Mathematical Equation 2].

[0208]

[0209] In [Equation 2], stands for tensor product operator.

[0210] When M=2 The GHZ state is generally expressed for M = 3. Sometimes, the GHZ state can be expressed by extending it to a system corresponding to d-dimension rather than 2-dimension.

[0211] continuous quantum error

[0212] In existing information systems, information is composed of '0' and '1', and errors are represented as '0' changing to '1' or '1' changing to '0'. Qubit can be thought of as a single point on the surface of the Bloch sphere. When an error occurs in a qubit in an existing information system, this case is called a bit flip error. This error means that the value of 'a' changes to the value of 'b', which means that when measuring a qubit, the measurement probability is changed differently from the original due to the error. Another type of error in an existing information system is class There is a phase flip error where the phase between them changes by 180 degrees. The error can occur with any phase along the X-axis or Z-axis, so quantum errors can have a continuous phase.

[0213] The decay of quantum information by measurement

[0214] Quantum information exists probabilistically, and quantum information collapses to a ground state the moment it is measured and cannot be restored to the state before measurement. The quantum information after measurement by the measurement operator is a probability and It collapses into one of the states of the basis that constitutes information. The collapsed information does not have the information of 'a' or 'b' and cannot return to the state before measurement.

[0215] From the perspective of quantum error-correcting codes, applying quantum error-correcting codes in quantum information systems requires generating codewords, estimating errors in the channel, and then restoring the information without measuring the information during the encoding and restoration process, or without measurements that would alter the information. In this process, continuously occurring quantum errors are digitized through measurements for error estimation.

[0216] quantum error channel

[0217] FIG. 11 illustrates an example of a quantum channel model based on environmental decoherence in a system applicable to the present disclosure.

[0218] Similar to classical communication, quantum communication processes can be affected by the quality of transmitted information due to imperfections present in the real environment. Interaction with this environment can lead to irreversible changes in the quantum state, a process known as decoherence. Environmental decoherence constitutes a major source of quantum state corruption, and can occur not only in quantum memory but also during quantum transmission or quantum processing. Figure 11 illustrates a quantum channel model widely used to model environmental decoherence.

[0219] Environmental decoherence can be described as the unwanted interaction of a qubit with its environment, more specifically, entanglement, which disrupts the coherent superposition of the underlying quantum state. For example, a qubit (or quantum system) loses energy due to its interaction with the environment. This can occur when a qubit's excited state decays due to spontaneous photon emission, or when a photon is lost or absorbed during transmission through an optical fiber. This type of decoherence can be modeled using an amplitude damping channel. Another example of environmental decoherence is known as dephasing or phase damping, which characterizes the loss of quantum information without energy loss. This can occur, for example, in the scattering of a photon or the perturbation of electronic states due to stray charges.

[0220] However, the amplitude damping channel or phase damping channel model For the qubit system, the resulting system is Because these channels have a Hilbert space of dimensionality, it may not be feasible to simulate them classically. For efficient classical simulation, the amplitude and phase decay channels are Pauli channels. can be approximated by the density operator The input state having is mapped to a state as shown in [Mathematical Formula 3] below.

[0221]

[0222] In [Equation 3], I, , , corresponds to a single-qubit Pauli operator. , , is the probability that Pauli X, Pauli Y, and Pauli Z errors will occur. Bit-flip errors corresponding to the Pauli X channel and bit-phase-flip errors corresponding to the Pauli Y channel are related to amplitude attenuation, while phase-flip errors corresponding to the Pauli Z channel are caused by phase attenuation. Most practical quantum systems are asymmetric channels, which are channels in which bit-flip, phase-flip, or bit-phase-flip errors dominate. Bit-flip, phase-flip, and bit-phase-flip errors occur with equal probability ( ) A special case of the Pauli channel is called a depolarizing channel and can be mathematically expressed as in [Mathematical Equation 4] below.

[0223]

[0224] If one of the qubits in the state passes through the depolarization channel, the fidelity Werner state is summarized as is defined as in [Mathematical Formula 5] below.

[0225]

[0226]

[0227]

[0228] Furthermore, quantum channels can consider not only quantum states but also errors occurring in operators used in quantum circuits. For example, errors and measurement errors related to the CNOT (controlled NOT operation) (=U) operator are mapped as shown in [Mathematical Equation 6] below. stands for Pauli I, X, Y, Z operators.

[0229]

[0230]

[0231]

[0232]

[0233]

[0234] In [Equation 6], means the pattern of errors, Is It means the probability of an error occurring, and means a measurement operator that includes measurement errors, stands for the measurement error rate.

[0235] quantum error correcting codes (QECCs)

[0236] Quantum error-correcting codes utilize additional qubits in addition to information qubits to generate codewords to preserve quantum information from errors. These codewords, which experience continuous errors, are then collapsed into codewords projecting discontinuous errors through measurement, after which the errors are detected and maintained as the original codeword. Most quantum error-correcting codes utilize stabilizer codes, which have properties similar to linear error-correcting codes used in digital systems.

[0237] stable operator group is a group of all stabilizers, each of which is a codeword vector is an operator with a +1 eigenvalue for the codeword vector The composition is as follows [Mathematical Formula 7].

[0238]

[0239] In [Equation 7], means a stable operator.

[0240] Stable operator group of quantum error-correcting codes can be expressed as [Mathematical Formula 8] below by a stabilizer generator.

[0241]

[0242] EPR status The stable operator group is as shown in [Mathematical Formula 9] below.

[0243]

[0244] An operator that is commutative with a safe operator is called a normalizer, and in quantum error correction codes, an operator that is not a stable operator among the normal operators is called a normalizer. ) is used to define a logical operator. The minimum distance of the quantum error correction code is determined by the smallest weight among the logical operators. is defined. In this case, the weight is the number of non-I Pauli operators included in the operator.

[0245] Quantum error correction codes with distance are identical to classical error correction codes in that they Errors with weight can be corrected, The dog's errors can always be detected whether an error has occurred or not.

[0246] for example, The stable operator generator and logical X, Z operators of quantum error correction codes are as follows [Mathematical Formula 10].

[0247]

[0248]

[0249]

[0250] Fig. 12 illustrates an example of an encoding circuit and a safety operator syndrome measurement circuit in a system applicable to the present disclosure. Specifically, Fig. 12a The encoding circuit of the quantum error correction code is shown in Fig. 12b. A safety operator syndrome measurement circuit is shown.

[0251] For error detection, quantum error correction codes perform measurements based on stability operators and correct errors according to the measurement result syndrome. Errors after measurement is a stable operator And when the anti-commute law holds true The measurement result will be -1, and if exchanged (commuted), it will be +1.

[0252] Unlike digital error-correcting codes, quantum error-correcting codes exhibit degeneracy. Therefore, different correctable errors can have the same syndrome value. Such codes are called degenerate codes. This degeneracy opens up the possibility that the performance of quantum error-correcting codes could surpass the limitations of classical error-correcting codes.

[0253] Error Digitization

[0254] Quantum errors occur continuously. However, by introducing stable operator measurements during the error correction process, continuous errors can be corrected through discontinuous Pauli error correction. Any 1-qubit unitary operator can be expressed as [Mathematical Formula 11] below, and after the stability operator measurement Errors collapse into one of I, X, Y, or Z.

[0255]

[0256] In [Equation 11], is a complex number,

[0257]

[0258] Satisfies.

[0259] Therefore, after the measurement of the stable operator, the error remains in the form of one of the Pauli errors discontinuously occurring in the codeword, and when the quantum error correction code correctly corrects the error, the error is corrected by performing a correcting operation that multiplies the collapsed Pauli error or the Pauli error by the form of the stable operator. The correcting operation can be performed physically, and in some cases, it is replaced by recording it in software instead of performing it physically.

[0260] threshold

[0261] Error rate of codeword after error correction code encoding ( ) Error rate of physical qubits before this encoding process ( ) is required to be lower than a specific physical error rate, as in [Mathematical Formula 12] below.

[0262]

[0263] The corresponding physical error rate is defined as a threshold, and in circuit-based quantum error correction codes (QECCs), the logical error rate, which is the error rate of the codeword, decreases exponentially through concatenation, and in topological quantum error correction codes (topological QECCs), the logical error rate decreases exponentially as the code distance increases. The logical error rate includes the error rate of fault-tolerant logical operations. The threshold has different values ​​depending on the type of quantum error correction code and the error occurrence channel modeling, and depending on the code, topological codes show a lower threshold than concatenated-based codes. Pseudo thresholds are also utilized depending on the channel modeling. Table 2 below shows the threshold estimates.

[0264] CodeThresholdGeometric Constraints Arbitrary Interaction 2D Nearest Neighbor arrary Arbitrary InteractionSurface Code 2D Nearest Neighbor arrary

[0265] quantum entanglement distillation protocol (EDP)

[0266] Quantum entanglement distillation protocol is a technique that utilizes a large number of entangled states with low fidelity, local operators and classical communication (LOCC), to share a small number of entangled states with high fidelity among many parties.

[0267] Various entanglement distillation protocols have been developed, including recurrence, quantum privacy amplification (QPA), breeding, and hashing. Recurrence and QPA protocols utilize classical communication bidirectionally, from Alice to Bob and from Bob to Alice, while breeding and hashing protocols utilize classical communication unidirectionally, from Alice to Bob. In general, two-way protocols have the advantage of operating in poor channel environments compared to one-way protocols, and one-way protocols utilize fewer resources than two-way protocols.

[0268] High-fidelity EPR states or entangled states generated by the entanglement distillation protocol can be utilized in quantum teleportation or quantum direct communication, quantum key distribution, and distributed quantum computing.

[0269] QPA protocol

[0270] Figure 13 illustrates an example of Alice and Bob performing the QPA protocol according to one embodiment of the present disclosure. The QPA protocol is a bidirectional protocol that utilizes two EPR states for each round, probabilistically generating a single EPR state with high fidelity.

[0271] As a first step, Alice and Bob apply the unitary operator shown in [Equation 13] below to the individual qubits of each EPR pair.

[0272]

[0273]

[0274]

[0275]

[0276] In [Equation 13], means the unitary operation that Alice performs, means the unitary operation that Bob performs.

[0277] The unitary course is and are mutually converted. That is, This is because the operations performed thereafter are good at correcting X errors and Y errors, but not Z errors, so the Z errors in the state after each round are converted to Y errors to correct them in the subsequent rounds.

[0278] In the second step, Alice and Bob perform the CNOT operator between the two EPR pairs, and finally measure the EPR state operated by the target qubit in the Z basis and share the measurement value through classical communication. If the shared measurement values ​​are the same, Alice and Bob determine that the EPR state operated by the control qubit has higher fidelity and use it thereafter. If the shared measurement values ​​are different, the EPR state operated by the control qubit is discarded. Therefore, the QPA protocol is probabilistically successful depending on the measurement result, and the success probability ( ) is the initial fidelity (F or F init ) is determined by.

[0279] When the initial EPR state passes through a symmetric depolarizing channel, the entangled state after passing through the channel is as shown in [Mathematical Formula 14] below.

[0280]

[0281] The probability of success when performing a single round using the Werner state of fidelity F And the output fidelity F' is as follows [Mathematical Formula 15].

[0282]

[0283]

[0284] FIG. 14 illustrates an example of the success probability of the QPA protocol in a system applicable to the present disclosure. FIG. 15 illustrates an example of the fidelity performance of the QPA protocol in a system applicable to the present disclosure.

[0285] Additionally, to achieve high fidelity, each round can be performed repeatedly, with at least The dog's EPR state is utilized.

[0286] Depending on the availability of memory in the QPA protocol, each round of the QPA protocol can be connected serially rather than in parallel, operating in pumping mode. When operating in entanglement pumping mode, instead of proceeding with a new round using the EPR state output from each round, the round is performed using the output EPR state of one round and the initial EPR state, which has the advantage of reducing the amount of quantum memory used. However, the increase in fidelity is low, and when fidelity saturates, it must be replaced with a round-out EPR pair.

[0287] FIG. 16 illustrates an example of the fidelity performance of the QPA protocol according to measurement errors in a system applicable to the present disclosure. FIG. 17 illustrates an example of the success probability of the QPA protocol according to measurement errors in a system applicable to the present disclosure. In FIG. 16 , the horizontal axis represents input fidelity, the vertical axis represents output fidelity, and p represents measurement error. In FIG. 17 , the horizontal axis represents input fidelity, the vertical axis represents success probability, and p represents measurement error.

[0288] As mentioned above in the quantum error channel, errors can occur related to the CNOT operator and the measurement operator in Fig. 13. Measurement errors can degrade the performance of the QPA protocol in terms of output fidelity and measurement probability. Referring to Fig. 16, as the error of the CNOT operator increases, the maximum value of the output fidelity decreases. Referring to Fig. 17, the error of the CNOT operator increases the minimum threshold of the input fidelity required for the output fidelity to be higher than the input fidelity. ) is increased, the measurement probability is confirmed to decrease. That is, the error of the measurement operator is less than the minimum threshold of the input fidelity ( ) and increase the probability of success ( or ) can be reduced. Therefore, to overcome such measurement errors, a technique can be proposed in which the sender and receiver utilize local ancilla qubits as in Fig. 18.

[0289] FIG. 18 illustrates an example of an entanglement distillation protocol utilizing measurement error filtering using local ancilla qubits according to one embodiment of the present disclosure. Referring to FIG. 18, a sender (Alice) and a receiver (Bob) can utilize local ancilla qubits to determine whether to use a qubit.

[0290] Step 1: The sender (Alice) and the receiver (Bob) are ρ (0) Set the qubit at position as the control qubit, and ρ (1) Set the qubit at the location as the target qubit, and perform a CNOT operation (controlled NOT operation) between the control qubit and the target qubit.

[0291] Step 2: The sender (Alice) prepares n-1 ancilla qubits, and the receiver (Bob) prepares m-1 ancilla qubits.

[0292] Step 3: The sender (Alice) and the receiver (Bob) send ρ (1) Set the qubit at the position as a control qubit, set each of the ancilla qubits as a target qubit, and perform a CNOT operation between the control qubit and the target qubit.

[0293] Step 4: The sender (Alice) measures n qubits in the Z basis, and the receiver (Bob) measures m qubits in the Z basis. Then, step 5-1 or step 5-2 is performed, resulting in ρ (0) It is decided whether to preserve it or not.

[0294] Step 5-1: Sender (Alice) and receiver (Alice) measure ρ if the measurement results are the same. (0), and if any of the measurement results are different, ρ (0) In [Table 3] below, we will use a detection technique to indicate that all measurement results must be the same to preserve the qubit.

[0295] Step 5-2: The sender (Alice) and the receiver (Alice) measure if multiple of the measurement results match, ρ (0) , and if any of the measurement results are different, ρ (0) In [Table 3] below, we will show that all measurement results are based on majority votes and that the qubits are preserved using a correcting technique.

[0296] At this time, the channel threshold according to the measurement error rate p, which is the number of ancilla qubits, can be expressed in the form of [Table 3] below.

[0297] P m channel Thresholdn=m=1n=m=2(Detecting)n=m=3(Detecting)n=m=3(Correcting)n=m=4(Detecting)n=m=5(Correcting)p=00.50.50.50.50.50.5p=0.030.540.5 010.5010.5020.5010.501p=0.050.60.5020.5010.5040.5010.501p=0.10 .620.5060.5010.5150.5010.503p=0.1640.720.5170.5020.5410.5010.51

[0298] recurrence protocol

[0299] The recurrence protocol, similar to the QPA protocol, is a bidirectional protocol that utilizes two EPR states in each round, probabilistically generating a single high-fidelity EPR state. The difference is that the first step performs a twirling operation, rather than a unitary operation. In this first step, Alice and Bob probabilistically apply the twirling operator to individual qubits of each EPR pair. Equation 16 below represents the twirling operation.

[0300]

[0301] In [Equation 16], B x means an operator that rotates π / 2 around the X-axis, and B y means an operator that rotates π / 2 around the Y-axis, and B z means an operator that rotates π / 2 around the Z-axis.

[0302] The twirling process transforms an arbitrary mixed state M into a Werner state This is the process for changing to .

[0303] In the second step, Alice and Bob perform the CNOT operator between the two EPR pairs, and finally measure the EPR state operated as the target in the Z basis and share the measurement value through classical communication. If the shared measurement value determines that the EPR state operated as the control qubit has higher fidelity, the EPR state operated as the control qubit is utilized, and if the shared measurement value is different, the EPR state operated as the control qubit is discarded. Therefore, the recurrence protocol is probabilistically successful depending on the measurement result, and the success probability ( ) is determined by the initial fidelity. When a single round is performed using the Werner state of fidelity F, the success probability is as follows [Mathematical Formula 17].

[0304]

[0305] Additionally, to achieve high fidelity, each round can be performed repeatedly, with at least The dog's EPR state is utilized.

[0306] fidelity Output fidelity when performing a single round using the Werner state is as follows [Mathematical Formula 18].

[0307]

[0308] Depending on the availability of memory in the recurrence protocol, each round of the recurrence protocol can be connected serially rather than in parallel, operating in pumping mode. When operating in entanglement pumping mode, instead of proceeding with a new round using the EPR state output from each round, the round is performed using the output EPR state of one round and the initial EPR state, which has the advantage of reducing the use of quantum memory. However, the increase in fidelity is low, and when the fidelity saturates, it must be replaced with a round-out EPR pair.

[0309] Due to the difference in operators used in the first step, it has lower fidelity performance than the QPA protocol when an arbitrary state is used as the input state.

[0310] double selection protocol

[0311] Figure 19 illustrates an example of the structure of a dual-selection protocol according to one embodiment of the present disclosure. The dual-selection protocol is a bidirectional protocol similar to the recurrence or QPA protocol, but instead of utilizing two EPR states in each round, it utilizes three EPR states to create one entangled state.

[0312] In each round, the double-selection protocol procedure can be performed as follows.

[0313] Step S1901: Each sender and receiver (e.g. Alice and Bob) have three entangled states (ρ (0) , ρ (1) , ρ (2) ) among ρ (0) with control qubit, ρ (1) Each CNOT is performed with the target qubit as the target qubit.

[0314] Step S1903: Each sender and receiver have ρ (2) The qubit of the position is the control bit, ρ (1) Perform CNOT with the qubit of the position as the target bit.

[0315] Step S1905: Each sender and receiver have ρ (1) Measure the qubits in the Z basis, and ρ (2) Measure the qubits in the X basis.

[0316] Step S1907: Each sender and receiver share their measurement results with each other, and if the sender's X basis measurement result and the receiver's X basis measurement result are the same, and the sender's Z basis measurement result and the receiver's Z basis measurement result are the same, then ρ (0) Preserve the qubit of the position. Otherwise, if at least one of the X basis measurement results or the Z basis measurement results is inconsistent, ρ (0) Discard the qubit at the location.

[0317] When additional rounds are performed, the transmitter and receiver may repeat steps S1901 to S1907 by applying the Hamadad operator to each input state, changing the positions of the control bits and target bits of the CNOT, and transforming the measurement basis.

[0318] In the case of the aforementioned dual selection protocol, it is known that it has the characteristics of a high channel threshold, high maximum fidelity, and a wide gate working range compared to the QPA or recurrence protocol.

[0319] Here, the channel threshold is the fidelity (ρ) that is input when the EPR state is preserved in the entanglement distillation protocol (EDP) or entanglement purification protocol (EPP). (0) , ρ (1) To increase the fidelity of the input state, it means the fidelity of the input state that is required at a minimum.

[0320] Fig. 20 illustrates an example of maximum and minimum fidelity performance according to the error rate of the CNOT operator and the measurement operator in a dual selection or single selection circuit according to an embodiment of the present disclosure. In Fig. 20, the X-axis represents the error rate of the CNOT operator and the measurement operator utilized in the dual selection or single selection circuit, and the Y-axis represents the fidelity. Here, the X-axis represents the error rate of the operator utilized in the EDP operation, is the CNOT operator described above in [Equation 6]. It means the sum of (eg . is the measurement error rate described above in [Mathematical Formula 6] . The Y-axis represents the threshold value, and in Fig. 20 was written as . Same operator error Double choice in the environment This single choice It has a lower channel threshold than the lower one. Therefore, it is confirmed that the fidelity required for the entanglement state in dual selection is lower.

[0321] Maximum fidelity is the maximum fidelity that can be achieved by performing multiple rounds of the EDP protocol. In Fig. 20. is expressed as . Same operator error Double choice in the environment A single choice It can be verified that entangled states with higher fidelity can be created at higher levels.

[0322] The gate operating range refers to the error rate range of the CNOT and measurement operators when the EDP protocol operates properly. As shown in Fig. 21, the operating range of dual selection can be confirmed to be wider than that of single selection.

[0323] Therefore, a dual-selection circuit has an advantage over a single-selection circuit in an environment where gate errors exist. Therefore, when a dual-selection circuit is utilized, gate errors are generally considered. When the X measurement results and the Z measurement results of the transmitter and receiver are identical and the EPR state is preserved, the fidelity of the preserved EPR state is as shown in Fig. 22, and the error rate of the gate ( ) and the fidelity preserved varies depending on the gate error rate, and the lower the gate error rate, the higher the fidelity preserved, and even when a gate error occurs, an entangled state with high fidelity can be created within a certain range.

[0324] Furthermore, a technique can be proposed to recycle entangled states without discarding them when measurement results in a dual-selection circuit are inconsistent. Entangled states with inconsistent measurement results can be reused through a measurement error filtering technique utilizing the local ancilla described above in Fig. 18.

[0325] Figure 23 shows the fidelity according to the measurement results in the dual selection protocol according to one embodiment of the present disclosure. In Figure 23, the gate error rate is It was assumed that the environment was . Referring to Fig. 23, the gate error rate is The channel threshold of the dual-selection protocol in this environment is It is confirmed that the dual-choice protocol can operate efficiently in environments where the initial fidelity is greater than or equal to 0.553 and less than or equal to 0.984. For the dual-choice protocol, the fidelity of entangled states with inconsistent measurement results can exceed 0.553 in some initial fidelity ranges. Entangled states with fidelity greater than 0.553 can be further enhanced through an additional dual-choice EPP process. Therefore, entangled states with inconsistent measurement results can be reused.

[0326] Fig. 24 illustrates an example of one round in a procedure in which a first device and a second device determine reuse based on a dual-selection EDP according to an embodiment of the present disclosure. Referring to Fig. 24, if the measurement results in the dual-selection EDP procedure do not match, discarded qubits can be recycled. For example, if the output fidelity If satisfies , qubits can be recycled, and the specific procedure is as follows.

[0327] In step S2401, an EPR pair is created. The EPR pair can be created by the sender, receiver, or a third device. A total of three EPR pairs can be created.

[0328] In step S2403, the sender transmits one qubit from the EPR pair. If the receiver generated an EPR pair in step S2401, the receiver can transmit one qubit from the EPR pair to the sender. Furthermore, if the EPR pair was generated by a third device, the third device can split the EPR pair and transmit it to either the sender or the receiver.

[0329] In step S2405, the sender and receiver perform a CNOT gate for the dual-selection EDP. For example, the sender and receiver have three entangled states (ρ (0) , ρ (1) , ρ (2) ) among ρ(0) as a control bit, ρ (1) Each performs CNOT with ρ as the target bit, and the sender and receiver are (2) The qubit of the position is the control bit ρ (1) Each CNOT is performed with the qubit of the position as the target bit.

[0330] At step S2407, the transmitter and receiver perform Z and X measurements. For example, the transmitter and receiver may measure ρ (1) Each qubit in the position is measured in the Z basis and ρ (2) Each qubit in the position can be measured in X basis.

[0331] In step S2409, the transmitter and receiver share the measurement results with each other. The transmitter and receiver compare the measurement results and, based on the fidelity estimation, calculate ρ as follows. (0) It can decide whether to preserve, recycle, or discard the qubits in the position.

[0332] If the sender's X measurement result and the receiver's X measurement result match, and the sender's Z measurement result and the receiver's Z measurement result match, step S2411 is performed. That is, the sender and receiver are ρ (0) Decide to preserve the qubit of the position.

[0333] If the X measurement results are inconsistent, the Z measurement results are inconsistent, or both are inconsistent, ρ (0) The fidelity of the entanglement state of the position is determined by the channel threshold ( ) is higher than ρ, then step S2413 is performed. That is, the sender and receiver are ρ (0) Decide to recycle the space. Therefore, ρ (0) The sender and receiver can store the qubits in the slot. The stored reusable qubits can be used to perform additional EDPs along with other reusable qubits.

[0334] If the X measurement results are inconsistent, or the Z measurement results are inconsistent, or both are inconsistent, ρ (0)The fidelity of the entanglement state of the position is determined by the channel threshold ( ) is lower than ρ, then step S2415 is performed. That is, the sender and receiver are ρ (0) Discard the qubit of the position.

[0335] Hashing protocol

[0336] Figure 25 illustrates an example of a hashing protocol based on QECCs according to an embodiment of the present disclosure. The hashing protocol is a one-way protocol that utilizes a decryption circuit of a quantum error correction code to distill it into an entangled state. In the first step, Alice and Bob encode and decrypt quantum error correction codes (QECCs) using circuits related to encoding and decryption. ) is performed on each EPR state, and a specific qubit is measured, similar to syndrome extraction. In the second step, Alice shares the measurement result with Bob, and Bob performs a correction operator according to the product pattern of his measurement result and Alice's measurement result. The correction operator is determined by the correction operator according to the syndrome of the quantum error correction code, and in the hashing protocol, the syndrome is obtained as the product of the measurement results. If the initial fidelity is greater than a threshold value, the unmeasured EPR state has improved fidelity.

[0337] In the case of the EPR state, since it is a CSS state and an H-invariant state (CSS-H invariant state) that is closed for the H transformation of the fixed operator, a decryption circuit of an arbitrary error correction code is utilized. Since it is a CSS state like a 3-qubit GHZ state utilized by multiple parties, but is an H-variable state (CSS-H variant), a decryption circuit of a CSS quantum error correction code must be utilized, and in the case of a non-CSS state, a CSS-H code, that is, a quantum error-definite code in which a logical H is expressed in the form of a tensor product of individual (transversal) H, must be utilized. Here, the CSS state is a CSS state for each fixed operator It means a state that can be expressed by one of the Pauli operators (X or Y or Z).

[0338] Breeding Protocol

[0339] The breeding protocol is a one-way protocol, similar to the hashing protocol. In the breeding protocol, This is a protocol that improves n>m low-fidelity EPR states to high-fidelity by utilizing m pure entangled states when Alice and Bob share a pure entangled state. In this case, to distill one EPR state, Von-Neumann entropy A sufficient number of pure EPR states are required, and theoretically, the entropy of all n EPR states can be removed to create a pure entangled state.

[0340] To perform the breeding protocol, first, Alice and Bob perform CNOT operations on n impure EPR states and m pure EPR states for a specific BXOR detection process, and then measure the m pure EPR states. Second, Alice shares the measurement results with Bob, and Bob performs a correction operator according to the product pattern of his measurement results and Alice's measurement results. If the initial fidelity is greater than a threshold value, the unmeasured EPR states have a fidelity of 1.

[0341] The fidelity performance of the protocol output value can be determined depending on how the BXOR process is performed, and the BXOR circuit can be determined based on the decoding circuit of the quantum error correction code in the BXOR detection process.

[0342] The above-mentioned hashing protocol and breeding protocol have a high yield (the number of EPR states required to obtain one EPR state with Fidelity 1) compared to QPA or recurrence, and the yield is expressed as in [Mathematical Formula 19] below.

[0343]

[0344] In [Equation 19], stands for Von-Neumann entropy.

[0345] If necessary, the breeding / hashing protocol can be utilized in conjunction with QPA / recurrence.

[0346] Unidirectional or bidirectional distinction of entanglement distillation protocol (EDP)

[0347] The bidirectional (recurrence or QPA protocol) or unidirectional EDP technique consists of a transceiver, a quantum channel, and a classical channel, as shown in Fig. 26 and Fig. 28.

[0348] (1) Bidirectional EDP technique

[0349] Figure 26 illustrates an example of the structure of a single round of a bidirectional EDP technique according to one embodiment of the present disclosure. In a single round, the bidirectional EDP technique operates as follows.

[0350] At step S2601, the sender (Alice) uses a nonlinear element to generate two EPR states.

[0351] In step S2603, the sender transmits one qubit from each EPR state to the receiver (Bob) (two in total). The quantum channel includes the generation defect of the EPR state, a wireless photonic channel, and a quantum memory error channel.

[0352] In step S2605, the sender and receiver perform a unitary operation by grouping two EPR states. If no Werner state is generated after the quantum channel, the Werner state Unitary operations for conversion to and performs CNOT operations.

[0353] In step S2607, the sender and receiver measure some qubits. In step S2605, the qubit used as the target qubit for the CNOT operation is measured. FIG. 27 illustrates an example of a process in which the sender and receiver measure qubits according to one embodiment of the present disclosure.

[0354] In step S2609, the receiver transmits its measurement result (1 bit) to the sender, and the sender transmits its measurement result (1 bit) to the receiver over the classical channel.

[0355] In step S2611, the sender and receiver compare their own measurement result bits with the other party's measurement result bits received via the classical channel. If the shared measurement results do not match, the sender and receiver discard the EPR state not used in the measurement and repeat steps S2601 through S2609. If the measurement results match, the corresponding qubit is preserved.

[0356] If an EPR state with higher fidelity is required, the sender and receiver perform steps S2303 to S2311 using the preserved qubits in a single round. Minimum when performing a round The EPR state must be shared between the sender and receiver, and additional qubits are required depending on the measurement results. Ultimately, a single high-fidelity EPR state is generated.

[0357] (2) One-way EDP technique

[0358] FIG. 28 is a diagram illustrating an example of the structure of a unidirectional EDP technique in a system applicable to the present disclosure.

[0359] At step S2801, In the case of a one-way EDP utilizing quantum error correction codes, the sender (Alice) utilizes a nonlinear element, Creates an EPR state of the dog.

[0360] At step S2803, the sender transmits one qubit from each EPR state to the receiver (Bob) (total (dog). At this time, the quantum channel includes the generation defect of the EPR state, the wired and wireless photon channel, and the quantum memory error channel.

[0361] At step S2805, the sender and receiver are unitary operators, and in the case of unidirectional EDP, the promised Performs a decoding circuit or BXOR circuit of a quantum error correction code.

[0362] At step S2807, the sender and receiver each The qubit of the dog is measured. At this time, the measured qubit is a BXOR circuit or The location of the measurement qubit is determined based on the properties of the quantum error correction code.

[0363] At step S2809, the receiver reports the measurement results to the sender ( bits) are transmitted over the classical channel.

[0364] In step S2811, the sender estimates the syndrome or error from the measurement result of the receiver and performs a correction operation for error correction on the qubits that were not measured in step S2807. The correction operator is determined based on the product pattern of the measurement results, and the Pauli operator One of the pair of EPR states operates on the sender's qubit.

[0365] Finally, in the case of recurrence or QPA bidirectional EDP, one high-fidelity EPR state is preserved. In the case of one-way EDP using error correction codes The high EPR state of the dog is preserved.

[0366] Quantum entanglement distillation can correct channel errors in the entangled state shared by Alice and Bob through the above process. This occurs by transferring a portion of the entanglement from multiple entangled states to a smaller number of entangled states, utilizing classical channels.

[0367] Thus, EDP aims to create entangled states with high fidelity. Currently known QPA / recurrence protocols have the limitation of requiring significant resources to generate the desired fidelity, and hashing / breeding protocols based on quantum error-correcting codes operate only at high initial fidelity.

[0368] Adaptive mode EDP protocol

[0369] Fig. 29 illustrates an example of the basic structure of an adaptive mode EDP technique according to an embodiment of the present disclosure. In order to reduce the required resources of the existing QPA technique and to expand the fidelity range in which the error correction code-based EDP operates, the method of Fig. 29 is applied, which selectively utilizes a quantum error correction code decoding circuit or a QPA circuit in step S2905 (i.e., a unitary operation process), but performs a discarding process similar to a bidirectional EDP for some syndrome patterns of QECCs in step S2911 (i.e., a correction operation / discarding step).

[0370] FIG. 30 illustrates an example block diagram of a QECCs-based bidirectional EDP technique according to one embodiment of the present disclosure. The process of the adaptive mode QECCs-based EDP technique proposed in the present disclosure is as follows.

[0371] In step S3001, if the QPA mode is selected as the adaptive mode, the bidirectional EDP protocol of Fig. 26 is performed. The following description is the process of the QECCs-based bidirectional EDP technique as the adaptive mode, and the process of dividing the QPA mode and the QECCs-based bidirectional EDP mode will be described later in the fidelity-based parameter estimation process.

[0372] At stage S3003, When utilizing QECCs, the sender (Alice) utilizes nonlinear elements Creates an EPR state of the dog.

[0373] In step S3005, the sender transmits one qubit from each EPR state to the receiver (Bob). At this time, the quantum channel includes the generation defect of the EPR state, a wireless photonic channel, and a quantum memory error channel.

[0374] In step S3007, the sender and receiver are committed to performing unitary operations as unitary operations. Performs the decoding circuit of QECCs.

[0375] At step S3009, the sender and receiver each Measure the qubit of the dog. At this time, the measured qubit is The location of the measurement qubit is determined based on the properties of the QECCs.

[0376] In step S3011, the receiver and the transmitter transmit the measurement results to each other. At this time, each Each bit is transmitted through a classical channel.

[0377] In step S3013, the sender and receiver multiply their own measurement results with the measurement results of the other party that they have received, and according to the pattern of the multiplied values, the transmitter and receiver do not measure in step S3009. After performing a correction operation on the EPR state of the dog, the EPR state is either preserved or discarded. If the EPR state is discarded, steps S3003 to S3011 are performed again. is Alice's measurement result, is Bob's measurement result, the product of the measurement results ( ) is the promised pattern If it belongs to , step S3015 is performed.

[0378] At step S3015, the sender has not measured the EPR state. performs a correction operation on its own qubit. At this time, the probability of performing the correction operation is is defined as . The correction operation is According to the pattern of It is determined as one of them, and operates on the sender's qubit among the EPR pair states of the unmeasured EPR state.

[0379] pattern Variables that determine silver Correctable by quantum error correcting codes Errors to be corrected in EDP using QECCs in adaptive mode among the errors ( ) and is agreed upon between the sender and receiver in advance. Errors to be corrected ( ) is defined as in [Mathematical Formula 20] below.

[0380]

[0381] For example, using [[,7,1,3]] QECCs In this case, the promised pattern is the union of the syndrome pattern in which no error occurred and the syndrome pattern in which one error occurred. is created, If we have a stable operator, then is created

[0382]

[0383] After correcting the EPR state through an appropriate Pauli operation according to the syndrome, the EPR state is preserved, and if a product of measurement results other than S, i.e. a syndrome, is generated, the unmeasured EPR state is discarded.

[0384] Fidelity (when using QECCs in adaptive mode) )Performance and success probability The performance is as shown in Figs. 31 to 34.

[0385] For quantum error correction codes There is a syndrome pattern of dogs, If the value of is 1, there are 22 patterns ( ) to correct errors and discard the EPR state if any other pattern is measured.

[0386] Figures 31 and 32 show the EDP performance when [[7,1,3]] QECCs are used bidirectionally, and Figures 33 and 34 show the EDP performance when [[5,1,3]] QECCs are used bidirectionally. Specifically, Figure 31 shows the fidelity performance of the output EPR state when [[7,1,3]] QECCs are used. In Figure 31, the line represented by [[7,1,3]] QECCs corresponds to the case where all syndromes are corrected in [[7,1,3]] QECCs. [[7,1,3]] t corr For the line indicated by =1, for syndrome patterns where errors are estimated to be 0 or 1, the EPR state is preserved after correcting the error, and for other syndrome patterns, the EPR state is discarded. [[7,1,3]] t corr For the line indicated by =0, the EPR state is preserved for syndrome patterns in which no error occurs, and the EPR state is discarded for other syndrome patterns. For the line indicated by , it means that the fidelity does not change, It is efficient to perform EDP at an initial fidelity above the line indicated by . For example, when utilizing [[7,1,3]] QECCs (e.g. [[7,1,3]] QECCs), it is efficient to operate at an initial fidelity of 0.92 or higher.

[0387] Figure 32 illustrates an example of the probability of preserving the output EPR state when utilizing [[7,1,3]] QECCs according to one embodiment of the present disclosure. For the line represented by [[7,1,3]] QECCs, it remains 1 because the EPR state is preserved for all syndrome patterns. [[7,1,3]] t corr For the line represented by =1, it is the probability of preserving the EPR state after correction for an error with 0 or 1 syndrome pattern. [[7,1,3]] t corrFor the line indicated by =0, it is the probability of preserving the EPR state for a syndrome pattern in which no error occurred. Figures 33 and 34 illustrate the fidelity and success probability when QECCs are [[5,1,3]], using the same structure as Figures 31 and 32.

[0388] In this disclosure, for the convenience of explanation, the method of preparing and distributing qubits in each EPR state by the sender (Alice) and the receiver (Bob) will be described as follows: the sender prepares qubits in each EPR state and transmits one qubit from each EPR state from the sender to the receiver. However, the qubit generation and distribution method applicable to the present disclosure is not limited to this, and various methods may be applied. For example, the method of preparing an EPR state in a third-party node and transmitting it to a first node (e.g., Alice) and a second node (e.g., Bob) may be combined with or substituted for the procedures described in the present disclosure. As another example, the method of preparing an EPR state in the receiver and transmitting one qubit from the EPR state to the sender may also be applied in the same manner.

[0389] Average fidelity-based parameter estimation process

[0390] When using QECCs in adaptive mode, the fidelity of the EPR state generated after the EDP process is the target fidelity. The minimum EPR state (fidelity) satisfying ) to utilize the parameters of QECCs and parameters of adaptation mode Or To estimate , an optimization process according to [Mathematical Formula 21] is performed.

[0391]

[0392]

[0393] Fidelity of the QPA protocol results The number of qubits utilized after a round and the final fidelity are determined as shown in [Mathematical Formula 22] below.

[0394]

[0395]

[0396]

[0397]

[0398] In [Equation 22], represents the success probability of the i-th round, respectively. represents the fidelity after the ith round.

[0399] When QECCs are used in adaptive mode, the fidelity is as follows [Mathematical Formula 23].

[0400]

[0401]

[0402] In [Equation 23], and has a boundary as shown in [Mathematical Formula 24] below.

[0403]

[0404]

[0405]

[0406]

[0407] [[7,1,3]], [[5,1,3]] When using QECCs in adaptive mode, the actual fidelity ( )performance, Performance estimation (Est) based on performance and boundary is as shown in FIGS. 35 to 38. Specifically, FIG. 35 shows an example of fidelity estimation of an adaptation mode EDP based on [[7,1,3]] QECCs according to an embodiment of the present disclosure. FIG. 36 shows an example of fidelity estimation of an adaptation mode EDP based on [[5,1,3]] QECCs according to an embodiment of the present disclosure. FIG. 37 shows an example of success probability estimation of an adaptation mode EDP based on [[7,1,3]] QECCs according to an embodiment of the present disclosure. FIG. 38 shows an example of success probability estimation of an adaptation mode EDP based on [[5,1,3]] QECCs according to an embodiment of the present disclosure.

[0408] In Figures 35 and 36, Est [[7,1,3]] t corr =1, Est [[7,1,3]] t corr =0, Est [[5,1,3]] t corr =1, Est [[5,1,3]] t corr The line marked as =0 represents an estimate of the output fidelity (F'), and [[7,1,3]] t corr =1, [[7,1,3]] t corr =0, [[5,1,3]] t corr =1, [[5,1,3]] t corr The line indicated by =0 represents the actual value of the output fidelity. Also, t corr In the case of =1, the EPR state is corrected and preserved for syndrome patterns estimated to be 0 or 1, and t corr =0 means that the EPR state is preserved for syndrome patterns in which no error occurs, and the EPR state is discarded in other cases.

[0409] In Figures 37 and 38, Est [[7,1,3]] t corr =1, Est [[7,1,3]] t corr =0, Est [[5,1,3]] t corr=1, Est [[5,1,3]] t corr The line represented by =0 is the EDP success probability (P succ ) means the estimate of [[7,1,3]] t corr =1, [[7,1,3]] t corr =0, [[5,1,3]] t corr =1, [[5,1,3]] t corr The line indicated by =0 represents the actual value of the EDP success probability. Also, t corr In the case of =1, the EPR state is corrected and preserved for syndrome patterns estimated to be 0 or 1, and t corr =0 means that the EPR state is preserved for syndrome patterns in which no error occurs, and the EPR state is discarded in other cases.

[0410] [Table 4] to [Table 6] below show the specific goal fidelity ( or ) is the result of the optimal mode and parameter estimation to satisfy the requirements. The mode is determined among the adaptive modes QPA, QECCs (QECCs-based bidirectional EDP technique), and detecting, and refers to the EDP operation method that utilizes the minimum resources in each initial fidelity. 'QPA' refers to the QPA mode, and 'QECCs' refers to the QECCs-based bidirectional EDP protocol. In this case, 'Detecting' is a bidirectional EDP protocol based on QECCs. This means that Num_EPR is the number of EPR states utilized in each mode. When a bidirectional protocol based on QECCs is utilized in mode, the optimal code and number of errors to correct ( ) and is an estimated value using the bound. Gain is the number of qubits reduced when a bidirectional protocol based on QECCs is used compared to QPA, and QPA rounds is the number of rounds when used in QPA mode.

[0411] [Table 4] is EDP ​​protocol and spec in corresponds to [Table 5] Optimal EDP protocol and spec in corresponds to [Table 6] EDP ​​protocol and spec in It corresponds to .

[0412] 1- modeNum_EPRnkd GainQPA 라운드0.851.00E-06'QPA'792.9544'-''-''-''-''-'60.861.00E-06'QPA'654.7041'-''-''-''-''-'60.871.00E-06'QPA'542.753'-''-''-''-''-'60.881.00E-06'QPA'156.4529'-''-''-''-''-'50.891.00E-06'QPA'135.3346'-''-''-''-''-'50.91.00E-06'QPA'117.3719'-''-''-''-''-'50.911.00E-06'QPA'102.049'-''-''-''-''-'50.921.00E-06'QPA'88.9412'-''-''-''-''-'50.931.00E-06'QECCs'74.7453291111-2.9528'-'0.941.00E-06'Detecting'47.839927390-20.1893'-'0.951.00E-06'QECCs'23.797282101-35.8961'-'0.961.00E-06'QECCs'20.2648282101-32.2237'-'0.971.00E-06'QECCs'11.162427391-10.1298'-'0.981.00E-06'Detecting'8.285525570-11.047'-'0.991.00E-06'Detecting'4.697816450-3.8568'-'

[0413] 1- modeNum_EPRnkd GainQPA 라운드0.851.00E-07'QPA'792.9544'-''-''-''-''-'60.861.00E-07'QPA'654.7041'-''-''-''-''-'60.871.00E-07'QPA'542.753'-''-''-''-''-'60.881.00E-07'QPA'451.691'-''-''-''-''-'60.891.00E-07'QPA'377.3025'-''-''-''-''-'60.91.00E-07'QPA'316.2845'-''-''-''-''-'60.911.00E-07'QPA'102.049'-''-''-''-''-'50.921.00E-07'QPA'88.9412'-''-''-''-''-'50.931.00E-07'QPA'77.6981'-''-''-''-''-'50.941.00E-07'QECCs'61.1904291111-6.8388'-'0.951.00E-07'QECCs'50.8073291111-8.8858'-'0.961.00E-07'QECCs'20.2648282101-32.2237'-'0.971.00E-07'QECCs'17.6041282101-28.6431'-'0.981.00E-07'QECCs'10.01227391-30.816'-'0.991.00E-07'Detecting'5.186921560-12.3894'-'

[0414] 1- modeNum_EPRnkd GainQPA Round0.9991.00E-06'Detecting'1.921317940-2.0947'-'0.99911.00E-06'Detecting'1.91817940-2.0964'-'0.99921.00E-06'Det ecting'1.914817940-2.098'-'0.99931.00E-06'Detecting'1.911517940-2.0997'-'0.99941.00E-06'QECCs'1.8235311752-2.18 61'-'0.99951.00E-06'QECCs'1.8235311752-2.1845'-'0.99961.00E-06'QECCs'1.8235311752-2.1829'-'0.99971.00E-06'QECCs '1.8235311752-2.1813'-'0.99981.00E-06'QECCs'1.8235311752-2.1797'-'0.99991.00E-06'Detecting'1.669215930-2.3324'-'

[0415] In this disclosure, for the convenience of explanation, the method of preparing and distributing qubits in each EPR state by the sender (Alice) and the receiver (Bob) will be described as follows: the sender prepares qubits in each EPR state and transmits one qubit from each EPR state from the sender to the receiver. However, the qubit generation and distribution method applicable to the present disclosure is not limited to this, and various methods may be applied. For example, the method of preparing an EPR state in a third-party node and transmitting it to a first node (e.g., Alice) and a second node (e.g., Bob) may be combined with or substituted for the procedures described in the present disclosure. As another example, the method of preparing an EPR state in the receiver and transmitting one qubit from the EPR state to the sender may also be applied in the same manner.

[0416] Additionally, depending on the environment, the parameter estimation process can be performed in one of the following scenarios ①, ②, and ③.

[0417] ① When the base station and terminal share a table based on initial fidelity (e.g., Table 4, Table 5, Table 6, etc. are shared in advance)

[0418] ② In an environment where tables are not shared, when the base station and terminal each perform parameter estimation according to initial fidelity

[0419] ③ In an environment where tables are not shared, when the base station performs parameter estimation and informs the terminal of the parameter values.

[0420] In case ①, the initial fidelity measured by the base station and the terminal ( ) is not in the pre-shared table, the initial fidelity is low or equal ( ) is assumed and the parameters are utilized. For example, if the base station and the terminal share [Table 4] but the measured initial fidelity is 0.935, the initial fidelity is 0.93. By utilizing the parameters of , . The Look-up Table corresponding to the optimal EDP protocol and spec exemplified here is the initial fidelity ( ), goal fidelity It can be configured individually according to the method, and it is assumed that the base station and the terminal both have individual look-up tables in a pre-arranged manner.

[0421] In scenarios ② and ③, the proposed technique is used based on the measured initial fidelity. Parameters can be estimated. Initial fidelity is measured by, and goal fidelity is In case ②, the base station and the terminal perform the optimization function. The values ​​of each are derived and the quantum error correction code decoding circuit is performed without exchanging additional classical information for parameter estimation. In case of ③, the base station performs parameter estimation. The value is transmitted to the terminal, and then quantum error correction code decoding and subsequent processes are performed.

[0422] In case ①, the base station and the terminal require additional memory for table storage, but can perform adaptive mode EDP without additional communication for optimization function and parameter exchange.

[0423] In case ②, the base station and terminal do not require additional memory for table storage, but complexity is added for optimization in the base station or terminal.

[0424] In case ③, the base station and terminal do not require additional memory for table storage, but the base station adds complexity for optimization and classical communication for parameter exchange.

[0425] In the above scenarios, it is assumed that the initial fidelity has been measured by the base station and the terminal in advance, using a predefined method, prior to the entanglement distillation process. In this case, ① and ② require that both the base station and the terminal share the same initial fidelity measurements through the initial fidelity measurement process. In ③, only the base station estimating the parameters needs to know the initial fidelity. Therefore, ① and ② involve sharing the initial fidelity measurements during the initial fidelity measurement process.

[0426] In the above-described method, when both the base station and the terminal have the look-up table, but the information on the initial fidelity is only available to the base station or the terminal, the base station or the terminal with the initial fidelity can derive only the index corresponding to the optimal EDP protocol and specification from the look-up table and transmit the index to the terminal or base station without the initial fidelity, thereby operating the optimal protocol. For example, when the initial fidelity is known only to the base station and the index of QPA is 0 and the index of QECCs is 1, If so, send 0, When 1 and after Transmits values ​​to the terminal.

[0427] In [Equation 21], if there are constraints other than the initial fidelity and target fidelity, they can be added to the constraint conditions of the optimization problem. For example, there is a limit on the number of EPR states that can be transmitted and received at a time. If the condition occurs, optimization is performed using the following [Mathematical Formula 25].

[0428]

[0429]

[0430]

[0431] In the case of [Table 4] to [Table 6] mentioned above, is the optimized parameter value within the constraints. The Look-up table corresponding to the optimal EDP protocol and spec can be determined in various ways, and the Look-up table can be determined based on the initial fidelity ( ), goal fidelity In addition, the number of EPR states that can be transmitted and received (N) can be individually determined. This disclosure assumes that the base station and the terminal both have individual lookup tables in a pre-agreed manner.

[0432] EDP ​​and fidelity-based parameter estimation process using adaptive mode

[0433] FIG. 39 illustrates an example of the overall procedure of the adaptive mode EDP technique according to one embodiment of the present disclosure. Specifically, FIG. 39 is an overall block diagram integrating the entanglement distillation technique via the aforementioned QPA and the entanglement distillation technique via two-way QECCs.

[0434] In step S3901, in an environment where the initial fidelity and the target fidelity are given as constraints, it is decided through prediction of the final consumed resources whether to perform entanglement distillation through QPA or through bidirectional QECCs for the base station and the terminal, respectively. In case of utilizing bidirectional QECCs EDP, the base station and the terminal determine the QECCs parameters and When utilizing QPA, the base station and terminal share the number of QPA rounds.

[0435] If bidirectional QECCs are utilized, the base station and terminal perform step S3903. Step S3903 may perform the process of the QECCs-based bidirectional EDP technique described above in FIG. 30. Accordingly, steps S3003 to S3015 may be performed by the base station and terminal.

[0436] If QPA is utilized, the base station and terminal perform step S3905. Step S3905 may perform the bidirectional EDP protocol technique described above in FIG. 26. Accordingly, steps S2601 to S2611 may be performed by the base station and terminal.

[0437] Minimum fidelity sharing in EDP used in adaptive mode

[0438] When performing a single round of EDP protocol in QPA, one high-fidelity EPR pair is generated by utilizing two low-fidelity EPR pairs. At this time, in order to measure whether a high-fidelity EPR pair has been generated, the sender and receiver each measure one EPR pair they have and share the measurement result. That is, as shown in Fig. 27, the sender and receiver each measure the second qubit and share the measurement result ( ) is shared. If the EPR pair is not measured, one EPR pair is preserved, otherwise one EPR pair is discarded. At this time, as shown in [Table 4] to [Table 6] described above, various numbers of rounds are performed depending on the input fidelity and target fidelity. The EPR pair generated after the round always satisfies the target fidelity. [Table 7] below shows the product of the measurement results depending on various input fidelities. ) indicates fidelity to the protocol. In the actual protocol, In this case, only the EPR state is preserved and utilized. [Table 7] below shows the fidelity according to the measurement results in the QPA protocol.

[0439] input Fidelity ( ) Fidelity in case of Fidelity in case of 0.60.6204380.250.70.7352940.250.80.838150.250.90.9263960.25

[0440] In contrast, when performing a bidirectional protocol based on QECCs, the syndrome ( )this Even if it is included in the set of syndromes that are assumed to be errors below, the fidelity of the preserved EPR pair varies depending on the syndrome pattern. For example, the [[5,1,3]] quantum error correcting code When utilized, EPR pairs are preserved when a total of 16 syndrome patterns are generated. The fidelity of the EPR pairs preserved according to each syndrome pattern is as follows. [Table 8] shows [[5,1,3]], When utilizing quantum error correction codes, the fidelity of an EPR pair according to the syndrome pattern is represented. In this case, S in [Table 8] is defined as follows.

[0441]

[0442]

[0443] Fidelity by Syndrome PatternAverage FidelityInput Fidelity( )0000 0.60.7535730.3751820.4156560.70.919130.4882350.567520.80.9828770.6346820.750850.90.9984770.8076140.920492

[0444] For example, in an environment with input fidelity of 0.9, the quantum error correction code [[5,1,3]] (i.e., when used as QECCs), an output fidelity of 0.92 can be obtained on average. However, depending on the syndrome pattern being measured, if 0000 is measured as the syndrome output value, an EPR pair with a fidelity of 0.998477 is preserved, but for other syndromes (e.g., 0001), an EPR pair with a fidelity of 0.807614 is obtained after error correction, thereby preserving an EPR pair with a lower output fidelity compared to the input fidelity.

[0445] [[7,1,3]] quantum error correcting code When utilized, EPR pairs are preserved when a total of 22 specific syndrome patterns are generated. The fidelity of the EPR pairs preserved according to each syndrome pattern is as follows. [Table 9] shows [[7,1,3]], When utilizing quantum error correction codes, the fidelity of an EPR pair according to the syndrome pattern is represented. In this case, S in [Table 9] is defined as follows.

[0446] Fidelity by Syndrome PatternAverage FidelityInput Fidelity( )000000 0.60.778840.4574520.4889940.650.875750.5342830.5794240.70.9361930.6137720.6716020.750.9700750.6913150.7586220.80.9875110.7640980.8358730.850.9956570.8310230.9007890.90.9989260.892160.9517210.980.9998860.948190.986428

[0447] For example, in an environment with input fidelity of 0.8, the [[7,1,3]] quantum error correction code (i.e., when used as QECCs), an output fidelity of 0.835873 is obtained on average. However, depending on the syndrome pattern being measured, when 000000 is measured as the syndrome output value, an EPR pair with a fidelity of 0.987511 is preserved, but for other syndromes (e.g., 000001), an EPR pair with a fidelity of 0.764098 is obtained after error correction, thereby preserving an EPR pair with a lower output fidelity compared to the input fidelity.

[0448] FIG. 40 illustrates an example of the average and minimum fidelity performance of a bidirectional EDP according to an embodiment of the present disclosure. Specifically, FIG. 40 illustrates the average and minimum fidelity performance of a bidirectional EDP utilizing [[5,1,3]] QECCs and [[7,1,3]] QECCs in an adaptive mode.

[0449] In Fig. 40, F avg ([[5,1,3]]) represents the average fidelity performance of two-way EDP using the [[5,1,3]] quantum error correction code. F min ([[5,1,3]]) represents the minimum fidelity performance of two-way EDP using the [[5,1,3]] quantum error correction code. F avg([[7,1,3]]) represents the average fidelity performance of two-way EDP using the [[7,1,3]] quantum error correction code. F min ([[7,1,3]]) represents the minimum fidelity performance of two-way EDP using the [[7,1,3]] quantum error correction code. Here, F min ([[5,1,3]]) and F min ([[7,1,3]]) is a quantum error correcting code This shows the case where it is used.

[0450] The average fidelity due to the entire syndrome pattern is higher than the fidelity due to a specific syndrome (e.g., ) generates EPR pairs with lower fidelity, and therefore, the present disclosure proposes a method to additionally share fidelity according to a specific syndrome in an adaptive mode. Then, based on the shared minimum fidelity, the sender and receiver perform EDP by discarding or utilizing the shared EPR state as needed.

[0451] Figure 41 illustrates an example of an adaptive mode-based EDP technique procedure that considers minimum fidelity according to one embodiment of the present disclosure. Referring to Figure 41, the transmitter and receiver can additionally share fidelity and perform additional EDP procedures according to specific syndromes in the adaptive mode.

[0452] In step S4101, it is determined whether entanglement distillation will be performed for the base station and terminal via QPA or via bidirectional QECCs. The criterion for determining the entanglement distillation method can be determined based on average fidelity. For example, the entanglement distillation method can be determined by predicting the final resource consumption in an environment where initial fidelity and target fidelity are given as constraints. The specific method will be described later in the minimum fidelity-based QECC parameter estimation process.

[0453] If the two-way QECCs mode is selected as the adaptive mode, step S4103 is performed, and if the QPA mode is selected, steps S4119 to S4127 are performed. Steps S4119 to S4127 can be performed in the manner described above in steps S2301 to S2309 of FIG. 26. Thereafter, the transmitter and receiver compare their own measurement result bits with the measurement result of the other party received through the classical channel, and if the measurement results do not match, the EPR state not used in the measurement is discarded and steps S4119 to S4127 are performed again. If the measurement results match, the EPR state not used in the measurement is preserved. In the following, a case where the two-way QECCs mode is selected is described.

[0454] At step S4103, When utilizing quantum error correction codes, the sender (Alice) utilizes nonlinear elements Creates an EPR state of the dog.

[0455] In step S4105, the sender transmits one qubit from each EPR state to the receiver (Bob). At this time, the quantum channel may include a generation defect of the EPR state, a wired or wireless photonic channel, a quantum memory error channel, etc.

[0456] At step S4107, the sender and receiver are committed to unitary operation. Performs a decoding circuit for a quantum error correction code.

[0457] At step S4109, the sender and receiver each Measure the qubit of the dog. At this time, the measured qubit is The location of the measurement qubit is determined based on the properties of the quantum error correction code.

[0458] At step S4111, the receiver tells the sender The measurement results of bits are transmitted to the classical channel.

[0459] In step S4113, the sender multiplies its own measurement result with the measurement result of the receiving party, and according to the pattern of the multiplied value, the unmeasured value in step S4109 After performing a correction operation on the EPR state of the dog, the EPR state is either preserved or discarded. If the EPR state is discarded, steps S4103 to S4111 are performed again.

[0460] Alice's measurement results and Bob's measurement results About, the product of the measurement results ( ) is the promised pattern If it belongs to , step S4115 is performed.

[0461] At step S4115, the sender has an unmeasured EPR state ( ) performs a correction operation on its own qubit. The correction operation is According to the pattern of It is determined as one of the EPR pair states of the sender's qubit among the EPR states that have not been measured. If the EPR state is preserved during the execution of steps S4113 to S4115, the sender is determined according to the product of the measurement results. The fidelity of the EPR state of the dog is estimated. The sender shares the estimated fidelity with the receiver by transmitting it over a classical channel. The method for estimating the minimum fidelity is described below. At the same time, the sender informs the receiver that the EPR state is preserved.

[0462] In this disclosure, for the convenience of explanation, the method of preparing and distributing qubits in each EPR state by the sender (Alice) and the receiver (Bob) will be described as follows: the sender prepares qubits in each EPR state and transmits one qubit from each EPR state from the sender to the receiver. However, the qubit generation and distribution method applicable to the present disclosure is not limited to this, and various methods may be applied. For example, the method of preparing an EPR state in a third-party node and transmitting it to a first node (e.g., Alice) and a second node (e.g., Bob) may be combined with or substituted for the procedures described in the present disclosure. As another example, the method of preparing an EPR state in the receiver and transmitting one qubit from the EPR state to the sender may also be applied in the same manner.

[0463] Furthermore, in step S4111, if Alice and Bob share their measurement results, they can each estimate their minimum fidelity. Furthermore, it is self-evident that Alice and Bob can transmit their measurement results to each other, calculate their syndromes, and then Bob (or Alice) can perform a correction operation to estimate the minimum estimated value.

[0464] In step S4117, the sender and receiver perform additional communication to share the minimum fidelity after performing the adaptive mode. Then, if necessary, they decide whether to discard or preserve the EPR state preserved in the previous step. The decision to preserve or discard the EPR state can be made in various ways. As an example of preserving the EPR state, if the fidelity of the entangled state previously shared through the EDP protocol is high, even an entangled pair that does not satisfy the target fidelity can be preserved. For example, when an EPR entanglement state is needed after a total of 10 distillation protocols, if the fidelity of the 10th entanglement state is sufficiently high considering the fidelities of the previous 9, it can be preserved even if the fidelity of the last EPR entanglement state does not reach the target fidelity.

[0465] Minimum fidelity estimation technique when utilizing QECCs bidirectionally

[0466] When utilizing bidirectional QECCs in adaptive mode, the target fidelity is satisfied on average. A parameter estimation process exists. However, depending on the syndrome measurement results, there may be cases where the target fidelity is not met. Therefore, an additional process is needed to report the fidelity for each syndrome after it occurs. Below, a method for estimating fidelity when a specific syndrome occurs is described.

[0467] In the initial fidelity of In case of a syndrome of weight error, the minimum fidelity of the output state ( ) has a lower bound as shown in [Mathematical Formula 26] below, and in this disclosure, the output fidelity is estimated through the lower bound.

[0468]

[0469] The probability of performing a correction operation is defined as the probability of success ( ) is estimated as in [Mathematical Formula 27] in the same way as when the existing QECCs are used in adaptive mode.

[0470]

[0471] [[7,1,3]], [[5,1,3]] QECCs When used in adaptive mode, the average fidelity ( )Performance and Minimum Fidelity( ) performance and estimation (Est) can be represented as in FIGS. 42 and 43. FIG. 42 illustrates an example of minimum fidelity estimation performance when a [[7,1,3]] error correcting code is used in two ways in a system according to an embodiment of the present disclosure. FIG. 43 illustrates an example of minimum fidelity estimation performance when a [[5,1,3]] error correcting code is used in two ways in a system according to an embodiment of the present disclosure.

[0472] est F in Fig. 42 and Fig. 43 min ,t corr =0 and est F min ,t corr =1 means an estimate of fidelity. In Fig. 42 and Fig. 43, F min ,t corr =0 and F min ,t corr =1 means the actual value of fidelity. In Fig. 42 and Fig. 43, est F min ,t corr =0 and F min ,t corr =0 indicates that the EPR state is preserved after correction for syndrome patterns estimated to have 0 or 1 error, and the EPR state is discarded in other cases. In Fig. 42 and Fig. 43, est F min ,t corr =1 and F min ,t corr=1 indicates that the EPR state is preserved only for syndrome patterns in which no error occurs, and the EPR state is discarded in other cases.

[0473] Figures 42 and 43 show that the fidelity of the preserved EPR state is greater than the estimated fidelity, as the estimate of the minimum fidelity is estimated to be a lower value than the actual fidelity.

[0474] Minimum fidelity based Parameter estimation process

[0475] When using QECCs in adaptive mode, the minimum fidelity of the EPR state generated after the EDP process is the target fidelity ( ) while satisfying the minimum EPR state (fidelity ) to utilize the parameters of QECCs and parameters of adaptation mode Or Or The following optimization process is performed to estimate .

[0476]

[0477]

[0478] In [Equation 28], the minimum estimated fidelity can be estimated through [Mathematical Formula 26].

[0479] Specific goal fidelity (Table 10 to Table 12) = or ) shows the results of optimal mode and parameter estimation to satisfy the condition.

[0480] 1- modeNum_EPRnkD GainQPA 라운드0.851.00E-06'QPA'792.9544'-''-''-''-''-'60.861.00E-06'QPA'654.7041'-''-''-''-''-'60.871.00E-06'QPA'542.753'-''-''-''-''-'60.881.00E-06'QPA'156.4529'-''-''-''-''-'50.891.00E-06'QPA'135.3346'-''-''-''-''-'50.91.00E-06'QPA'117.3719'-''-''-''-''-'50.911.00E-06'QPA'102.049'-''-''-''-''-'50.921.00E-06'QPA'88.9412'-''-''-''-''-'50.931.00E-06'QPA'77.6981'-''-''-''-''-'50.941.00E-06'Detecting'47.839927390-20.1893'-'0.951.00E-06'Detecting'35.950527390-23.7426'-'0.961.00E-06'Detecting'25.049626380-27.4389'-'0.971.00E-06'Detecting'10.707225570-10.585'-'0.981.00E-06'Detecting'8.285525570-11.047'-'0.991.00E-06'Detecting'4.697816450-3.8568'-'

[0481] 1- modeNum_EPRnkD GainQPA 라운드0.851.00E-07'QPA'792.9544'-''-''-''-''-'60.861.00E-07'QPA'654.7041'-''-''-''-''-'60.871.00E-07'QPA'542.753'-''-''-''-''-'60.881.00E-07'QPA'451.691'-''-''-''-''-'60.891.00E-07'QPA'377.3025'-''-''-''-''-'60.91.00E-07'QPA'316.2845'-''-''-''-''-'60.911.00E-07'QPA'102.049'-''-''-''-''-'50.921.00E-07'QPA'88.9412'-''-''-''-''-'50.931.00E-07'QPA'77.6981'-''-''-''-''-'50.941.00E-07'QPA'68.0292'-''-''-''-''-'50.951.00E-07'Detecting'53.925827290-5.7673'-'0.961.00E-07'Detecting'27.096927390-25.3916'-'0.971.00E-07'Detecting'19.133226380-27.114'-'0.981.00E-07'Detecting'8.285525570-32.5425'-'0.991.00E-07'Detecting'5.186921560-12.3894'-'

[0482] 1- modeNum_EPRnkD GainQPA Round0.9991.00E-06'Detecting'1.921317940-2.0947'-'0.99911.00E-06'Detecting'1.91817940-2.0964'-'0.99921.00E-06'Detect ing'1.914817940-2.098'-'0.99931.00E-06'Detecting'1.911517940-2.0997'-'0.99941.00E-06'Detecting'1.908317940-2.1013'- '0.99951.00E-06'Detecting'1.90517940-2.103'-'0.99961.00E-06'Detecting'1.901817940-2.1046'-'0.99971.00E-06'Detectin g'1.892301650-2.1128'-'0.99981.00E-06'Detecting'1.8349311750-2.1683'-'0.99991.00E-06'Detecting'1.50096420-2.5007'-'

[0483] [Table 10] Minimum fidelity based EDP protocol and spec in [Table 11] shows Minimum fidelity based EDP protocol and spec in [Table 12] shows Minimum fidelity based EDP protocol and spec in It represents.

[0484] Mode is determined among QPA, QECCs (QECCs-based bidirectional EDP technique), and Detecting among the adaptive modes, and refers to the EDP operation method that utilizes the minimum resources in each initial fidelity. 'QPA' refers to QPA mode, and 'QECCs' refers to QECCs-based bidirectional EDP protocol. In this case, 'Detecting' is a bidirectional EDP protocol based on QECCs. This means that Num_EPR is the number of EPR states utilized in each mode. When a bidirectional protocol based on QECCs is utilized in mode, the optimal code and number of corrected errors ( ) and is an estimated value using bound. Gain is the number of qubits reduced when a bidirectional protocol based on QECCs is used compared to QPA, and QPA rounds is the number of rounds when used in QPA mode.

[0485] For example, in an environment where the initial fidelity is 0.95, If you want to satisfy the fidelity of [[29,1,11]] quantum error correction code based on the average fidelity (e.g. [Table 5]) It can be used as a standard, but based on minimum fidelity (e.g. [Table 11]), the quantum error correction code [[27,2,9]] The method based on average fidelity compared to QPA uses 8.8 fewer EPR pairs, while the method based on minimum fidelity uses 5.7 fewer EPR pairs.

[0486] Figure 44 illustrates an example of the overall process of a minimum fidelity-based parameter estimation and adaptive mode-based EDP technique according to one embodiment of the present disclosure. Referring to Figure 44, parameter estimation in the minimum fidelity-based adaptive mode and correction operations based on the parameters can be performed, or the EPR state can be discarded and the protocol can be performed again.

[0487] In step S4401, in an environment where the initial fidelity and the target fidelity are given as constraints, it is decided through prediction of the final consumed resources whether to perform entanglement distillation through QPA or 2-way QECCs for the base station and the terminal, respectively. In case of utilizing 2-way QECCs EDP, the base station and the terminal determine the QECCs parameters and . Here, the QECCs parameters and As described above, it can be determined based on minimum fidelity. When utilizing QPA, the base station and terminal share the number of QPA rounds.

[0488] If 2-way QECCs are utilized, the base station and terminal perform step S4403. Step S4403 may perform the process of the QECCs-based bidirectional EDP technique described above in FIG. 30. Accordingly, steps S3003 to S3015 may be performed by the base station and terminal.

[0489] If QPA is utilized, the base station and terminal perform step S4405. Step S4405 may perform the bidirectional EDP protocol technique described above in FIG. 26. Accordingly, steps S2601 to S2611 may be performed by the base station and terminal.

[0490] Entanglement state reuse in EDP using two-way QECCs

[0491] As described above, when performing EDP in adaptive mode based on minimum fidelity, the fidelity values ​​of unmeasured entangled pairs vary depending on the syndrome of QECCs. For example, the fidelity of EPR pairs according to the measurement syndrome pattern when utilizing the [[5,1,3]] quantum error correction code is as shown in [Table 13] below. In [Table 13] below, S is defined as follows.

[0492] Initial Fidelity(Average Fidelity by Syndrome Pattern) )0000 0.60.7535730.3751820.4156560.70.919130.4882350.567520.80.9828770.6346820.750850.90.9984770.8076140.920492

[0493] For example, in an environment with input fidelity of 0.9, the quantum error correction code [[5,1,3]] (i.e., when used as QECCs), an output fidelity of 0.92 is obtained on average. However, depending on the syndrome pattern being measured, when 0000 is measured as the syndrome output value, an EPR pair with a fidelity of 0.998 is preserved, but for other syndromes (e.g., 0001), an EPR pair with a fidelity of 0.808 is obtained after error correction, thereby preserving an EPR pair with a lower output fidelity compared to the input fidelity.

[0494] As another example, if only the [[5,1,3]] error correction code is used, the initial fidelity is 0.9, and the target fidelity is 0.91, and if the target fidelity is set based on the average fidelity, the [[5,1,3]] code will correct and preserve unmeasured qubits for all syndromes ( ), if the target fidelity is set based on the minimum fidelity, the qubit is preserved only when the 0000 syndrome is measured ( (This is equivalent to performing two-way QECCs EDP in this case). If we think of the process as utilizing the [[5,1,3]] quantum error correction code four times for 20 entangled pairs (all four times measuring syndromes other than 0000), then the four unmeasured entangled pairs are discarded based on the minimum fidelity.

[0495] In this disclosure, we propose a technique for additionally utilizing unmeasured EPR pairs instead of discarding them when discarded syndromes are measured. In the example above, when performing two rounds of QPA using four EPR pairs, one EPR pair with a fidelity of 0.949 can be generated according to the fidelity formula after performing QPA in [Equation 22], and an entangled state exceeding the target fidelity of 0.91 is generated. In addition to QPA, various types of EDP protocols can be performed (e.g., two-way QECCs, QECCs, etc.) and can be operated in various operating modes (e.g., recurrence method, entanglement pumping mode, etc.). In addition, the criteria for reusing entangled pairs that should be discarded can also be set in various ways (e.g., , (Whether QPA can be used)).

[0496] For two-way QECCs EDP that reuses entangled states, the parameters In addition Parameters are introduced here. is the maximum weight of the estimation error that can reuse the entanglement state. In the example above, to meet the target fidelity of 0.91 as the minimum fidelity criterion, This is utilized (but only in the case of utilizing the 0000 syndrome) ), additionally, if the QPA protocol is utilized for entangled pair reuse, all syndromes can be utilized. This is it.

[0497] Bidirectional QECCs EDP protocol that recycles entangled states

[0498] FIG. 45 illustrates an example of the overall process of a Two-way QECCs EDP protocol for reusing entangled qubits according to one embodiment of the present disclosure.

[0499] As mentioned above, EPR reuse criteria are selected using various criteria (e.g. ) can be selected, and the formula utilized in the optimization process can also be modified. Referring to Fig. 45, for the existing optimization, the protocol can be performed in the same manner as the existing adaptation mode (i.e., the optimization formula is applied in the same manner as before), and the case of recycling the entangled pair according to the measurement result can be performed.

[0500] The mode selection process for the adaptive mode-based EDP technique can be performed as described above. For example, if the QPA mode is selected as the adaptive mode, the bidirectional EDP protocol of FIG. 26 is performed. FIG. 45 illustrates the procedure for reusing the EPR state when the QECCs-based bidirectional EDP technique is selected as the adaptive mode.

[0501] In step S4501, parameters for selection and reuse of the QECC-based bidirectional EDP mode are determined. To divide the QPA mode and the QECC-based bidirectional EDP mode, the above-mentioned average fidelity-based parameter estimation process or minimum fidelity-based A parameter estimation process can be performed. The parameter for reuse is the maximum weight parameter of the estimation error that can reuse the entangled state. may be included. Therefore, For parameter selection, a criterion for reuse of the entangled state can be determined. Fig. 45 Output fidelity when using symbols Input fidelity Bigger than An example of a case where is set is shown.

[0502] At step S4503, When utilizing quantum error correction codes, the sender (Alice) utilizes nonlinear elements to Creates an EPR state of the dog.

[0503] In step S4505, the sender transmits one qubit from each EPR state to the receiver (Bob). At this time, the quantum channel includes the generation defect of the EPR state, a wired / wireless photonic channel, and a quantum memory error channel.

[0504] At step S4507, the sender and receiver are committed to the Unitary Operation operation as a unitary operation. Performs a decoding circuit for a quantum error correction code.

[0505] At step S4509, the sender and receiver each Measure the qubit of the dog. At this time, the measured qubit is The location of the measurement qubit is determined based on the properties of the quantum error correction code.

[0506] At step S4511, the receiver tells the sender: The measurement results of bits are transmitted to the classical channel.

[0507] In step S4513, the sender multiplies its own measurement result with the measurement result of the receiving party, and according to the pattern of the multiplied value, it measures the value not measured in step S4509. After performing a correction operation on the EPR state of the dog, it is decided whether to (a) preserve it, (b) perform an additional EDP on the unmeasured EPR state, or (c) discard the EPR state. If the EPR state is discarded (i.e., case (c)), steps S4503 to S4511 are performed again. is Alice's measurement result, is Bob's measurement result, the product of the measurement results ( ) is the promised pattern If it belongs to , step S4515 is performed.

[0508] if go If it does not belong to, it can be additionally determined whether to perform EDP according to various criteria (i.e., in case of (b) or (c)). For example, whether to perform EDP can be determined by comparing the fidelity of the unmeasured qubit with the initial fidelity. For example, if the fidelity of the unmeasured qubit is greater than or equal to the initial fidelity, the reuse of the EPR state is determined (i.e., in case of (b)), and step S4517 can be performed. If the fidelity of the unmeasured qubit is less than the initial fidelity, the EPR state is discarded (i.e., in case of (c)), and steps S4503 to S4511 are performed again. At this time, the aforementioned When utilizing QECCs in two ways, the fidelity of an unmeasured qubit can be estimated based on the weight w of the error associated with the measured syndrome in the aforementioned minimum fidelity estimation technique.

[0509] At step S4515, the sender has an unmeasured EPR state ( (a) performs a correction operation on its own qubit (i.e., case (a)). The correction operation is According to the pattern of It is determined as one of them, and operates on the sender's qubit among the EPR pair states of the unmeasured EPR state.

[0510] If the EPR state is preserved, the sender multiplies the measurement results by The fidelity of the EPR state of the dog is estimated and the estimated fidelity can be shared with the receiver by transmitting it over a classical channel (minimum fidelity sharing is optional, and is not necessary when using average fidelity). At the same time, the sender informs the receiver that the EPR state is preserved.

[0511] At step S4517, if the EPR state is reused, EDP is performed with the unmeasured qubit.

[0512] In this disclosure, for the convenience of explanation, the method of preparing and distributing qubits in each EPR state by the sender (Alice) and the receiver (Bob) will be described as follows: the sender prepares qubits in each EPR state and transmits one qubit from each EPR state from the sender to the receiver. However, the qubit generation and distribution method applicable to the present disclosure is not limited to this, and various methods may be applied. For example, the method of preparing an EPR state in a third-party node and transmitting it to a first node (e.g., Alice) and a second node (e.g., Bob) may be combined with or substituted for the procedures described in the present disclosure. As another example, the method of preparing an EPR state in the receiver and transmitting one qubit from the EPR state to the sender may also be applied in the same manner.

[0513] It is also self-evident that in step S4511, Alice and Bob transmit the measurement results to each other, each calculates the syndrome, and then Bob (or Alice) performs a correction operation, and Alice (or Bob) can estimate the estimated value of the fidelity.

[0514] also It is obvious that Alice and Bob can initially agree on parameters and perform the protocol without performing it, and then calculate the fidelity based on the measured syndrome to check whether the initial entanglement state reuse criterion is satisfied and decide whether to perform EDP.

[0515] Example 1: Based on average fidelity and After optimizing the parameters, a method for reusing entangled states using QPA

[0516] Case 1-1) to satisfy If you set

[0517] [Table 14] shows the target fidelity based on the average fidelity. Initial fidelity by When performed in adaptive mode, it shows the parameter optimization results.

[0518] 1- modeNum_EPRnkD GainQPA Round 0.851.00E-06'QPA'792.9544'-''-''-''-''-'60.861.00E-06'QPA'654.7041'-''-''-''-''-'60.871.00E-06'QPA'542.753'-''-''-''-'60.881.00E-06'QPA'156.4529'-''-''-'' -''-'50.891.00E-06'QPA'135.3346'-''-''-''-''-'50.91.00E-06'QPA'117.3719'-''-''-' '-''-'50.911.00E-06'QPA'102.049'-''-''-''-''-'50.921.00E-06'QPA'88.9412'-''-''-' '-''-'50.931.00E-06'adaptive'74.7453291111-2.952850.941.00E-06'Detecting'47.8399 27390-20.1893'-'0.951.00E-06'adaptive'23.797282101-35.8961'-'0.961.00E-06'adapti ve'20.2648282101-32.2237'-'0.971.00E-06'adaptive'11.162427391-10.1298'-'0.981.00 E-06'Detecting'8.285525570-11.047'-'0.991.00E-06'Detecting'4.697816450-3.8568'-'

[0519] In the technique utilizing qubit reuse, ' in [Table 15] below ' The parameter is additionally utilized, and its value means the maximum weight of the estimation error that can reuse the entangled state. [Table 15] shows that when an EPR state with a fidelity higher than the initial fidelity is reused, Represents the average fidelity-based qubit recycling specification in .

[0520] fidelity_of_reusedfidelity_of_( +1)prob_of_{ }prob_of_{ }0.85'-''-''-''-''-''0.86'-''-''-''-''-''0.87'-''-''-''-''-''0.88'-''-''-''-''-''-'0.89'-''-''-''-''-''0.9'-''-''-''-''0.91'-''-''-''-''0.92'-''-''-''-''-''0.9320.994990.111030.387980.668370.9 410.997920.17830.188130.512350.9520.971490.0103780.588310.837340.9620.992830.0260030.690850.90010.9710.999990.890410.806280.806280.9810.999690.128480.603460.911350.99010.961660.851460.85146

[0521] In [Table 15], ‘fidelity of reused’ is The fidelity of the unmeasured entangled state, estimated by the error of the corresponding weight, has a higher value than the initial fidelity. If the error is estimated to be greater than 1, the fidelity is 'fidelity of { It is marked as '+1}' and has a lower value than the initial fidelity. 'prob of { }'silver The lower bound of the probability of the following number of errors occurring is 'prob of { }'silver The lower bound on the probability of the following number of errors occurring is approximately prob of { }- prob of {} as the probability corresponding to the number of It can be assumed that the qubits of a dog can be recycled.

[0522] For example, previously the initial fidelity was 0.98( If, Fidelity of the goal( ) to satisfy Using the parameters of , for syndromes where the weight of the error is estimated to be 1, Although the entangled pairs could not be preserved, through qubit recycling, we confirmed that the initial fidelity was higher than 0.98 for syndromes where the error weight is estimated to be 1, and thus EDP can be performed later using only the corresponding qubits or by transmitting additional entangled states. If the QPA protocol is performed using only the five entangled states, two rounds of QPA can be performed, and then Fidelity of ( ≥ ) can be created.

[0523] For an initial fidelity of 0.95, A dog entanglement state is created, For the syndrome corresponding to , EDP can be performed by confirming that the initial fidelity is higher than 0.95. However, even if QPA is performed immediately for the first round, the target fidelity cannot be exceeded, so QPA cannot be used. In this case, the two entangled states are preserved, and only nk qubits are transmitted in the subsequent entangled pair transmission for EDP, and then QECCs It performs EDP based on bidirectional QECCs.

[0524] Case 1-2) to satisfy If you set

[0525] [Table 16] shows the target fidelity based on the average fidelity. Initial fidelity by = 0.85~0.99 shows the parameter optimization results when performed in adaptive mode. [Table 16] is identical to [Table 14] with the same target fidelity.

[0526] 1- modeNum_EPRnkD GainQPA Round 0.851.00E-06'QPA'792.9544'-''-''-''-''-'60.861.00E-06'QPA'654.7041'-''-''-''-''-'60.871.00E-06'QPA'542.753'-''-''-''-'60.881.00E-06'QPA'156.4529'-''-''-'' -''-'50.891.00E-06'QPA'135.3346'-''-''-''-''-'50.91.00E-06'QPA'117.3719'-''-''-' '-''-'50.911.00E-06'QPA'102.049'-''-''-''-''-'50.921.00E-06'QPA'88.9412'-''-''-' '-''-'50.931.00E-06'adaptive'74.7453291111-2.952850.941.00E-06'Detecting'47.8399 27390-20.1893'-'0.951.00E-06'adaptive'23.797282101-35.8961'-'0.961.00E-06'adapti ve'20.2648282101-32.2237'-'0.971.00E-06'adaptive'11.162427391-10.1298'-'0.981.00 E-06'Detecting'8.285525570-11.047'-'0.991.00E-06'Detecting'4.697816450-3.8568'-'

[0527] In the technique utilizing qubit reuse, ' in [Table 17] below ' parameter is additionally utilized, and its value is the maximum weight of the estimation error that can reuse the entangled state. [Table 17] shows that when reusing an EPR state with a fidelity of 0.5 or higher, Represents the average fidelity-based qubit recycling specification in .

[0528] fidelity_of_reusedfidelity_of_( +1)prob_of_{ }prob_of_{ }'-''-''-''-''-''-''-''-''-''-''-''-''-''-''-''-''-''-''-''-''-''-''-''-''-''-''-''-''-''-''-''-''-''-''-''-''-''-'20.994990.111030.387980.6683710.997920.1783 0.188130.5123520.971490.0103780.588310.8373420.992830.0260030.690850.900120.890410.000862740.806280.953810.999690.128480.603460.9113510.961660.000284270.851460.98907

[0529] In [Table 17], ‘fidelity of reused’ is It is the fidelity of the unmeasured entangled state when estimated by the error of the corresponding weight, and it can be confirmed that it is higher than 0.5. If the error is estimated to be greater than 1, the fidelity is 'fidelity of { It is marked as 'prob_of_{+1}' and has a lower value than the initial fidelity. }'silver is the lower bound of the probability of occurrence of the following number of errors, and 'prob_of_{ }'silver The lower bound of the probability of the following number of errors occurring is approximately prob_of_{ }- prob_of_{ } as the probability corresponding to the number of It can be assumed that the qubits of a dog can be recycled.

[0530] For example, previously the initial fidelity was 0.98( If =0.98), Fidelity of the goal( ) to satisfy Using the parameters of , for syndromes where the weight of the error is estimated to be 1, Although the entangled pairs could not be preserved, through qubit recycling, the fidelity was confirmed to be higher than 0.5 for syndromes where the error weight is estimated to be 1, so that EDP can be performed later using only the corresponding qubit or by transmitting additional entangled states. If the QPA protocol is performed using only the five entangled states, two rounds of QPA can be performed, and then Fidelity of ( ≥ ) can be created.

[0531] Since k entangled states with lower output fidelity than Case 1 can be utilized, Case 2 is higher than the value The value is greater than or equal to the initial fidelity. For example, if the initial fidelity is 0.97, [Table 14] and [Table 15] (case 1-1) The value is 1, whereas in [Table 16] and [Table 17] (case 1-2) The value increases by 2, so the probability of not being discarded is { }) also increases from 0.81 to 0.95.

[0532] Example 2: Based on average fidelity and After optimizing the parameters, a method for reusing entangled states using adaptive mode

[0533] When the adaptive mode EDP technique is used in the EDP technique, an additional entanglement distillation process is performed using k recycled entangled qubits. At this time, the parameters of the adaptive mode EDP ( ) An optimization process can be utilized for optimization, and the following [Mathematical Formula 29] can be used.

[0534]

[0535]

[0536]

[0537] In [Mathematical Formula 29], F'' is the amount preserved after distillation when using the adaptive mode EDP technique in the EDP technique. It refers to the fidelity of the dog's entanglement state.

[0538] As described above in [Table 14] and [Table 15] Recycling parameters based on If used, Five qubits are recycled in [[4,2,2]] QECCs. By utilizing it, after performing additional EDP, Two entangled states can be obtained.

[0539] Example 3: Based on average fidelity and The parameter is When optimized with parameters

[0540] is selected It is not decided, When parameters are selected by comprehensively considering [Equation 30] or [Equation 31], the optimization process can be performed (when QPA is used as EDP).

[0541]

[0542]

[0543] It is self-evident that optimization functions and constraints can be changed or added depending on the usage environment.

[0544] Additional resource reduction techniques in bidirectional QECCs EDP

[0545] In this disclosure ( ) in bidirectional QECCs EDP We propose a technique to correct some errors with the weight of . Through this, the fidelity of the output entanglement state is ( ) It can be seen that the bidirectional QECCs used have a lower EDP than the EDP, but the success probability increases. Figures 46 and 47 In bidirectional QECCs EDP =1 Among the syndromes of errors with weight Fidelity F' and success probability of entanglement state when error correction and preservation are performed for the dog syndrome It shows.

[0546] [[5,1,3]] When the bidirectional QECCs EDP is performed using quantum error correction codes, to generate an entangled state satisfying the target fidelity of 0.95 in an environment with an initial fidelity of 0.9, The bidirectional QECCs parameters should be utilized. Therefore, if a syndrome other than 0000 is measured, the entangled state should be discarded. However, by utilizing the procedures of the present disclosure, = Even if 6 syndromes (i.e. 0001, 0010, 0011, 0100, 0101, 0010) are measured, the entanglement state can be preserved, and the success probability is , and a higher probability can be guaranteed compared to the existing 0.59141. Therefore, from the perspective of the average resource consumed, as This can result in a resource reduction of up to 27%.

[0547] Parameters Decision-making techniques

[0548] Parameters Is It refers to the number of syndromes that will be preserved after correction without discarding the EPR state among the syndromes of errors with weight. ( ) When the bidirectional QECCs parameter is utilized, the following [Mathematical Formula 32] is used to consume minimum resources while satisfying the target fidelity. can be decided.

[0549]

[0550] In [Equation 32], Is It means the fidelity of the output EPR state when the dog's syndrome is additionally corrected, and can be determined as in [Mathematical Formula 33] below.

[0551]

[0552]

[0553] In [Equation 33], Is ( ) means the probability of success in two-way QECCs EDP, silver ( ) refers to the output fidelity in two-way QECCs EDP, Is It means the success probability in two-way QECCs EDP, silver It refers to the output fidelity in two-way QECCs EDP.

[0554] Analysis of output status

[0555] The Werner state can be expressed as follows [Mathematical Formula 34].

[0556]

[0557]

[0558] If additionally a errors are corrected and the type of syndrome pattern and QECCs utilized is used, the output entanglement state is not Werner (i.e., as in [Equation 35]). If this does not hold, a Bell diagonal state W can be created.

[0559]

[0560] In this case, if additional EDP is performed, EDP performance may degrade. Furthermore, if additional operations are performed by utilizing the output entanglement state, the number of operations may increase. Therefore, if transformation into a Werner state is desired, the following method can be used.

[0561] When the sender and receiver perform twirling using [Mathematical Formula 16], the input state can be changed as shown in [Mathematical Formula 36] below.

[0562]

[0563] In [Equation 36], B x means an operator that rotates π / 2 around the X-axis, and B y means an operator that rotates π / 2 around the Y-axis, and B z means an operator that rotates π / 2 around the Z-axis. If EDP is performed, EDP ​​can be performed by utilizing quantum error correction codes having different X, Y, and Z error correction capabilities depending on the values ​​of [Mathematical Formula 37] below. By having the sender and receiver each perform the operation, and After changing the value of , the same quantum error correction code can be utilized.

[0564]

[0565]

[0566] Procedure for additional resource reduction in bidirectional QECCs EDP

[0567] FIG. 48 illustrates an example of a procedure for additional resource reduction in a bidirectional QECCs EDP according to one embodiment of the present disclosure.

[0568] At step S4801, the sender sets the bidirectional QECCs EDP parameters ( ) parameters for initial fidelity ( ), goal fidelity ( ) is estimated based on.

[0569] In step S4803, the sender additionally specifies the number of syndromes to be corrected. and Determines the dog's syndrome pattern.

[0570] At step S4805, the sender (Alice) utilizes a nonlinear element to Creates an EPR state of the dog.

[0571] In step S4807, the sender transmits one qubit from each EPR state to the receiver (Bob). At this time, the quantum channel includes the generation defect of the EPR state, a wired / wireless photonic channel, and a quantum memory error channel.

[0572] At step S4809, the sender and receiver are committed to the Unitary Operation operation as a unitary operation. Performs quantum error correction code circuit.

[0573] At step S4811, the sender and receiver each Measure the qubit of the dog. At this time, the measured qubit is The location of the measurement qubit is determined based on the properties of the quantum error correction code.

[0574] At step S4813, the receiver tells the sender: The measurement results of bits are transmitted to the classical channel.

[0575] S4815 The sender multiplies its own measurement result with the measurement result of the receiving party. decides. If Ga syndrome pattern If included, step S4817 is performed. If Ga syndrome pattern If not included, the sender may discard the EPR state and perform steps S4805 to S4815.

[0576] At step S4817, the sender measures the pattern of the multiplied values ​​not measured at step S4811. Correction operations are performed on the EPR state of the dog. At this time, the syndrome pattern for which the correction operation is performed The number of It can be a dog. Correction operation According to the pattern of It is determined as one of them, and is applied to the sender's qubit among the EPR pair states of the unmeasured EPR state.

[0577] At step S4819, the transmitter and receiver are twirled or otherwise placed in the Werner state. . Also, the sender and receiver are in the Bell diagonal state. After saving, it can be used in the future. Step S4519 can be performed optionally depending on the situation.

[0578] For convenience, the method of preparing and distributing qubits in each EPR state by the sender (Alice) and the receiver (Bob) will be described in such a way that the sender prepares qubits in each EPR state and transmits one qubit from each EPR state from the sender to the receiver. However, the qubit generation and distribution method applicable to the present disclosure is not limited to this and various methods may be applied. For example, the method of preparing an EPR state in a third-party node and transmitting it to a first node (e.g., Alice) and a second node (e.g., Bob) may be combined with or substituted for the procedures described in the present disclosure. As another example, the method of preparing an EPR state in the receiver and transmitting one qubit from the EPR state to the sender may also be applied in the same way.

[0579] It is also self-evident that in step S4813, Alice and Bob transmit the measurement results to each other, and after each calculates the syndrome, Bob (or Alice) performs the correction operation and can estimate the estimated value of the fidelity for Alice (or Bob).

[0580] Also, the weight of the error is adjusted as needed. In the following cases, An additional protocol can be implemented to recycle the entangled state for the dog's syndrome pattern.

[0581] Below, a procedure for the EDP protocol utilizing the transformation of the Bell diagonal state is described.

[0582] How to convert Bell diagonal states

[0583] The bell diagonal state can be converted using the first conversion method or the second conversion method according to each unitary.

[0584] The first conversion method is as follows [Mathematical Formula 38] is utilized.

[0585]

[0586]

[0587] In [Equation 38], is. Through the first conversion method, While maintaining and Conversions between them can be performed.

[0588] The second conversion method is as follows [Mathematical Formula 39] is utilized.

[0589]

[0590]

[0591] In [Equation 39], is. Through the second conversion method, While maintaining , Conversions between them can be performed.

[0592] The third conversion method is as follows [Mathematical Formula 40] is utilized.

[0593]

[0594]

[0595] In [Equation 40], is. Through the third conversion method, While maintaining , Conversion between them can be performed.

[0596] The fourth conversion method is as follows [Mathematical Formula 41] is utilized.

[0597]

[0598]

[0599] In [Equation 41], is. Through the fourth conversion method, While maintaining and Conversions between them can be performed.

[0600] and The Bell diagonal state can be freely transformed using operators. In addition, the Bell diagonal state can be transformed into a Werner state using Twiring and Pauli Y.

[0601] Also, considering the global phase, in front of each unitary Includes The same results can be obtained even if .

[0602] 2-1 EDP using operator adaptation

[0603] The Z basis measurement of the CNOT and target qubits changes the state of the qubits as shown in [Mathematical Formula 42] below.

[0604]

[0605] That is, the sender and receiver are fixed as in Fig. 15. Rather than performing it, it is tailored to the target performance as in Fig. 49. , or an operator adaptation technique that performs twirling as in Fig. 50. Additionally, due to the characteristics of 2-1 EDP performance, Alternatively, a technique of selecting between twirling can also be performed.

[0606] For example, the initial state is In this case, the QPA protocol always With a probability of can only generate Bell diagonal states with fidelity of , and recurrence is always With a probability of can generate a Bell diagonal state with fidelity. When an adaptive computational technique is utilized, With a probability of A Bell diagonal state with fidelity can be generated.

[0607] Also the initial state is In this case, the QPA protocol cannot achieve improved performance, but when computational adaptation techniques are utilized, If you do it through With a probability of A Bell diagonal state with a fidelity of can be generated. The computational adaptation method is not limited to the above-described example. Therefore, utilizing unitary can generate states with different fidelities with different success probabilities.

[0608] Figure 51 illustrates an example of a 2-1 EDP protocol utilizing an operational adaptation technique according to one embodiment of the present disclosure. Referring to Figure 51, operations can be applied differently depending on the situation to change the state of a qubit.

[0609] At step S5101, through channel estimation The coefficient of state is decided.

[0610] At step S5103, the sender determines the target output state based on or the appropriate operator during twirling Select .

[0611] In step S5105, the sender creates two EPR states.

[0612] In step S5107, the sender transmits one qubit from each EPR state to the receiver (Bob). Therefore, a total of two qubits are transmitted. The transmitted qubits undergo a quantum channel, which includes EPR state generation defects, wired and wireless photonic channels, and quantum memory error channels.

[0613] In step S5109, the sender and receiver are the operators determined in step S5103. It performs operations on each qubit using .

[0614] In step S5111, the two entangled states are gathered and bundled, and the target qubits of CNOT and CNOT are measured in the Z basis.

[0615] In step S5113, the sender and receiver share the Z-basis measurement results. If the measurement results are the same, the entangled state used as the control qubit is preserved.

[0616] If the shared measurement results are different, the entangled state used as the control qubit is discarded, and the process can be restarted from step S5105.

[0617] For convenience of explanation, the method of preparing and distributing qubits in each EPR state by the sender (Alice) and the receiver (Bob) will be described as follows: the sender prepares qubits in each EPR state and transmits one qubit from each EPR state from the sender to the receiver. However, the qubit generation and distribution method applicable to the present disclosure is not limited to this, and various methods may be applied. For example, the method of preparing an EPR state in a third-party node and transmitting it to a first node (e.g., Alice) and a second node (e.g., Bob) may be combined with or substituted for the procedures described in the present disclosure. As another example, the method of preparing an EPR state in the receiver and transmitting one qubit from among the EPR states to the sender may also be applied in the same manner.

[0618] Also in this disclosure, the same Although the state is considered as an input value, in order to generate the target output state for different Bell diagonal states, Or the appropriate operator during twirling It is self-evident that you can choose .

[0619] quantum teleportation (QT)

[0620] Quantum teleportation is a technology that transmits quantum information from a sender at a specific location to a receiver located a certain distance away. Unlike traditional teleportation, which involves transmitting actual carriers, quantum teleportation transmits quantum information while the carriers on both sides remain fixed. This quantum information transmission requires entangled quantum states, or Bell states. Bell states can be used to establish statistical correlations between distinct physical systems. Because any change experienced by one of the entangled particles causes the other particle to experience the same change, the two particles can be interpreted as acting as a single quantum state.

[0621] Figure 52 illustrates an example of a quantum transmission protocol according to one embodiment of the present disclosure. Quantum transmission requires a classical channel capable of transmitting two classical bits, an entanglement state (e.g., Bell state) generating device, a quantum channel for moving two particles in an entangled state to transmitting and receiving devices located at different locations, a Bell state measuring device at a transmitting end, and a unitary computation device at a receiving end. As an example, the classical channel may be a wireless channel in a wireless communication system, and the bits transmitted through the wireless channel may be classical bits. As another example, the classical channel may be a wired channel in a wired communication system. However, in the following, the terms classical channel and classical bit are referred to to clarify the difference between a quantum channel and a conventional communication channel, but this may not be limited thereto. In other words, the classical channel may be any channel for transmitting data.

[0622] In addition, the following describes a method for performing two-way communication between a first device (5210) and a second device (5220), and the devices may not be limited to a specific form.

[0623] For example, the quantum information you want to transmit The quantum transmission protocol for can be expressed as follows.

[0624] - Entanglement generation: An entangled state of two qubits is created using a Bell state generator.

[0625] - Entanglement distribution: The generated entangled qubits are moved through a quantum channel, with one qubit moving to the location of the first transmitter device (5210) and the other qubit moving to the location of the second receiver device (5220).

[0626] - Quantum pre-processing: The first device (5210) measures the Bell state for the quantum state |φ〉 to be transmitted and one qubit of the Bell state it has. Therefore, the first device (5210) can obtain a result corresponding to one of the Bell states. At this time, the qubit state that the second device (5220) has in response to the result of the Bell state measurement of the first device (5210) is as shown in [Table 18] below.

[0627] BSM Results of and Alice's QubitBob's Qubit

[0628] - Classical information transmission: The first device (5210) encodes the bell state measurement result into two classical bits and transmits it to the second device (5220).

[0629] - Quantum post-processing: The second device (5220) can obtain a quantum state identical to the quantum information |φ〉 that the first device (5210) wants to transmit by performing a unitary operation on the remaining one qubit of the Bell state that it has through the two classical bits received from the first device (5210).

[0630] quantum direct communication (QDC)

[0631] Quantum direct communication (QKD) is a method for securely transmitting classical message information. It shares similarities with quantum key distribution (QKD), a technology used in 4G and 5G secure communication, but there are also differences. Quantum key distribution (QKD) utilizes the unclonable nature of quantum mechanics to securely transmit message information transmitted over classical channels, sharing symmetric secret key information between the sender and receiver. In contrast, quantum direct communication (QD) shares the classical message information to be transmitted directly over the quantum channel, rather than a secret key.

[0632] Among quantum direct communication technologies, quantum secure direct communication (QSDC) boasts the advantage of not generating information leaks related to transmitted information, ensuring high reliability. A two-step QSDC technique utilizing entangled light sources is currently being studied. This two-step QSDC can be implemented based on super-dense coding techniques.

[0633] Super dense coding technique is a technique that can safely transmit classical information using quantum communication. It is a technique that can stably transmit 2 bits of classical information using the four types of single entangled photons (EPR-pairs) of [Mathematical Formula 43] below.

[0634]

[0635]

[0636]

[0637]

[0638] When using superdense coding, a transmitter can transmit two bits of classical information to a receiver using a single qubit through a quantum channel. First, two entangled qubits are created. The transmitter owns the first entangled qubit, and the receiver owns the second entangled qubit. There are four cases for the qubit that the transmitter wants to transmit: '00', '01', '10', and '11'. For each of the four cases above, the transmitter performs a qubit operation corresponding to each of the four cases on the entangled qubit it owns and then transmits it through the quantum channel. At this time, the qubit operation can be expressed in the form of I, Z, X, and iY. Each operation performed by the transmitter can change the entanglement state shared by the transmitter and receiver into a different basis form that is orthogonal to each other. Therefore, the receiver measures the qubit it owns and recovers the two bits of information transmitted by the transmitter.

[0639] FIG. 53 illustrates an example of a procedure for transmitting quantum information in a two-step quantum secure direct communication according to an embodiment of the present disclosure. In FIG. 53, SRs 1 to SR 4 are optical delay lines that serve as quantum memories. CEs (checking eavesdropping) 1 and CE 2 are devices that check for the presence of eavesdroppers. CMs (coding messages) encode classical message information to be transmitted from a transmitter (5310) to a receiver (5320). EPR sources generate entangled light sources in EPR states, and bell state measurement is a device that measures entangled photon pairs. Furthermore, in quantum communication, the transmitter (5310) may be referred to as the first device (5310) or Alice, and the receiver (5320) may be referred to as the second device (5320) or Bob, and the same notation may be used below.

[0640] In two-step quantum secure direct communication, unlike superdense coding, entangled photon pairs are not transmitted all at once, but are transmitted in two stages through an upper quantum channel and a lower quantum channel. To eavesdrop on the entangled light source, an eavesdropper must know information from both sides of the entangled photon pair to measure and decipher the transmitted information. To prevent eavesdropping, two-step quantum secure direct communication uses a method where one side of the entangled photon pair is transmitted first, and its security is verified against eavesdropping. Once security is guaranteed, the remaining part of the photon pair, which encodes the message information to be sent, is transmitted.

[0641] The definitions of symbols or abbreviations used below are as follows.

[0642] - EPP: entanglement purification protocol

[0643] - EDP: entanglement distillation protocol

[0644] - LOCC: local operator and classical communication

[0645] - QSDC: quantum secure direct communication

[0646] - F: fidelity of initial mixed state

[0647] - or : success probability or pass probability

[0648] - : channel threshold

[0649] - : measurement error rate

[0650] - ECC: error correcting code

[0651] In QPA or single-choice protocols, the error of the measurement operator is determined by the channel threshold ( ) and increase the probability that the measurement results will match ( or ) can be a cause of reducing the error. Therefore, a technique can be proposed in which the sender and the receiver each utilize local ancilla qubits to resolve the error of the measurement operator. As an example, a measurement error filtering technique utilizing the local ancilla described above in FIG. 18 can be proposed. When the measurement error filtering technique is applied, the channel threshold is as shown in [Table 3] below. In this disclosure, unlike measurement error filtering, a technique is proposed that can efficiently control the measurement error by using an error correction code.

[0652] The present disclosure proposes a technique for measuring a plurality of target qubits after collecting target qubits for measurement and performing error correction encoding on the target qubits. The present disclosure can be applied when measurement is required for a plurality of target qubits for measurement. Here, the target qubits for measurement may be qubits on which measurement is to be performed in an entanglement distillation protocol (e.g., qubits on which a CNOT operation is performed). As an example, the target qubits for measurement may be target qubits on which measurement is to be performed after a CNOT operation in a QPA. As another example, the target qubits for measurement may be qubits on which measurement is to be performed in an X basis or a Z basis after a CNOT operation is performed twice in a dual-selection protocol.

[0653] The present disclosure proposes a technique for performing error correction encoding on target qubits measured in the Z basis after a CNOT operation, and then measuring the result of the error correction encoding. Therefore, the qubits measured in the Z basis after the CNOT operation can be set as measurement target qubits to be encoded based on the error correction code. A QPA protocol using a pair of control qubits and a pair of target qubits can convert control qubits with low fidelity into qubits with high fidelity using the measurement results of the target qubits. At this time, a technique utilizing a local ancilla as shown in FIG. 18 can be performed. In the technique utilizing a local ancilla as shown in FIG. 18, a separate ancilla bit is applied to each qubit. In contrast, the present disclosure can convert multiple pairs of target qubits into qubits with high fidelity using multiple pairs of control qubits and multiple pairs of target qubits.

[0654] In addition, the present disclosure can be applied to various entanglement distillation protocols as well as the QPA protocol. As shown in Fig. 19, ρ (0) Qubit of position, ρ (1) Qubits and ρ of the position (2) In a dual-choice entanglement distillation protocol using qubits in a position, the qubits to be measured at various stages of the dual-choice entanglement distillation protocol can be encoded using a single error-correcting code. Specifically, ρ of the dual-choice EDP at various stages (1) Qubits of the position and ρ (2) The qubits in the position can be set as the measurement target qubits based on the error correction code. Afterwards, the measurement target qubits can be encoded and decoded with the error correction code. Through this process, ρ (1) Qubits and ρ of the position (2) Measurement errors for the qubits in the position can be eliminated. Based on the subsequent measurement results, ρ (0) It can be determined whether the qubit of the position is preserved or not.

[0655] Figure 54a illustrates an example of a procedure for independently performing four QPA protocols according to one embodiment of the present disclosure. Referring to Figure 54a, Alice and Bob have ρ (0) Let ρ be the control qubit, and (1) A CNOT operation that sets the target qubit can be performed. Therefore, the QPA protocol can be performed for each of the four pairs of control qubits and the four pairs of target qubits. Therefore, Alice can compare the measurement result of the target qubit corresponding to one control qubit with the measurement result of the target qubit measured by Bob to determine whether the control qubit has been converted to a high-fidelity entangled state or can be preserved. That is, measurements on the four target qubits (5401-1 to 5407-1) can be performed individually. At this time, as shown in FIG. 18, after measuring one target qubit (5401-1) after an operation with at least one ancilla qubit, the measurement result for the target qubit (5401-1) and the measurement result with at least one ancilla qubit can be combined to determine whether the control qubit can be reused. If three ancilla bits are utilized for each of the four protocols, a total of 12 ancilla bits are required. This disclosure proposes a method for reducing the number of ancilla qubits used. If target qubits are encoded and then decoded using a single error-correcting code, the ancilla bit can be used to correct multiple target qubits. Therefore, the number of required ancilla bits can be reduced. This disclosure proposes a method for encoding and decoding multiple target qubits using a quantum error-correcting code, thereby determining whether to reuse control qubits using the error-correcting code.

[0656] FIG. 54B illustrates an example of a procedure for measuring target qubits by utilizing an extended Hamming code according to an embodiment of the present disclosure. For convenience of explanation, it is assumed that the QPA protocol of FIG. 53A is used. Therefore, in order to perform the entanglement distillation procedure in FIG. 54B, it is assumed that Alice performs a CNOT operation with control qubits and target qubits (5401-1 to 5407-1 of FIG. 54A) as input. Here, the (m, n) extended Hamming code means encoding n information bits using a total of m bits. Therefore, mn parity bits are required to encode n information bits. Each parity bit is calculated as the XOR result of the data bits corresponding to a specific position. The extended Hamming code can detect up to 2-bit errors by including additional parity bits. Therefore, the reliability for correction and detection can be increased by using the extended Hamming code compared to the Hamming code. For convenience of explanation below, Alice decides to use the (8, 4) extended Hamming code as an error-correcting code. That is, the measurement target qubits (5401-2 to 5407-2) can be set to four target qubits (5401-1 to 5407-1), and errors can be corrected using four ansilla bits.

[0657] To use the (8,4) extended Hamming code, four (=8-4) parity bits are required. At this time, the four parity bits can be set using four ancilla bits. In Fig. 54b, the ancilla bits are represented as |0>. Alice can generate eight qubits by encoding the four measurement target qubits (5401-2 to 5407-2) and the four ancilla bits using the (8,4) extended Hamming code, as shown in Fig. 54b. After this, Alice can obtain the encoded classical bits by measuring the eight encoded qubits. Alice and Bob then share the obtained classical bits with Bob. Alice and Bob can decide whether to preserve the control qubits based on the information of the shared classical bits. At this time, Bob can use the same (8,4) extended Hamming code of Fig. 54b as Alice to measure the measurement target qubits. Alice and Bob can decide to share the measurement results for the four target qubits and preserve the control qubits corresponding to the matched qubits among the four target qubits. For convenience of explanation, Alice and Bob are described as using error-correcting codes when using the QPA protocol, but this can also be applied to other entanglement distillation protocols that require measurement. Below, we describe how error-correcting codes are utilized in the dual-choice EDP.

[0658] FIG. 54C illustrates examples of qubits to be measured to be encoded with error correction codes in a dual-selection EDP according to one embodiment of the present disclosure. Alice and Bob in FIG. 54C may perform some or all of the procedures described above in FIG. 19 to perform the dual-selection EDP. As described above in FIG. 19, in order to determine whether a pair of qubits are preserved, Alice must perform Z-basis measurements and X-basis measurements on two qubits. The measurement value of the X-basis for a specific qubit can be replaced by the measurement value of the Z-basis for a specific qubit on which the Hamada operation is performed. Therefore, when performing the dual-selection EDP once, measurements on the Z-basis measurement qubits (5401-3, 5403-3) must be performed. At this time, Alice may perform measurements on the first dual-selection EDP and the second dual-selection EDP based on error correction codes. That is, the Z basis measurement qubits (5401-3, 5403-3) in the first dual-selection EDP and the Z basis measurement qubits (5405-3, 5407-3) in the second dual-selection EDP can be encoded through a single error correction code circuit. That is, Alice can set the Z basis measurement qubits (5401-3 to 5407-3) to the four measurement target qubits (5401-2 to 5407-2 in FIG. 54b) of the error correction code. Therefore, Alice can utilize the (8,4) extended hamming code, which is an error correction code.

[0659] Afterwards, Alice can obtain the measurement values ​​for the Z basis measurement qubits (5401-3, 5403-3) in the first dual-selection EDP and the Z basis measurement qubits (5405-3, 5407-3) in the second dual-selection EDP by measuring and decoding the encoded measurement target qubits (5401-2 to 5407-2). Afterwards, Alice and Bob share the measurement results and decide whether to preserve the qubits.

[0660] Although Alice encodes the Z basis measurement qubits (5401-1 to 5407-1, 5401-3 to 5407-3) based on the error correction code in FIGS. 54a to 54c, Bob can also encode the Z basis measurement qubits (5409-1 to 5415-1, 5409-3 to 5415-3) in the same manner as Alice. Accordingly, Bob can set the Z basis measurement qubits (5409-1 to 5415-1, 5409-3 to 5415-3) as the measurement target qubits (5401-2 to 5407-2) to be measured based on the error correction code.

[0661] FIG. 55 illustrates an example of a communication device performing an entanglement distillation procedure using an error correction code according to an embodiment of the present disclosure. FIG. 55 illustrates a method performed by a device performing quantum communication (Alice and Bob of FIG. 26, Alice and Bob of FIG. 28, Alice and Bob of FIG. 29, devices (4910, 4920) of FIG. 49, and devices (5010, 5020) of FIG. 50). In the description referring to FIG. 55, the operating subject is referred to as a first device, and the first device is a device included in a quantum network and can perform a role such as a transmitting node or a receiving node. In this case, when the first device performs a role as a transmitting node, it can be referred to as Alice, and when it performs a role as a receiving node, it can be referred to as Bob.

[0662] Referring to FIG. 55, in step S5501, the first device performs a connection establishment procedure. The first device can connect to other devices via a classical channel or a quantum channel through an initial connection procedure. To perform the initial connection procedure, the first device can detect a synchronization signal and receive system information. The first device can transmit a signal for initial connection (e.g., a random access preamble) to a control device and receive a response signal to the signal for initial connection from the control device. Here, the system information can include information related to the properties or characteristics of the control device for performing quantum communication. The system information can be transmitted via a master information block (MIB) and a system information block (SIB).

[0663] In step S5503, the first device performs a configuration procedure related to an error correction code. The first device can share configuration information related to the error correction code with a second device that performs communication using a quantum state. That is, the first device can receive configuration information related to the error correction code from the second device and transmit the configuration information related to the error correction code to the second device. At this time, the configuration information may include information regarding the number of measurement target qubits to be measured by the first device and the second device using the error correction code. For example, the configuration information transmitted from the first device to the second device may include the number of measurement target qubits of the first error correction code used by the first device. Furthermore, the configuration information transmitted from the second device to the first device may include the number of measurement target qubits of the second error correction code used by the second device. At this time, the configuration information is not limited to a specific form. That is, the configuration information related to the error correction code may be transmitted using at least one of the number of information bits to be used for the error correction code or the number of parity bits.

[0664] In step S5505, the first device performs an entanglement distillation procedure based on an error-correcting code. The entanglement distillation protocol is not limited to a specific protocol. For example, the entanglement distillation protocol may use a single-selection protocol or a QPA protocol based on an error-correcting code. Here, the parity bits of the error-correcting code may be determined using ancilla bits. The first device may perform the distillation protocol based on the first error-correcting code and then determine which qubits to preserve.

[0665] In step S5507, the first device transmits data using the converted qubits based on the entanglement distillation protocol. Whether the control qubits converted using the entanglement distillation protocol are preserved can be determined based on whether the target qubits match. The first device transmits data based on the preserved qubits. Since qubits in an entangled state are formed between the first device and the second device through the entanglement distillation protocol, data can be transmitted using the qubits in the entangled state. At this time, if the first device is a receiving device, the first device can receive the data using the converted qubits.

[0666] In FIG. 55, the configuration information is described as transmitting information regarding the error correction codes to be used by the first device and the second device, but is not limited thereto. That is, it can be implemented in a form in which one device configures settings related to the error correction code and then transmits them to another device. For example, the first device can determine the number of qubits to be measured for the first error correction code to be used by the first device and the number of qubits to be measured for the second error correction code to be used by the second device, and transmit the number of qubits to be measured for the first error correction code to the second device. Alternatively, the second device can determine the number of qubits to be measured. Alternatively, the third device can determine the settings for the first error correction code and the second error correction code, and transmit the settings for the error correction code to the first device and the second device.

[0667] Using the method described in Figure 55, an entanglement distillation protocol can be performed based on error-correcting codes, and quantum communication can be performed using preserved qubits. Below, the specific process of performing the entanglement distillation protocol based on error-correcting codes is described.

[0668] Fig. 56 illustrates an example in which a first device according to an embodiment of the present disclosure corrects a measurement error based on an error correction code. Fig. 56 illustrates a method performed by a device performing quantum communication (Alice and Bob of Fig. 26, Alice and Bob of Fig. 28, Alice and Bob of Fig. 29, devices (4910, 4920) of Fig. 49, and devices (5010, 5020) of Fig. 50). In the description with reference to Fig. 56, the operating subject is referred to as the first device, and the first device is a device included in a quantum network and can perform a role such as a transmitting node, a receiving node, etc. In this case, when the first device performs a role as a transmitting node, it can be referred to as Alice, and when it performs a role as a receiving node, it can be referred to as Bob.

[0669] Referring to FIG. 56, in step S5601, the first device distributes qubits in a quantum entangled state. To this end, the first device can generate a pair of entangled qubits composed of a first qubit and a second qubit. One qubit of the pair of qubits can be stored in the first device, and the other qubit can be transmitted to the second device. Multiple pairs of qubits in an entangled state can be shared. Accordingly, the first device can generate multiple pairs of entangled qubits, store one qubit of each pair of qubits, and transmit the other qubit to the second device.

[0670] In step S5603, the first device performs a CNOT operation. The first device performs a CNOT operation that sets one of the qubits stored in the first device as a control qubit and sets the other qubit as a target qubit. By repeatedly performing this CNOT operation, the first device can obtain output qubits of a plurality of target qubits on which the CNOT operation has been performed. The output qubits of the plurality of target qubits thus generated are set as target qubits for measurement of an error-correcting code.

[0671] In step S5605, the first device encodes the qubits to be measured and at least one ancilla qubit based on an error correction code. Here, the ancilla qubit is an auxiliary qubit used in quantum computing, and refers to a qubit that is mainly used to temporarily store a state required in an intermediate process of calculation or for error detection and correction in quantum algorithms. At this time, the output qubits of the qubits to be measured are set as information bits of the error correction code, and at least one ancilla qubit is set as a parity bit.

[0672] In step S5607, the first device measures the encoded qubits. The basis for the measurement may be set in advance. For example, the encoded qubits may be measured using the Z basis. Accordingly, the first device can obtain classical bits by measuring the qubits to be measured.

[0673] In step S5609, the first device checks whether there is an error based on the measurement result. The first device can obtain information bits by decoding the classical bits obtained through the measurement. At this time, a correction procedure can be performed on the information bits based on the parity bits among the classical bits obtained through the measurement. As a result, in step S5605, the first device can check the measurement results for the measurement target qubits set as information bits. That is, the measured classical bits can be divided into information bits and parity bits, and the first device can check whether there is an error by decoding an error correction code based on the parity bit.

[0674] In step S5611, the first device shares the measurement results with the second device. The first device transmits the measurement results regarding the qubits to be measured to the second device, and receives the results measured by the second device from the second device. The measurement results regarding the qubits to be measured may include at least one of the measurement values ​​of the qubits to be measured after the CNOT operation or whether the decoding was successful. If the decoding is successful, the measurement result may transmit the measurement values ​​of the output qubits of the qubits to be measured that were successfully measured. If the decoding fails, the first device may transmit information indicating the failure using one bit.

[0675] In step S5613, the first device determines whether to use the control qubits. It compares the measurement values ​​of the measurement target qubits received from the second device with the measurement values ​​of the measurement target qubits measured by itself, and determines the positions of the measurement target qubits having the same measurement values. The first device determines that the output qubits for the control qubits formed after the CNOT operation, whose measurement result values ​​correspond to the positions of the measurement target qubits having the same measurement values, are to be used for quantum communication.

[0676] In Fig. 55, it is described that the first device generates an entangled qubit pair, but this is not limited thereto. For example, the entangled qubit pair may be pre-distributed, in which case step S5601 may be omitted. In addition, the entangled qubit pair may be generated by the second device and then distributed to the first device. In another example, after the third device generates an entangled qubit pair, it may transfer one qubit from each pair of qubits to the first device and the remaining one qubit to the second device.

[0677] Also, the type of the second error correction code used by the second device does not necessarily have to be the same as the first error correction code used by the first device. For example, the first device may use a (3, 1) error correction code, and the second device may use an (8, 4) error correction code. In this case, since the (3, 1) error correction code can obtain a result for one bit using three bits, the first device can obtain a measurement result for one target qubit using the (3, 1) error correction code. Therefore, the first device can perform the (3, 1) error correction code four times to obtain measurement results for four target qubits and sequentially transmit the measurement results to the second device. The second device can determine whether the control qubit is preserved by comparing the measurement results for the four target qubits measured using the (8, 4) error correction code with the measurement results transmitted from the first device. Additionally, the first error correction code used by the first device may be set to a Hamming code, and the second error correction code used by the second device may be set to a Bose-Chaudhuri-Hocquenghem (BCH) code.

[0678] In step S5603 of FIG. 56, it has been described that the control qubit of the CNOT operation is set to a bit that determines whether to preserve, and the target qubit of the CNOT operation is set to the qubits to be measured, but this is not limited thereto. For example, a first CNOT operation and a second CNOT operation may be performed in a single entanglement distillation protocol, such as a double-choice entanglement distillation protocol, and measurement results for two qubits may be required. In this case, the output qubit for the control qubit of the first CNOT operation may be set to a qubit for which preservation is determined, and the output qubit for the target qubit of the first CNOT operation may be input as the control qubit of the second CNOT operation. In this case, the measurement results for both the control qubit of the second CNOT operation and the output qubits for the target qubit are required, and both the control qubit and the output qubits for the target qubit of the second CNOT operation may become qubits to be measured. Here, a Hamada operation can first be performed on the output qubit for the target qubit of the second CNOT operation to measure in the same Z basis.

[0679] Fig. 57 illustrates an example of a procedure diagram of an entanglement distillation protocol based on an error correction code according to an embodiment of the present disclosure. Fig. 57 illustrates a method performed by devices performing quantum communication (Alice and Bob of Fig. 26, Alice and Bob of Fig. 28, Alice and Bob of Fig. 29, devices (4910, 4920) of Fig. 49, and devices (5010, 5020) of Fig. 50). In the description with reference to Fig. 57, the operating subjects are referred to as a first device and a second device, and the first device and the second device are devices included in a quantum network and can perform roles such as a transmitting node, a receiving node, etc. At this time, when the first device or the second device performs the role of a transmitting node, it can be referred to as Alice, and when it performs the role of a receiving node, it can be referred to as Bob. In Fig. 57, the first device Using error correction codes, the second device It is assumed that error correction codes are utilized. The first and second devices may be a base station and a terminal, respectively. For convenience of explanation, the first and second devices are assumed to perform QPA as illustrated in FIG. 13, but the present disclosure is not limited thereto.

[0680] In step S5701, the first device or the second device generates an EPR pair and transmits one qubit from the EPR pair to the other device. For convenience of explanation, it is assumed below that the first device generates an EPR pair and transmits one of the qubits included in the EPR pair to the second device. Step S5701 may be performed repeatedly, and as a result, the first device and the second device may share the qubits of multiple EPR pairs.

[0681] In step S5703, the first device and the second device perform a CNOT operation for a single-selection EPP. The first device selects a qubit ρ among the qubits divided in step S5705. (0) Let ρ be the control qubit, and qubit ρ (1) The CNOT operation is performed with the target qubit as the target qubit. The second device also performs the qubit ρ (0) A qubit ρ that is entangled with (0)' Let ρ be the control qubit, and qubit ρ (1) A qubit ρ that is entangled with (1)' A CNOT operation is performed with target qubits. At this time, if multiple target qubits are included in the input of one error correction code encoding circuit, step S5703 can be repeatedly performed. Therefore, as a result of performing the CNOT operation, multiple control qubits ρ (0) The output qubits of the fields, the target qubit ρ (1) The output qubits of the control qubit ρ (0)' The output qubits and the target qubit ρ (1)'The output qubits of the fields can be generated. At this time, the output qubit of a specific qubit means the qubit that is output at that position after a CNOT operation of a specific qubit with another qubit.

[0682] In step S5705, the first device and the second device prepare an ancillary qubit and perform an error correction code encoding circuit. The first device Since it utilizes error correction codes, the error correction codes are qubit ρ of the dog (1) is used to measure the output qubits of the fields. The first device is Prepare the dog's ancilla qubits. That is, qubit ρ of the dog (1) The output qubits of the An error correction code encoding circuit is performed using the anscilla qubits of the dog. Similarly, the second device is the first device. Because it utilizes error correction codes, qubit ρ of the dog (1)' The output qubits of the An error-correcting code encoding circuit is implemented using ancillar qubits.

[0683] At step S5707, the first device and the second device measure the encoded qubits in the Z basis. Therefore, the first device The measurement results of the dog can be obtained, and the second device You can obtain the measurement results of the dog.

[0684] In step S5709, the first device and the second device perform error correction code decoding based on the measurement results. The first device By performing error correction code decoding based on the measurement results of the dog, qubit ρ of the dog (1) Classical bit information about the output qubits of the can be estimated. Similarly, the first device By performing error correction code decoding based on the measurement results of the dog, qubit ρ of the dog (1)' Classical bit information about the output qubits of the can be estimated.

[0685] In step S5711, the first device and the second device determine whether decoding is successful. The first device and the second device can determine whether decoding is successful in the following manner. (Detection): or If the syndrome bit is a zero-error syndrome, the decryption is considered successful and the classical bit information is estimated. That is, the first device is the classical bit information. can be estimated, and the second device is classical bit information. can be estimated.

[0686] (Correction): or Except for the zero-error syndrome among the syndrome bits, in the case of correctable error syndrome, decryption is judged to be successful and classical bit information is estimated. That is, the first device is classical bit information. can be estimated, and the second device is classical bit information. can be estimated. If decoding is successful, step S5715 is performed, and if decoding fails, step S5713 is performed.

[0687] In step S5713, the first device and the second device decide to discard the control bit corresponding to the classical bit if the decoding fails. That is, the qubit ρ corresponding to the classical bit in step S5501 (0) The output qubit and qubit ρ (0)' The output qubit is discarded.

[0688] At step S5715, the first device and the second device successfully decrypt the classical bits and classic beats Share information about the first and second devices. The first and second devices share a shared classical bit and classic beats Compare the qubit ρ corresponding to the classical bit with the classical bit having the same value. (0) The output qubit and qubit ρ (0)' The entanglement state of the output qubit is preserved, and the entanglement state corresponding to the classical bit with a different value is discarded.

[0689] Referring to Figure 55, the first device and the second device can each use different error correction codes, and can determine whether to preserve the control qubits based on the error correction codes. At this time, the classical bits and classic beats The method of conveying information about can be determined in various ways. For example, the first device and the second device and A method of sharing in advance can be used. If the first device fails to decode based on the error correction code, it can transmit information indicating the decoding failure or information indicating the discarding of the control qubits to the second device. In this case, the second device Because the values ​​are transmitted in advance, the first device can know the number of control qubits to be discarded, and the second device can also discard the qubits it stores that correspond to the control qubits discarded by the first device. Similarly, the second device can transmit information indicating a decoding failure or the discarding of control qubits to the first device.

[0690] Fig. 58 illustrates a first example of signaling performed in an entanglement distillation protocol based on an error correction code according to one embodiment of the present disclosure. Fig. 58 illustrates a method performed by devices performing quantum communication (Alice and Bob of Fig. 26, Alice and Bob of Fig. 28, Alice and Bob of Fig. 29, devices (4910, 4920) of Fig. 49, and devices (5010, 5020) of Fig. 50). In the description referring to Fig. 58, the operating subjects are referred to as a first device (5810) and a second device (5820), and the first device (5810) and the second device (5820) are devices included in a quantum network and can perform roles such as a transmitting node and a receiving node. In this case, when the first device (5810) or the second device (5820) performs the role of a transmitting node, it can be referred to as Alice, and when it performs the role of a receiving node, it can be referred to as Bob. In Fig. 58, the first device (5810) Using error correction codes, the second device (5820) It is assumed that an error correction code is utilized. The first device (5810) and the second device (5820) can be a base station and a terminal, respectively.

[0691] Referring to Fig. 58, in step S5801, parameter values ​​related to error correction codes are shared. The parameter values ​​related to error correction codes are the number of measurement target qubits used for error correction codes. or The information qubits of the error correction code can be set to the measurement target qubits. The method of sharing the parameter values ​​related to the error correction code is not limited to a specific method. For example, when the first device (5810) acts as a control device (e.g., a base station), the first device (5810) may share the error correction code parameter values. and Determine all the values ​​and send them to the second device (5820). and can be transmitted. As another example, the first device (5810) can transmit to the second device (5820). The value is passed, and the second device (5820) to the first device (5810). can pass values. As another example, both the first device (5810) and the second device (5820) and The value can be provided in advance or received from another third device. It is assumed that the first device (5810) and the second device (5820) share entangled qubits and perform the CNOT operation of the entanglement distillation protocol.

[0692] At step S5803, the first device (5810) The error correction code procedure is performed, and at step S5805, the second device (5820) An error correction code procedure is performed. Here, the error correction code procedure is performed based on the output qubit and ansilla bit of the target qubit generated after the CNOT operation. At this time, the error correction code used by the first device (5810) and the error correction code used by the second device (5820) must use the same type of error correction code, or different types of error correction codes may be used. For example, the error correction code used by the first device (5810) may be an extended hamming code, and the error correction code used by the second device (5820) may be a Bose-Chaudhuri-Hocquenghem (BCH) code. In addition, although the first device (5810) and the second device (5820) use the same type of error correction code, which is an extended hamming code, the number of target qubits for error correction code measurement may be set differently. That is, and The values ​​may be set differently.

[0693] In step S5807, the first device (5810) transmits a decoding success indicator to the second device (5820). The method for determining whether decoding is successful may be set differently depending on the type of error correction code. For example, if the measurement result of the ancilla bits is zero-error syndrome or correctable error syndrome, decoding may be determined to be successful. The decoding success indicator may be composed of a 1-bit field value, where '0' may indicate decoding success and '1' may indicate decoding failure. It is also possible to define '0' as decoding failure and '1' as decoding success. If the second device (5820) receives a value corresponding to a decoding success, the second device (5820) performs step S5813, and the second device (5820) that received an indicator corresponding to a decoding failure measures the number of target qubits of the error correction code of the first device (5810). Discard as many control qubits as possible.

[0694] In step S5809, the second device (5820) transmits a decoding success indicator to the first device (5810). If the first device (5810) receives a value corresponding to a decoding success, the first device (5810) performs step S5811. On the other hand, if the first device (5810) receives an indicator corresponding to a decoding failure, the first device (5810) measures the number of target qubits of the error correction code of the second device (5820). Discard as many control qubits as possible.

[0695] In step S5811, the first device (5810) transmits the measurement result to the second device (5820). If the first device (5810) has successfully decoded and has received an indicator indicating successful decoding from the second device (5820), the decoding is successful. Transmits the dog information bit to the second device (5820).

[0696] In step S5813, the second device (5820) transmits the measurement result to the first device (5810). If the second device (5820) has successfully decoded and has received an indicator indicating successful decoding from the first device (5810), the second device (5820) indicates that the decoding was successful. Transmits the dog information bit to the first device (5810).

[0697] Using the procedure described above in Figure 58, successfully decoded information bits can be exchanged. The first and second devices can then compare the information bits they decoded with the information bits decoded by the other device. Since the information bits of the error-correcting code are measurement results of the target bits, the first and second devices can decide to store the control qubits corresponding to the information bits with the same value.

[0698] Fig. 59 illustrates a second example of signaling performed in an entanglement distillation protocol based on an error correction code according to an embodiment of the present disclosure. Fig. 59 illustrates a method performed by devices performing quantum communication (Alice and Bob of Fig. 26, Alice and Bob of Fig. 28, Alice and Bob of Fig. 29, devices (4910, 4920) of Fig. 49, and devices (5010, 5020) of Fig. 50). In the description referring to Fig. 59, the operating subjects are referred to as a first device (5910) and a second device (5920), and the first device (5910) and the second device (5920) are devices included in a quantum network and can perform roles such as a transmitting node and a receiving node. In this case, when the first device (5910) or the second device (5920) performs the role of a transmitting node, it can be referred to as Alice, and when it performs the role of a receiving node, it can be referred to as Bob. In Fig. 59, it is assumed that the first device (5910) utilizes a (3, 1) error correction code, and the second device (5920) utilizes an (8, 4) error correction code. The first device (5910) and the second device (5920) may be a base station and a terminal, respectively.

[0699] In step S5901, the first device (5910) and the second device (5920) perform a connection establishment procedure. Through the connection establishment procedure, a quantum channel or classical channel through which the first device (5910) and the second device (5920) can communicate can be established.

[0700] In step S5903, the first device (5910) and the second device (5920) share configuration information. The configuration information may include parameters related to an error correction code. For example, the configuration information may include at least one of the number of measurement target qubits of the first error correction code used by the first device (5910) or the number of measurement target qubits of the second error correction code used by the second device (5920). The configuration information may be transmitted through the classical channel established in step S5901. At this time, the information bits of the error correction code may be set to the measurement target qubits, and at least one parity bit may be set to at least one ancilla qubit.

[0701] In step S5905, the first device (5910) transmits a qubit to the second device (5920). The first device (5910) can generate entangled qubit pairs and divide the qubit pairs to generate a first signal and a second signal. The qubit transmitted to the second device (5920) can be included in the second signal and transmitted. For convenience of explanation, it is assumed that the first signal includes a first qubit and a third qubit, and it is assumed that the second signal includes a second qubit and a fourth qubit. In this case, the first qubit and the second qubit are qubits included in one entangled qubit pair, and the third qubit and the fourth qubit are qubits included in another entangled qubit pair.

[0702] In step S5907, the first device (5910) performs a CNOT operation. The first device (5910) can set the first qubit as a control qubit of the CNOT operation and the third qubit as a target qubit of the CNOT operation. The first device (5910) can perform a CNOT operation using the first qubit and the third qubit as inputs, and obtain a first output qubit corresponding to the first qubit and a third output qubit corresponding to the third qubit. The first device (5910) sets the third output qubit as a qubit to be measured.

[0703] In step S5909, the second device (5920) performs a CNOT operation. The second device (5920) can set the second qubit as a control qubit of the CNOT operation and the fourth qubit as a target qubit of the CNOT operation. The second device (5920) can perform a CNOT operation using the second qubit and the fourth qubit as inputs, and obtain a second output qubit corresponding to the second qubit and a fourth output qubit corresponding to the fourth qubit. The second device (5920) sets the fourth output qubit as a qubit to be measured.

[0704] In step S5911, the first device (5910) encodes the measurement target qubit and the anscilla qubit based on the error correction code and then measures the result. Since it is assumed that the first device (5910) uses the (8, 4) error correction code, the first device (5910) can set four target qubits as output target qubits, perform encoding using the four output target qubits and the four anscilla qubits, and then measure the encoded result.

[0705] In step S5913, the second device (5920) encodes the output qubit and anscilla qubit of the target qubit based on an error correction code, and then measures the result. For convenience of explanation, it is assumed that the second device (5920) uses a (3, 1) error correction code. Therefore, the second device (5920) can set one target qubit as an output target qubit, perform encoding using one output target qubit and two anscilla qubits, and measure the encoded result.

[0706] At step S5915, the first device (5910) checks for errors based on the measurement results. The first device (5910) can determine whether there are any errors by decoding the measurement results. If the decoding is successful without errors, the first device (5910) can obtain classical information about the four control qubits. At this time, it is assumed that the first device (5910) obtains '0011' through the (8, 4) error correction code.

[0707] In step S5917, the second device (5920) checks whether there is an error based on the measurement result. The second device (5920) checks whether there is an error based on the measurement result. The second device (5920) can check whether there is an error by decoding the measurement result. If the decoding is successful without an error, the first device (5910) can obtain classical information of the output qubit for one target qubit. At this time, the number of target qubits for the error correction code used by the first device (5910) or the number of target qubits for the error correction code used by the second device (5920) is previously shared. The first device (5910) and the second device (5920) can be set to obtain information for the same number of target qubits. Therefore, the second device (5920) can obtain classical information about the output qubits of the four target qubits by repeating the (3, 1) error correction code procedure four times. At this time, it is assumed that the second device (5920) performs the (3, 1) error correction code four times and obtains '0001'.

[0708] In step S5919, the first device (5910) and the second device (5920) share information related to the measurement results. That is, the first device (5910) transmits '0011' to the second device (5920), and the second device (5920) transmits '0001' to the first device (5910).

[0709] In steps S5921 and S5923, the first device (5910) and the second device (5920) determine whether to use the control qubit. Since the first device (5910) and the second device (5920) know their own measurement results and the other party's measurement results, they can determine which qubits to preserve. Since '0011' and '0001' differ only in the third bit and the rest are the same, the output qubit of the control qubit corresponding to the third bit is discarded, and the output qubits of the control qubits corresponding to the 1st, 2nd, and 4th bits are preserved. If the first bit is the measurement result regarding the output bit of the third qubit and the output bit of the fourth qubit, since the first bits are both '0', the first output qubit and the second output qubit, which are the output qubits of the corresponding control qubits, are preserved. Conversely, if the third bit is the measurement result of the output bit of the third qubit and the output bit of the fourth qubit, the third bit has different values ​​of '1' and '0', so the first output qubit and the second output qubit, which are the output qubits of the corresponding control qubit, are discarded.

[0710] In step S5925, the first device (5910) and the second device (5920) perform quantum communication. The first device (5910) and the second device (5920) can perform quantum communication using the qubits preserved in step S5923.

[0711] The method described above in FIG. 59 is described as performing one CNOT operation in one-step entanglement distillation protocol, but is not limited thereto. For example, multiple CNOT operations or other operations may be performed in one-step entanglement distillation protocol. Accordingly, multiple measurement target qubits may be set in the entanglement distillation protocol, and the multiple measurement target qubits may be encoded using an error correction code. If a dual-choice entanglement protocol is used, whether the first qubit and the second qubit are preserved may be determined using two qubits. In this case, the fifth qubit and the sixth qubit, which are entangled qubit pairs, may be further included in the first signal and the second signal. That is, the first signal may further include the fifth qubit, and the second signal may further include the sixth qubit. At this time, the first device (5910) may further include the first qubit (e.g., p in FIG. 19). (0) qubit of the position) and the third qubit (e.g., p in Fig. 19 (1) The first CNOT operation is performed with the qubit of the third qubit as input, and the output qubit of the first CNOT operation corresponding to the third qubit and the fifth qubit (p in Fig. 19) are output. (2) A second CNOT operation can be performed using the qubits of the position as input. Accordingly, the measurement target qubits on which the first device (5910) performs measurement based on the error correction code may include the output qubits of the second CNOT operation.

[0712] Using the method described above, measurement errors can be corrected, and the output fidelity and success probability of the entanglement distillation protocol can be improved. When measurement errors are corrected using the technique proposed in this disclosure, the output fidelity of the entanglement distillation protocol can be improved. and success rate The performance can be expressed as follows [Mathematical Formula 44].

[0713]

[0714] In [Equation 44], and is the probability that the error-correcting code correctly estimates the bits without error and the probability that an error occurs when the sender and receiver each succeed in decoding, and is determined by the performance of the error-correcting code. Is Among the error patterns that cause syndromes, it refers to errors that are correctly corrected. Is Among the error patterns that cause syndromes, it refers to an error pattern that is not corrected correctly and causes a codeword error. refers to a set of syndrome patterns that perform error correction.

[0715] Below, we describe a performance comparison according to the error correction codes used by the sender and receiver.

[0716] Example 1) When both the sender and receiver use the (8,4) extended Hamming code.

[0717] The sender and receiver can utilize the extended Hamming code for measurement error control, as shown in Fig. 54b. (8,4) The extended Hamming code is a code that can correctly correct up to one error and detect two errors. In the following, if it is determined that two errors have occurred, it is defined that the decryption was not successful. (8,4) When the extended Hamming code is used, when the entanglement distillation protocol using measurement error filtering with n = m = 2 is used, and when no correction is made, the performances can be expressed as shown in Figs. 60 to 62, respectively.

[0718] Figures 60a and 60b illustrate gate errors according to one embodiment of the present disclosure. m When =0.05, the performance of output fidelity and success probability for input fidelity is shown. Figures 61a and 61b show that the gate error according to one embodiment of the present disclosure is pm When =0.1, the performance of output fidelity and success probability for input fidelity is shown. Figures 62a and 62b show that the gate error according to one embodiment of the present disclosure is p m When =0.164, the performance of output fidelity and success probability for input fidelity is shown. In Figs. 60 to 62, the case of using the (8,4) extended Hamming code is denoted as 'Extended Hamming(8,4)', the case of using the detection mode among the cases of using the entanglement distillation protocol with measurement error filtering where n=m=2 is denoted as 'n=m=2(detecting)', and the case of not making any correction is denoted as 'no correction'.

[0719] Referring to FIGS. 60 to 62, the entanglement distillation protocol using measurement error filtering where n = m = 2 requires one ansilla bit when measuring one target qubit. Therefore, a total of four ansilla bits are required to measure four target qubits. The (8,4) extended Hamming code also requires four ansilla bits to measure four target qubits. In other words, the entanglement distillation protocol using measurement error filtering and the proposed technique using the (8,4) extended Hamming code were compared in an environment where the same number of ansilla bits were used, and they showed similar output fidelity values. However, the proposed technique using the (8,4) extended Hamming code has a higher success probability than the entanglement distillation protocol using measurement error filtering. In addition, the proposed technique using the (8,4) extended Hamming code has a higher output fidelity than the technique that does not make any correction, although there are cases where the encoding fails, and the success probability is different. This means that the proposed technique has a lower channel threshold compared to the technique without any correction.

[0720] Example 2) When both the sender and receiver use the (15, 5) BCH (Bose-Chaudhuri-Hocquenghem) code

[0721] The sender and receiver can use the BCH code. (15, 5) The BCH code can correctly correct up to three errors and can correct errors that are estimated to have occurred more than four errors. When using the (15, 5) BCH code, the performance of the entanglement distillation protocol with measurement error filtering where n = m = 3 and no correction can be obtained can be as shown in Figures 63 to 65.

[0722] Figures 63a to 63d illustrate gate errors according to one embodiment of the present disclosure. m When =0.05, the performance of output fidelity and success probability for input fidelity is shown. Figures 64a and 64d show that the gate error according to one embodiment of the present disclosure is p m When =0.1, the performance of output fidelity and success probability for input fidelity is shown. Figures 65a and 65c show that the gate error according to one embodiment of the present disclosure is p m When =0.164, the performance of output fidelity and success probability for input fidelity is shown. In Figs. 63 to 65, the case of using the (15, 5) BCH code is denoted as 'BCH(15,5)', the case of using the detection mode among the entanglement distillation protocols using measurement error filtering with n=m=3 is denoted as 'n=m=3(detecting)', the case of using the correction mode among the entanglement distillation protocols using measurement error filtering with n=m=3 is denoted as 'n=m=3(correcting)', and the case of not making any correction is denoted as 'no correction'.

[0723] In Figs. 63 to 65, the entanglement distillation protocol using measurement error filtering with n = m = 3 requires two ansilla bits when measuring one target qubit. Therefore, a total of 10 ansilla bits are required to measure five target qubits. The (15, 5) BCH code also requires 10 ansilla bits to measure five target qubits. In other words, the entanglement distillation protocol using measurement error filtering and the proposed technique using the (15, 5) BCH code were compared in an environment using the same number of ansilla bits. Referring to Figs. 63 to 65, the proposed technique using the (15, 5) BCH code has higher output fidelity than the entanglement distillation protocol using measurement error filtering with n = m = 3. p m For =0.05, the proposed technique exhibits a high success probability at all initial fidelities. Furthermore, compared to the n=m=3 (Detecting) technique, it exhibits lower output fidelity across all error rate ranges, but a very high success probability.

[0724] As mentioned above, the proposed technique, which corrects measurement errors based on error-correcting codes, allows for efficient measurements using a small number of ancilla bits. Therefore, the proposed technique enables efficient communication.

[0725] Below, examples of wireless device utilization to which various embodiments of the present disclosure are applied are described.

[0726] Figure 66 illustrates an example of a wireless device applicable to the present disclosure. The wireless device may be implemented in various forms depending on the use case / service (see Figure 1).

[0727] Referring to FIG. 66, the wireless device (200) corresponds to the wireless device (200) of FIG. 2 and may be composed of various elements, components, units / units, and / or modules. For example, the wireless device (200) may include a communication unit (210), a control unit (220), a memory unit (230), and additional elements (240). The communication unit may include a communication circuit (212) and a transceiver(s) (214). For example, the communication circuit (212) may include one or more processors (202) and / or one or more memories (204) of FIG. 2. For example, the transceiver(s) (214) may include one or more transceivers (206) and / or one or more antennas (208) of FIG. 2. The control unit (220) is electrically connected to the communication unit (210), the memory unit (230), and the additional elements (240) and controls the overall operations of the wireless device. For example, the control unit (220) can control the electrical / mechanical operations of the wireless device based on the program / code / command / information stored in the memory unit (230). In addition, the control unit (220) can transmit information stored in the memory unit (230) to an external device (e.g., another communication device) via a wireless / wired interface through the communication unit (210), or store information received from an external device (e.g., another communication device) via a wireless / wired interface in the memory unit (230).

[0728] The additional element (240) may be configured in various ways depending on the type of the wireless device. For example, the additional element (240) may include at least one of a power unit / battery, an input / output unit (I / O unit), a driving unit, and a computing unit. Although not limited thereto, the wireless device may be implemented in the form of a robot (Fig. 1, 100a), a vehicle (Fig. 1, 100b-1, 100b-2), an XR device (Fig. 1, 100c), a portable device (Fig. 1, 100d), a home appliance (Fig. 1, 100e), an IoT device (Fig. 1, 100f), a digital broadcasting terminal, a hologram device, a public safety device, an MTC device, a medical device, a fintech device (or a financial device), a security device, a climate / environmental device, an AI server / device (Fig. 1, 400), a base station (Fig. 1, 200), a network node, etc. Wireless devices may be mobile or stationary depending on the use / service.

[0729] In FIG. 66, various elements, components, units / parts, and / or modules within the wireless device (200) may be entirely interconnected via a wired interface, or at least some may be wirelessly connected via a communication unit (210). For example, within the wireless device (200), the control unit (220) and the communication unit (210) may be wired, and the control unit (220) and a first unit (e.g., 230, 240) may be wirelessly connected via the communication unit (210). In addition, each element, component, unit / part, and / or module within the wireless device (200) may further include one or more elements. For example, the control unit (220) may be composed of a set of one or more processors. For example, the control unit (220) may be composed of a set of a communication control processor, an application processor, an electronic control unit (ECU), a graphics processing processor, a memory control processor, etc. As another example, the memory unit (130) may be composed of RAM (Random Access Memory), DRAM (Dynamic RAM), ROM (Read Only Memory), flash memory, volatile memory, non-volatile memory, and / or a combination thereof.

[0730] Below, an implementation example of Fig. 66 is described in more detail with reference to the drawings.

[0731] Figure 67 illustrates examples of portable devices applicable to the present disclosure. Portable devices may include smartphones, smart pads, wearable devices (e.g., smartwatches, smartglasses), and portable computers (e.g., laptops, etc.). Portable devices may be referred to as Mobile Stations (MS), User Terminals (UT), Mobile Subscriber Stations (MSS), Subscriber Stations (SS), Advanced Mobile Stations (AMS), or Wireless Terminals (WT).

[0732] Referring to FIG. 67, the portable device (200) may include an antenna unit (208), a communication unit (210), a control unit (220), a memory unit (230), a power supply unit (240a), an interface unit (240b), and an input / output unit (240c). The antenna unit (208) may be configured as a part of the communication unit (210). Blocks 210 to 230 / 240a to 240c of FIG. 67 correspond to blocks 210 to 230 / 240 of FIG. 66, respectively.

[0733] The communication unit (210) can transmit and receive signals (e.g., data, control signals, etc.) with other wireless devices and base stations. The control unit (220) can control components of the mobile device (200) to perform various operations. The control unit (220) can include an AP (Application Processor). The memory unit (230) can store data / parameters / programs / codes / commands required for operating the mobile device (200). In addition, the memory unit (230) can store input / output data / information, etc. The power supply unit (240a) supplies power to the mobile device (200) and can include a wired / wireless charging circuit, a battery, etc. The interface unit (240b) can support connection between the mobile device (200) and other external devices. The interface unit (240b) can include various ports (e.g., audio input / output ports, video input / output ports) for connection with external devices. The input / output unit (240c) can input or output video information / signals, audio information / signals, data, and / or information input from a user. The input / output unit (240c) may include a camera, a microphone, a user input unit, a display unit (240d), a speaker, and / or a haptic module.

[0734] For example, in the case of data communication, the input / output unit (240c) obtains information / signals (e.g., touch, text, voice, image, video) input by the user, and the obtained information / signals can be stored in the memory unit (230). The communication unit (210) converts the information / signals stored in the memory into wireless signals, and can directly transmit the converted wireless signals to other wireless devices or to a base station. In addition, the communication unit (210) can receive wireless signals from other wireless devices or base stations, and then restore the received wireless signals to the original information / signals. The restored information / signals can be stored in the memory unit (230) and then output in various forms (e.g., text, voice, image, video, haptic) through the input / output unit (240c).

[0735] Figure 68 illustrates examples of vehicles or autonomous vehicles applicable to the present disclosure. The vehicles or autonomous vehicles may be implemented as mobile robots, cars, trains, manned / unmanned aerial vehicles (AVs), ships, etc.

[0736] Referring to FIG. 68, a vehicle or autonomous vehicle (200-1) may include an antenna unit (208-1), a communication unit (210-1), a control unit (220-1), a driving unit (240a-1), a power supply unit (240b-1), a sensor unit (240c-1), and an autonomous driving unit (240d-1). The antenna unit (208-1) may be configured as a part of the communication unit (210-1). Blocks 210-1 / 230-1 / 240a-1 to 240d-1 of FIG. 68 correspond to blocks 210 / 230 / 240 of FIG. 66, respectively.

[0737] The communication unit (210-1) can transmit and receive signals (e.g., data, control signals, etc.) with external devices such as other vehicles, base stations (e.g., base stations, roadside base stations (ROS), etc.), and servers. The control unit (220-1) can control elements of the vehicle or autonomous vehicle (200-1) to perform various operations. The control unit (220-1) may include an ECU (Electronic Control Unit). The drive unit (240a-1) can drive the vehicle or autonomous vehicle (200-1) on the ground. The drive unit (240a-1) may include an engine, a motor, a power train, wheels, brakes, a steering device, etc. The power supply unit (240b-1) supplies power to the vehicle or autonomous vehicle (200-1) and may include a wired / wireless charging circuit, a battery, etc. The sensor unit (240c-1) can obtain vehicle status, surrounding environment information, user information, etc. The sensor unit (240c-1) may include an IMU (inertial measurement unit) sensor, a collision sensor, a wheel sensor, a speed sensor, an incline sensor, a weight detection sensor, a heading sensor, a position module, a vehicle forward / backward sensor, a battery sensor, a fuel sensor, a tire sensor, a steering sensor, a temperature sensor, a humidity sensor, an ultrasonic sensor, an illuminance sensor, a pedal position sensor, etc. The autonomous driving unit (240d-1) may implement a technology for maintaining a driving lane, a technology for automatically controlling speed such as adaptive cruise control, a technology for automatically driving along a set path, a technology for automatically setting a path and driving when a destination is set, etc.

[0738] For example, the communication unit (210-1) can receive map data, traffic information data, etc. from an external server. The autonomous driving unit (240d-1) can generate an autonomous driving route and driving plan based on the acquired data. The control unit (220-1) can control the drive unit (240a-1) so that the vehicle or autonomous vehicle (200-1) moves along the autonomous driving route according to the driving plan (e.g., speed / direction control). During autonomous driving, the communication unit (210-1) can irregularly / periodically acquire the latest traffic information data from an external server and can acquire surrounding traffic information data from surrounding vehicles. In addition, during autonomous driving, the sensor unit (240c-1) can acquire vehicle status and surrounding environment information. The autonomous driving unit (240d-1) can update the autonomous driving route and driving plan based on newly acquired data / information. The communication unit (210-1) can transmit information regarding the vehicle location, autonomous driving route, driving plan, etc. to an external server. The external server can predict traffic information data in advance using AI technology, etc. based on information collected from the vehicle or autonomous vehicles, and provide the predicted traffic information data to the vehicle or autonomous vehicles. If the device (220-2) is an autonomous vehicle, it can perform the same procedure as the vehicle or autonomous vehicle (200-1). In addition, if the device (220-2) is a base station or a roadside base station, the device (220-2) can transmit data, control signals, etc. to the vehicle or autonomous vehicle (200-1) through the communication unit (210-2).

[0739] Figure 69 illustrates an example of a vehicle applicable to the present disclosure. The vehicle may also be implemented as a means of transportation, a train, an aircraft, a ship, etc. Referring to Figure 69, the vehicle (200) may include a communication unit (210), a control unit (220), a memory unit (230), an input / output unit (240a), and a position measurement unit (240b). Here, blocks 210 to 230 / 240a to 240b correspond to blocks 210 to 230 / 240 of Figure 66, respectively.

[0740] The communication unit (210) can transmit and receive signals (e.g., data, control signals, etc.) with other vehicles or external devices such as base stations. The control unit (220) can control components of the vehicle (200) to perform various operations. The memory unit (230) can store data / parameters / programs / codes / commands that support various functions of the vehicle (100). The input / output unit (240a) can output AR / VR objects based on information in the memory unit (230). The input / output unit (240a) can include a HUD. The position measurement unit (240b) can obtain position information of the vehicle (200). The position information can include absolute position information of the vehicle (200), position information within a driving line, acceleration information, position information with respect to surrounding vehicles, etc. The position measurement unit (240b) can include GPS and various sensors.

[0741] For example, the communication unit (210) of the vehicle (200) can receive map information, traffic information, etc. from an external server and store them in the memory unit (230). The location measurement unit (240b) can obtain vehicle location information through GPS and various sensors and store the information in the memory unit (230). The control unit (220) can create a virtual object based on the map information, traffic information, and vehicle location information, and the input / output unit (240a) can display the created virtual object on the vehicle window (240a-1, 240a-2). In addition, the control unit (220) can determine whether the vehicle (200) is being driven normally within the driving line based on the vehicle location information. If the vehicle (200) abnormally deviates from the driving line, the control unit (220) can display a warning on the vehicle window through the input / output unit (240a). Additionally, the control unit (220) can broadcast a warning message regarding driving abnormalities to surrounding vehicles through the communication unit (210). Depending on the situation, the control unit (220) can transmit vehicle location information and information regarding driving / vehicle abnormalities to relevant authorities through the communication unit (210).

[0742] Figure 70 illustrates examples of XR devices applicable to the present disclosure. The XR devices may be implemented as HMDs, head-up displays (HUDs) installed in vehicles, televisions, smartphones, computers, wearable devices, home appliances, digital signage, vehicles, robots, and the like.

[0743] Referring to FIG. 70, the XR device (200a) may include a communication unit (210), a control unit (220), a memory unit (230), an input / output unit (240a), a sensor unit (240b), and a power supply unit (240c). Here, blocks 210 to 230 / 240a to 240c of FIG. 70 correspond to blocks 210 to 230 / 240 of FIG. 66, respectively.

[0744] The communication unit (210) can transmit and receive signals (e.g., media data, control signals, etc.) with external devices such as other wireless devices, portable devices, or media servers. The media data can include videos, images, sounds, etc. The control unit (220) can control components of the XR device (200a) to perform various operations. For example, the control unit (220) can be configured to control and / or perform procedures such as video / image acquisition, (video / image) encoding, metadata generation and processing, etc. The memory unit (230) can store data / parameters / programs / codes / commands required for driving the XR device (200a) / generating XR objects. The input / output unit (240a) can obtain control information, data, etc. from the outside, and output the generated XR object. The input / output unit (240a) can include a camera, a microphone, a user input unit, a display unit, a speaker, and / or a haptic module. The sensor unit (240b) can obtain the XR device status, surrounding environment information, user information, etc. The sensor unit (240b) may include a proximity sensor, an illuminance sensor, an acceleration sensor, a magnetic sensor, a gyro sensor, an inertial sensor, an RGB sensor, an IR sensor, a fingerprint recognition sensor, an ultrasonic sensor, a light sensor, a microphone, and / or a radar. The power supply unit (240c) supplies power to the XR device (200a) and may include a wired / wireless charging circuit, a battery, etc.

[0745] For example, the memory unit (230) of the XR device (200a) may include information (e.g., data, etc.) required for creating an XR object (e.g., AR / VR / MR object). The input / output unit (240a) may obtain a command to operate the XR device (200a) from the user, and the control unit (220) may operate the XR device (200a) according to the user's operating command. For example, when the user attempts to watch a movie, news, etc. through the XR device (200a), the control unit (220) may transmit content request information to another device (e.g., a mobile device (200b)) or a media server through the communication unit (230). The communication unit (230) may download / stream content such as movies and news from another device (e.g., a mobile device (200b)) or a media server to the memory unit (230). The control unit (220) controls and / or performs procedures such as video / image acquisition, (video / image) encoding, and metadata generation / processing for content, and can generate / output an XR object based on information about surrounding space or real objects acquired through the input / output unit (240a) / sensor unit (240b).

[0746] In addition, the XR device (200a) is wirelessly connected to the mobile device (200b) through the communication unit (210), and the operation of the XR device (200a) can be controlled by the mobile device (200b). For example, the mobile device (200b) can act as a controller for the XR device (200a). To this end, the XR device (200a) can obtain 3D location information of the mobile device (200b), and then generate and output an XR object corresponding to the mobile device (200b).

[0747] Figure 71 illustrates examples of robots applicable to the present disclosure. Robots can be classified into industrial, medical, household, and military types, depending on their intended use or field.

[0748] Referring to FIG. 71, the robot (200) may include a communication unit (210), a control unit (220), a memory unit (230), an input / output unit (240a), a sensor unit (240b), and a driving unit (240c). Here, blocks 210 to 230 / 240a to 240c of FIG. 71 correspond to blocks 210 to 230 / 240 of FIG. 66, respectively.

[0749] The communication unit (210) can transmit and receive signals (e.g., driving information, control signals, etc.) with external devices such as other wireless devices, other robots, or control servers. The control unit (220) can control components of the robot (200) to perform various operations. The memory unit (230) can store data / parameters / programs / codes / commands that support various functions of the robot (200). The input / output unit (240a) can obtain information from the outside of the robot (200) and output information to the outside of the robot (200). The input / output unit (240a) can include a camera, a microphone, a user input unit, a display unit, a speaker, and / or a haptic module. The sensor unit (240b) can obtain internal information of the robot (200), surrounding environment information, user information, etc. The sensor unit (240b) may include a proximity sensor, an illuminance sensor, an acceleration sensor, a magnetic sensor, a gyro sensor, an inertial sensor, an IR sensor, a fingerprint recognition sensor, an ultrasonic sensor, a light sensor, a microphone, a radar, etc. The driving unit (240c) may perform various physical operations, such as moving the robot joints. In addition, the driving unit (240c) may enable the robot (200) to drive on the ground or fly in the air. The driving unit (240c) may include an actuator, a motor, wheels, brakes, propellers, etc.

[0750] Figure 72 illustrates an example of an AI device applicable to the present disclosure.

[0751] AI devices can be implemented as fixed or mobile devices, such as TVs, projectors, smartphones, PCs, laptops, digital broadcasting terminals, tablet PCs, wearable devices, set-top boxes (STBs), radios, washing machines, refrigerators, digital signage, robots, and vehicles.

[0752] Referring to FIG. 72, the AI ​​device (200) may include a communication unit (210), a control unit (220), a memory unit (230), an input / output unit (240a / 240b), a learning processor unit (240c), and a sensor unit (240d). Blocks 210 to 230 / 240a to 240d of FIG. 72 correspond to blocks 210 to 230 / 140 of FIG. 66, respectively.

[0753] The communication unit (210) can transmit and receive wired and wireless signals (e.g., sensor information, user input, learning models, control signals, etc.) with external devices such as other AI devices (e.g., 100a to 100f, 120 of FIG. 1) or AI servers (e.g., 100g of FIG. 1) using wired and wireless communication technology. To this end, the communication unit (210) can transmit information within the memory unit (230) to the external device or transfer a signal received from the external device to the memory unit (230).

[0754] The control unit (220) may determine at least one executable operation of the AI ​​device (200) based on information determined or generated using a data analysis algorithm or a machine learning algorithm. In addition, the control unit (220) may control components of the AI ​​device (200) to perform the determined operation. For example, the control unit (220) may request, search, receive, or utilize data from the learning processor unit (240c) or the memory unit (230), and may control components of the AI ​​device (200) to perform at least one executable operation, a predicted operation, or an operation determined to be desirable. In addition, the control unit (220) may collect history information including the operation contents of the AI ​​device (200) or user feedback on the operation, and store the collected history information in the memory unit (230) or the learning processor unit (240c), or transmit the collected history information to an external device such as an AI server (FIG. 1, 100g). The collected history information may be used to update a learning model.

[0755] The memory unit (230) can store data that supports various functions of the AI ​​device (200). For example, the memory unit (230) can store data obtained from the input unit (240a), data obtained from the communication unit (210), output data of the learning processor unit (240c), and data obtained from the sensing unit (140). In addition, the memory unit (230) can store control information and / or software codes necessary for the operation / execution of the control unit (220).

[0756] The input unit (240a) can obtain various types of data from the outside of the AI ​​device (200). For example, the input unit (220) can obtain learning data for model learning, input data to which the learning model will be applied, etc. The input unit (240a) may include a camera, a microphone, and / or a user input unit. The output unit (240b) may generate output related to vision, hearing, or touch. The output unit (240b) may include a display unit, a speaker, and / or a haptic module, etc. The sensing unit (140d) can obtain at least one of internal information of the AI ​​device (200), information about the surrounding environment of the AI ​​device (200), and user information using various sensors. The sensing unit (140d) may include a proximity sensor, an illuminance sensor, an acceleration sensor, a magnetic sensor, a gyro sensor, an inertial sensor, an RGB sensor, an IR sensor, a fingerprint recognition sensor, an ultrasonic sensor, a light sensor, a microphone, and / or a radar, etc.

[0757] The learning processor unit (240c) can train a model composed of an artificial neural network using learning data. The learning processor unit (240c) can perform AI processing together with the learning processor unit of the AI ​​server (Fig. 1, 100g). The learning processor unit (240c) can process information received from an external device via the communication unit (210) and / or information stored in the memory unit (230). In addition, the output value of the learning processor unit (240c) can be transmitted to an external device via the communication unit (210) and / or stored in the memory unit (230).

[0758] Figure 73 illustrates an example of a quantum communication device applicable to the present disclosure. The quantum communication device can be applied to various devices and can be operated in combination (or merged) with other non-quantum communication wired and / or wireless communication devices. Information in quantum communication can be a concept encompassing both bit information, the basic unit of classical information, and qubit information, the basic unit of quantum information.

[0759] The channel encoder (250) can encode the classical bits to be transmitted into coded bits. The channel encoder (250) can improve the reliability of the classical bits.

[0760] A quantum encoder (260) converts the encoded bits into a qubit basis (or computation basis). Here, the qubit basis is logical information about a quantum state and can be formed based on a physical quantum basis. For example, as a quantum basis at the transmitter and receiver, horizontal polarization and vertical polarization can be agreed to correspond to the qubit basis |0〉 and |1〉, respectively.

[0761] Classical information bits 0 or 1 can be converted into qubit basis |0〉 or |1〉 through a channel encoder (250) and a quantum encoder (260). The qubit basis generated at the transmitter can be transmitted to the receiver through a quantum channel.

[0762] The quantum decoder (270) at the receiving end can perform measurements based on a pre-arranged quantum basis and decode the qubit basis transmitted to the receiving end into coded bits. If multiple qubit basis determines the qubit state, a qubit coded deterministically or probabilistically can be obtained depending on the measured qubit basis.

[0763] The channel decoder (280) decodes the coded bits back into classical bits and can obtain the information bits sent by the transmitter.

[0764] The procedures related to the channel encoder (250) and channel decoder (280) indicated by dotted lines in FIG. 73 may be omitted. If the channel encoder (250) and channel decoder (280) are omitted, the qubit state can be transmitted from the quantum process of the transmitter to the receiver via a quantum channel. The received qubit state can be used by the quantum processor for various purposes. For example, to transmit the qubit state generated in the quantum processor, a quantum direct communication method in which the qubit state is converted into a photon and transmitted may be used, or a method in which quantum teleportation is performed based on an entanglement source shared by the transmitter and receiver in advance may be used. Here, quantum direct communication refers to a communication method in which classical message information to be transmitted is safely shared directly through a quantum channel, and quantum teleportation refers to a communication method in which quantum information itself is shared through a quantum entanglement channel.

[0765] The proposed methods described above can be implemented independently, but they can also be implemented as a combination (or merge) of some of the proposed methods. Rules can be defined so that the base station notifies the terminal of the applicability of the proposed methods (or information about the rules of the proposed methods) through a predefined signal (e.g., a physical layer signal or a higher layer signal).

[0766] The present disclosure may be embodied in other specific forms without departing from the technical ideas and essential features described herein. Therefore, the above detailed description should not be construed as limiting in all respects but rather as illustrative. The scope of the present disclosure should be determined by a reasonable interpretation of the appended claims, and all modifications within the equivalent scope of the present disclosure are intended to be included within the scope of the present disclosure. Furthermore, claims that are not explicitly cited in the claims may be combined to form an embodiment or incorporated into a new claim through a post-filing amendment.

[0767] The embodiments described herein may be applied to various wireless access systems. Examples of such wireless access systems include the 3rd Generation Partnership Project (3GPP) or 3GPP2 systems.

[0768] The embodiments described herein can be applied not only to the various wireless access systems described above, but also to all technical fields utilizing these various wireless access systems. Furthermore, the proposed method can be applied to mmWave and THz communication systems utilizing ultra-high frequency bands.

[0769] Additionally, the embodiments can be applied to various applications such as autonomous vehicles and drones.

Claims

In a method performed by a first device in a quantum communication system, A step of performing a connection establishment procedure with a second device; A step of receiving setting information from the second device; A step of generating a first signal and a second signal; a step of transmitting the second signal to the second device; and A step of performing an entanglement distillation procedure of the first signal and the second signal based on an error correction code using a plurality of measurement target qubits and at least one ancilla qubit, A method in which a first qubit included in the first signal is in a quantum entangled state with a second qubit included in the second signal. In the first paragraph, The above first qubit and the above second qubit are generated based on an EPR (Einstein-Podolsky-Rosen) state. In the first paragraph, The above entanglement distillation procedure is a method of performing a CNOT operation (controlled NOT operation) using a control qubit and a target qubit as inputs, and determining whether the control qubit is preserved based on the measurement result of the output qubit of the CNOT operation of the target qubit. In the first paragraph, A method in which the above error correction code is determined as one of a hamming code, an extended hamming code, and a Bose-Chaudhuri-Hocquenghem (BCH) code. In the first paragraph, The step of performing the entanglement distillation procedure of the first signal and the second signal based on the error correction code is as follows: A step of performing a CNOT operation (controlled NOT operation) using the first qubit included in the first signal and the third qubit included in the first signal as inputs; A step of encoding the output qubit of the CNOT operation corresponding to the third qubit and the at least one ancilla qubit using a first error correction code; a step of measuring the encoded qubits; and A method comprising a step of performing decoding based on the measurement results of the encoded qubits. In paragraph 5, A step of transmitting to the second device the number of qubits to be measured of the first error correction code used by the first device; a step of transmitting information indicating a failure of the decoding to the second device; and A method further comprising the step of discarding control qubits equal to the number of the measurement target qubits of the first error correction code. In paragraph 5, A step of receiving information from the second device indicating a failure in decoding performed by the second device; and Including a step of discarding control qubits equal to the number of measurement target qubits of the second error correction code used by the second device, A method in which the above setting information includes the number of qubits to be measured of the second error correction code. In paragraph 5, Further comprising a step of receiving a measurement result regarding a fourth qubit included in the second signal from the second device, The fourth qubit is entangled with the third qubit, If the measurement result regarding the third qubit and the measurement result regarding the fourth qubit are identical, the first qubit and the second qubit are preserved, A method in which the first qubit and the second qubit are discarded when the measurement results regarding the third qubit and the measurement results regarding the fourth qubit do not match. In paragraph 5, A method for determining that the measurement results of the encoded qubits are decoded using the first error correction code and that the decoding is successful if no error occurs in the decoding. In paragraph 5, A method for determining that the measurement results of the encoded qubits are decoded using the first error correction code, and that the decoding is successful if at least one error occurs by the decoding and correction is possible. In the first paragraph, The step of performing the entanglement distillation procedure of the first signal and the second signal based on the error correction code is as follows: A step of performing a first CNOT operation (controlled NOT operation) using the first qubit included in the first signal and the third qubit included in the first signal as inputs; and A step of performing the second CNOT operation using as input the output qubit of the first CNOT operation corresponding to the fifth qubit and the third qubit included in the first signal, The above entanglement distillation procedure is a double selection entanglement distillation procedure, A method wherein the plurality of measurement target qubits include output qubits of the second CNOT operation. In the first paragraph, A method wherein the first error correction code used by the first device is an error correction code of the same type as the second error correction code used by the second device. In Article 12, A method in which the number of qubits to be measured for the first error correction code is set differently from the number of qubits to be measured for the second error correction code. In the first paragraph, A method in which the first error correction code used by the first device is a different type of error correction code from the second error correction code used by the second device. In Article 14, The above first error correction code is set to an extended hamming code, The above second error correction code is set to a BCH (Bose-Chaudhuri-Hocquenghem) code. In a method performed by a second device in a quantum communication system, A step of performing a connection establishment procedure with the first device; A step of transmitting setting information to the first device; A step of receiving the second signal among the first signal and the second signal generated by the first device from the first device; and A step of performing an entanglement distillation procedure of the first signal and the second signal based on an error correction code using a plurality of measurement target qubits and at least one ancilla qubit, A method in which a first qubit included in the first signal is in a quantum entangled state with a second qubit included in the second signal. In a first device in a quantum communication system, Transmitter and receiver; and comprising a processor coupled to the above transceiver, The above processor, Perform the connection establishment procedure with the second device, Receive setting information from the second device, Generate a first signal and a second signal, Transmitting the second signal to the second device, A method for performing an entanglement distillation procedure of the first signal and the second signal based on an error correction code using a plurality of measurement target qubits and at least one ancilla qubit, A first device in which a first qubit included in the first signal is in a quantum entangled state with a second qubit included in the second signal. In the second device of the quantum communication system, Transmitter and receiver; and A processor connected to the above transmitter and receiver is included, The above processor, Perform the connection establishment procedure with the first device, Transmit setting information to the first device, Receive the second signal among the first signal and the second signal generated by the first device from the first device, Control to perform an entanglement distillation procedure of the first signal and the second signal based on an error correction code using a plurality of measurement target qubits and at least one ancilla qubit, A second device in which the first qubit included in the first signal is in a quantum entangled state with the second qubit included in the second signal. In communication devices, At least one processor; At least one computer memory connected to said at least one processor and storing instructions that direct operations when executed by said at least one processor, The above actions are, A step of performing a connection establishment procedure with a second device; A step of receiving setting information from the second device; A step of generating a first signal and a second signal; a step of transmitting the second signal to the second device; and A step of performing an entanglement distillation procedure of the first signal and the second signal based on an error correction code using a plurality of measurement target qubits and at least one ancilla qubit, A communication device in which a first qubit included in the first signal is in a quantum entangled state with a second qubit included in the second signal. In a non-transitory computer-readable medium storing at least one instruction, comprising at least one instruction executable by the processor, At least one of the above commands causes the first device to: Perform the connection establishment procedure with the second device, Receive setting information from the second device, Generate a first signal and a second signal, Transmitting the second signal to the second device, A method for performing an entanglement distillation procedure of the first signal and the second signal based on an error correction code using a plurality of measurement target qubits and at least one ancilla qubit, A computer-readable medium in which a first qubit included in the first signal is in a quantum entangled state with a second qubit included in the second signal.

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