Apparatus and method for determining position of reused qubit for entanglement distillation protocol in communication system

Abstract

The present disclosure is to perform an entanglement distillation protocol by using an entangled reused qubit in a communication system. This method may comprise the steps of: performing a random access procedure with a second device; transmitting configuration information to the second device; generating a first signal and a second signal; transmitting the second signal to the second device; determining at least one position where a reused qubit is to be used within a first entanglement distillation protocol, on the basis of a yield of the first entanglement distillation protocol; and obtaining a qubit having a fidelity greater than or equal to a first threshold by performing the first entanglement distillation protocol.

Description

Device and method for determining the location of a reusable qubit of an entanglement distillation protocol in a communication system

[0001] The present disclosure relates to a communication system, and more specifically to an apparatus and method for determining the location of a reusable qubit of an entanglement distillation protocol (EDP) in a communication system.

[0002] Wireless access systems are being widely deployed to provide various types of communication services, such as voice and data. Generally, a wireless access system is a multiple access system capable of supporting communication with multiple users by sharing available system resources (bandwidth, transmission power, etc.). Examples of multiple access systems include 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) systems.

[0003] In particular, as many communication devices require large communication capacities, enhanced mobile broadband (eMBB) communication technology is being proposed as an improvement over existing radio access technology (RAT). Furthermore, communication systems are being proposed that consider not only massive machine type communications (mmTC), which connects multiple devices and objects to provide various services anytime and anywhere, but also services and user equipment (UE) that are sensitive to reliability and latency. Various technical configurations are being proposed for this purpose.

[0004] The present disclosure relates to an apparatus and method for reusing output qubits of an entanglement distillation protocol (EDP) in a wireless communication system.

[0005] The present disclosure relates to an apparatus and method for determining the location of a reusable qubit of an entanglement distillation protocol by a transmitting node or a receiving node in a wireless communication system.

[0006] The present disclosure relates to an apparatus and method for replacing an initial qubit with a reusable qubit in a wireless communication system.

[0007] The present disclosure relates to an apparatus and method for determining the location where a reusable qubit is to be used based on yield in a wireless communication system.

[0008] The present disclosure relates to an apparatus and method for determining the locations of a plurality of reusable qubits based on a vector indicating the location where a single reusable qubit is used in a wireless communication system.

[0009] The present disclosure relates to an apparatus and method for determining the location of a reusable qubit having the highest yield in a wireless communication system.

[0010] The present disclosure relates to an apparatus and method for utilizing a reusable qubit having a lower fidelity than the fidelity of a qubit received through a quantum channel in a wireless communication system.

[0011] The present disclosure relates to an apparatus and method for transmitting or receiving configuration information for using a reusable qubit in a wireless communication system.

[0012] The present disclosure relates to an apparatus and method for determining yield based on the cost of qubits and the success rate of a sub-entanglement distillation protocol in a wireless communication system.

[0013] The technical objectives to be achieved in this disclosure are not limited to those mentioned above, and other unmentioned technical problems may be considered by those skilled in the art to which the technical configuration of this disclosure applies, based on the embodiments of this disclosure described below.

[0014] As an example of the present disclosure, the method comprises: performing a random access procedure with a second device; transmitting setting information to the second device; generating a first signal and a second signal; transmitting the second signal to the second device; determining at least one location in which a reusable qubit is used within the first entanglement distillation protocol based on the yield of the first entanglement distillation protocol; and obtaining a qubit having a fidelity greater than or equal to a first threshold by performing the first entanglement distillation protocol, wherein the first qubit included in the first signal may be in a quantum entangled state with a second qubit included in the second signal.

[0015] As an example of the present disclosure, the method comprises: performing a random access procedure with a first device; receiving setting information from the first device; receiving a second signal from the first device; determining at least one location in which a reusable qubit is used within the first entanglement distillation protocol based on the yield of the first entanglement distillation protocol; and obtaining a qubit having a fidelity greater than or equal to a first threshold by performing the first entanglement distillation protocol, wherein the 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 first device comprises a transceiver and a processor coupled to the transceiver, wherein the processor performs a random access procedure with a second device, transmits setting information to the second device, generates a first signal and a second signal, transmits the second signal to the second device, determines at least one location in which a reusable qubit is used within the first entanglement distillation protocol based on the yield of the first entanglement distillation protocol, and is configured to obtain a qubit having a fidelity greater than or equal to a first threshold by performing the first entanglement distillation protocol, wherein the first qubit included in the first signal may be in a quantum entangled state with a second qubit included in the second signal.

[0017] As an example of the present disclosure, a second device comprises a transceiver and a processor coupled to the transceiver, wherein the processor performs a random access procedure with a first device, receives setting information from the first device, receives the second signal from the first device, determines at least one location in which a reusable qubit is used within the first entanglement distillation protocol based on the yield of the first entanglement distillation protocol, and is configured to obtain a qubit having a fidelity greater than or equal to a first threshold by performing the first entanglement distillation protocol, wherein the first qubit included in the first signal may be in a quantum entangled state with the second qubit included in the second signal.

[0018] As an example of the present disclosure, a terminal comprises at least one processor, and at least one computer memory connected to the at least one processor and storing instructions that direct operations as executed by the at least one processor, wherein the operations include: performing a random access procedure with a second device; transmitting configuration information to the second device; generating a first signal and a second signal; transmitting the second signal to the second device; determining at least one location in which a reusable qubit is used within the first entanglement distillation protocol based on the yield of the first entanglement distillation protocol; and obtaining a qubit having a fidelity greater than or equal to a first threshold by performing the first entanglement distillation protocol, wherein the first qubit included in the first signal may be in a quantum entangled state with a second qubit included in the second signal.

[0019] As an example of the present disclosure, a non-transitory computer-readable medium storing at least one instruction comprises said at least one instruction executable by a processor, said at least one instruction configured such that the device performs a random access procedure with a second device, transmits setting information to the second device, generates a first signal and a second signal, transmits the second signal to the second device, determines at least one location in which a reusable qubit is used within the first entanglement distillation protocol based on the yield of the first entanglement distillation protocol, and obtains a qubit having a fidelity greater than or equal to a first threshold by performing the first entanglement distillation protocol, wherein the first qubit included in the first signal may be in a quantum entangled state with a second qubit included in the second signal.

[0020] The embodiments of the present disclosure described above are merely 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 those skilled in the art based on the detailed description of the present disclosure set forth below.

[0021] The following effects may be achieved by embodiments based on the present disclosure.

[0022] According to the present disclosure, the location of a reusable qubit can be efficiently searched in an entanglement distillation protocol that utilizes a reusable qubit in a communication system.

[0023] The effects obtainable from the embodiments of the present disclosure are not limited to those mentioned above, and other unmentioned effects can be clearly derived and understood by a person skilled in the art to which the technical configuration of the present disclosure applies from the description of the embodiments of the present disclosure below. That is, unintended effects resulting from implementing the configuration described in the present disclosure can also be derived by a person skilled in the art from the embodiments of the present disclosure.

[0024] The drawings attached below are intended to aid in understanding the present disclosure and may provide embodiments of the present disclosure together with the detailed description. However, the technical features of the present disclosure are not limited to specific drawings, and features disclosed in each drawing may be combined with one another to form new embodiments. Reference numerals in each drawing may denote structural elements.

[0025] FIG. 1 illustrates an example of a communication system applicable to the present disclosure.

[0026] FIG. 2 illustrates an example of a wireless device applicable to the present disclosure.

[0027] FIG. 3 illustrates a method for processing a transmission signal applicable to the present disclosure.

[0028] FIG. 4 illustrates a communication procedure between a terminal and a base station applicable to the present disclosure.

[0029] FIG. 5 illustrates an example of a communication structure that can be provided in a 6G (6th generation) system applicable to the present disclosure.

[0030] FIG. 6 illustrates an electromagnetic spectrum applicable to the present disclosure.

[0031] FIG. 7 illustrates a transmitter structure applicable to the present disclosure.

[0032] FIG. 8 illustrates an example of a functional framework for the application of artificial intelligence technology applicable to the present disclosure.

[0033] FIG. 9 illustrates an example of a procedure for utilizing an artificial intelligence model applicable to the present disclosure.

[0034] FIG. 10 illustrates a communication procedure based on artificial intelligence (AI) technology applicable to the present disclosure.

[0035] FIG. 11 illustrates an example of a quantum channel model based on environmental decoherence in a system applicable to the present disclosure.

[0036] FIG. 12 illustrates an example in which Alice and Bob perform a QPA protocol according to one embodiment of the present disclosure.

[0037] FIG. 13 illustrates an example of the structure of a dual-selection protocol according to one embodiment of the present disclosure.

[0038] FIG. 14 illustrates an example of fidelity according to a measurement result in a single selection (QPA) protocol when Pg=Pm=0 according to one embodiment of the present disclosure.

[0039] FIG. 15 illustrates an example of fidelity according to a measurement result in a dual selection protocol when Pg=Pm=0 according to one embodiment of the present disclosure.

[0040] FIG. 16 illustrates an example of fidelity according to a measurement result in a single selection protocol when Pg=Pm=0.2 according to one embodiment of the present disclosure.

[0041] FIG. 17 illustrates an example of fidelity according to measurement results in a dual selection protocol when Pg=Pm=0.2 according to one embodiment of the present disclosure.

[0042] FIG. 18 illustrates an example of signaling of a dual-select EDP utilizing reuse according to one embodiment of the present disclosure.

[0043] FIG. 19 illustrates an example of a QECCs-based hashing protocol according to one embodiment of the present disclosure.

[0044] FIG. 20 illustrates an example of the structure of a single round of a bidirectional EDP technique according to one embodiment of the present disclosure.

[0045] FIG. 21 illustrates an example of a process in which a transmitter and a receiver measure qubits according to an embodiment of the present disclosure.

[0046] FIG. 22 is a drawing illustrating an example of the structure of a unidirectional EDP technique in a system applicable to the present disclosure.

[0047] FIG. 23 illustrates an example of the basic structure of an adaptive mode EDP technique according to one embodiment of the present disclosure.

[0048] FIG. 24 illustrates an example of a block diagram of a QECCs-based bidirectional EDP technique according to one embodiment of the present disclosure.

[0049] FIG. 25 illustrates an example of the overall procedure of an adaptive mode EDP technique according to one embodiment of the present disclosure.

[0050] FIG. 26 illustrates an example of an adaptive mode-based EDP technique procedure considering minimum fidelity according to one embodiment of the present disclosure.

[0051] FIG. 27 illustrates an example of the entire process of a minimum fidelity-based parameter estimation and an adaptive mode-based EDP technique according to one embodiment of the present disclosure.

[0052] FIG. 28 illustrates an example of the entire process of a Two-way QECCs EDP protocol that recycles entangled qubits according to one embodiment of the present disclosure.

[0053] FIG. 29 illustrates an example of a procedure for additional resource reduction in a bidirectional QECCs EDP according to one embodiment of the present disclosure.

[0054] FIG. 30 illustrates an example of a process in which a transmitter and a receiver measure qubits in an EDP utilizing computational adaptation according to an embodiment of the present disclosure.

[0055] FIG. 31 illustrates an example of a process in which a transmitter and a receiver measure qubits in an EDP utilizing an operational adaptation that performs twirling according to one embodiment of the present disclosure.

[0056] FIG. 32 illustrates an example of a 2-1 EDP protocol utilizing a computational adaptation technique according to one embodiment of the present disclosure.

[0057] FIG. 33a illustrates an example of a structure of qubits for performing double-select EDP using one recycled qubit in the first round according to one embodiment of the present disclosure.

[0058] FIG. 33b illustrates an example of a structure of qubits for performing double-select EDP using one recycled qubit in the second round according to one embodiment of the present disclosure.

[0059] FIG. 34 illustrates an example of a structure for performing a dual-select EDP with two rounds according to one embodiment of the present disclosure.

[0060] FIG. 35 illustrates an example of an index value of a qubit position according to one embodiment of the present disclosure.

[0061] FIG. 36 illustrates an example of a procedure for searching for the location of a reusable qubit according to one embodiment of the present disclosure.

[0062] FIG. 37 illustrates an example of signaling for searching the location of a reusable qubit according to one embodiment of the present disclosure.

[0063] FIG. 38 illustrates another example of signaling for searching the location of a reusable qubit according to one embodiment of the present disclosure.

[0064] FIG. 39 illustrates an example of a procedure in which a transmitting node performs an entanglement distillation protocol based on reusable qubits according to one embodiment of the present disclosure.

[0065] FIG. 40 illustrates an example of a procedure in which a receiving node performs an entanglement distillation protocol based on reusable qubits according to one embodiment of the present disclosure.

[0066] FIG. 41 illustrates an example of a wireless device applicable to the present disclosure.

[0067] FIG. 42 illustrates an example of a portable device applicable to the present disclosure.

[0068] FIG. 43 illustrates an example of a vehicle or autonomous vehicle applicable to the present disclosure.

[0069] FIG. 44 illustrates an example of a vehicle applicable to the present disclosure.

[0070] FIG. 45 illustrates an example of an extended reality (XR) device applicable to the present disclosure.

[0071] FIG. 46 illustrates an example of a robot applicable to the present disclosure.

[0072] FIG. 47 illustrates an example of an AI device applicable to the present disclosure.

[0073] The following embodiments are combinations of the components and features of the present disclosure in a predetermined form. Each component or feature may be considered optional unless otherwise explicitly stated. Each component or feature may be implemented in a form not combined with other components or features. Additionally, 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 any embodiment may be included in other embodiments, or may be replaced with corresponding components or features of other embodiments.

[0074] In the description of the drawings, procedures or steps that could obscure the gist of the present disclosure have not been described, nor have procedures or steps that are understandable to those skilled in the art been described.

[0075] Throughout the specification, when a part is described as "comprising" or "including" a component, this means that, unless specifically stated otherwise, it does not exclude other components but may include additional components. Furthermore, terms such as "...part," "...unit," and "module" as used in the specification refer to a unit that performs at least one function or operation, and this may be implemented in hardware, software, or a combination of hardware and software. Additionally, "one (a or an)," "one," "the," and similar related terms may be used in the context describing the present disclosure (particularly in the context of the following claims) in both singular and plural forms, unless otherwise indicated in the specification or clearly contradicted by the context.

[0076] In this specification, the embodiments of the present disclosure are described with a focus on the data transmission and reception relationship between a base station and a mobile station. Here, the base station refers to a terminal node of a network that communicates directly with a mobile station. Specific operations described in this document as being performed by a base station may, in some cases, be performed by an upper node of the base station.

[0077] 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, '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.

[0078] Additionally, in 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).

[0079] Furthermore, the transmitting end refers to a fixed and / or mobile node that provides data or voice services, and the receiving end refers to a fixed and / or mobile node that receives data or voice services. Therefore, in the case of the uplink, a mobile station can be the transmitting end and a base station can be the receiving end. Similarly, in the case of the downlink, a mobile station can be the receiving end and a base station can be the transmitting end.

[0080] Embodiments of the present disclosure may be supported by standard documents disclosed in at least one of the wireless access systems, such as IEEE 802.xx systems, 3GPP (3rd Generation Partnership Project) systems, 3GPP LTE (Long Term Evolution) systems, 3GPP 5G (5th generation) NR (New Radio) systems and 3GPP2 systems, 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.

[0081] In addition, the embodiments of the present disclosure may be applied to other wireless access systems and are not limited to the systems described above. For example, they may be applicable to systems applied after the 3GPP 5G NR system and are not limited to specific systems.

[0082] That is, obvious steps or parts not described in the embodiments of the present disclosure may be described by referring to the aforementioned documents. Additionally, all terms disclosed in this document may be explained by the aforementioned standard documents.

[0083] Hereinafter, preferred embodiments according to the present disclosure will be described in detail with reference to the accompanying drawings. The detailed description disclosed below, together with the accompanying drawings, is intended to describe exemplary embodiments of the present disclosure and is not intended to represent the only embodiment in which the technical configuration of the present disclosure can be implemented.

[0084] Additionally, specific terms used in the embodiments of the present disclosure are provided to aid in understanding the present disclosure, and the use of such specific terms may be modified in other forms without departing from the technical spirit of the present disclosure.

[0085] 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).

[0086] For the sake of clarity, the following description is based on 3GPP communication systems (e.g., LTE, NR, etc.), but the technical scope of this disclosure is not limited thereto. LTE may refer to technology from 3GPP TS 36.xxx Release 8 onwards. Specifically, LTE technology from 3GPP TS 36.xxx Release 10 onwards is referred to as LTE-A, and LTE technology from 3GPP TS 36.xxx Release 13 onwards may be referred to as LTE-A pro. 3GPP NR may refer to technology from TS 38.xxx Release 15 onwards. 3GPP 6G may refer to technology from TS Release 17 and / or Release 18 onwards. "xxx" indicates a specific standard document number. LTE / NR / 6G may be collectively referred to as 3GPP systems.

[0087] Regarding the background technology, 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.

[0088] Communication systems applicable to the present disclosure

[0089] Although not limited thereto, the various descriptions, functions, procedures, proposals, methods, and / or flowcharts of the disclosure disclosed in this document may be applied to various fields requiring wireless communication / connection (e.g., 5G) between devices.

[0090] Examples are provided in more detail below with reference to the drawings. In the following drawings and descriptions, the same reference numerals may represent the same or corresponding hardware blocks, software blocks, or function blocks unless otherwise described.

[0091] FIG. 1 illustrates an example of a communication system to which the present disclosure applies.

[0092] Referring to FIG. 1, the communication system (100) to which the present disclosure applies includes a wireless device, a base station, and a network. Here, the wireless device refers to a device that performs communication using 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 Thing) device (100f), and an AI (artificial intelligence) device / server (100g). For example, the vehicle may include a vehicle equipped with wireless communication capabilities, an autonomous vehicle, a vehicle capable of performing inter-vehicle communication, etc. Here, the vehicle (100b-1, 100b-2) may include an unmanned aerial vehicle (UAV) (e.g., a drone). The XR device (100c) includes an augmented reality (AR) / virtual reality (VR) / mixed reality (MR) device and may be implemented in the form of a head-mounted device (HMD), a head-up display (HUD) equipped in a vehicle, a television, a smartphone, a computer, a wearable device, a home appliance, digital signage, a vehicle, a robot, etc. The portable device (100d) may include a smartphone, a smartpad, a wearable device (e.g., a smartwatch, smart glasses), a computer (e.g., a laptop, etc.). The home appliance (100e) may include a TV, a refrigerator, a washing machine, etc. The IoT device (100f) may include a sensor, a smart meter, etc.For example, the base station (120) and 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.

[0093] Wireless devices (100a to 100f) can be connected to a network (130) through a base station (120). AI technology may be applied to the wireless devices (100a to 100f), and the wireless devices (100a to 100f) can be connected to an AI server (100g) through the network (130). The network (130) can be configured using a 3G network, a 4G (e.g., LTE) network, a 5G (e.g., NR) network, or a 6G network. The wireless devices (100a to 100f) may communicate with each other through the base station (120) / network (130), but may 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). Also, an IoT device (100f) (e.g., a sensor) can communicate directly with another IoT device (e.g., a sensor) or other wireless devices (100a to 100f).

[0094] Wireless communication / connection (150a, 150b, 150c) can be established between wireless devices (100a to 100f) / base station (120) and between base station (120) / base station (120). Here, wireless communication / connection can be established through various wireless access technologies such as uplink / downlink communication (150a), sidelink communication (150b) (or D2D communication), and communication between base stations (150c) (e.g., relay, IAB (integrated access backhaul)). Through wireless communication / connection (150a, 150b, 150c), wireless devices and base stations / wireless devices, and base stations and base stations can transmit / receive wireless signals to / from each other. For example, wireless communication / connection (150a, 150b, 150c) can transmit / receive signals through various physical channels. To this end, based on the various proposals of the present disclosure, at least some of the following may be performed: a process for setting various configuration information for transmitting / receiving wireless signals, a process for various signal processing (e.g., channel encoding / decoding, modulation / demodulation, resource mapping / demapping, etc.), a resource allocation process, etc.

[0095] Devices applicable to the present disclosure

[0096] FIG. 2 illustrates an example of a wireless device that can be applied to the present disclosure.

[0097] Referring to FIG. 2, the wireless device (200) can transmit and receive wireless signals through 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).

[0098] 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 sequences of operation disclosed in this document. For example, the processor (202) may process information within the memory (204) to generate a first information / signal and then transmit a wireless signal containing the first information / signal through the transceiver (206). Additionally, the processor (202) may receive a wireless signal containing a second information / signal through the transceiver (206) and then store information obtained from the 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, memory (204) may store software code containing 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 sequences of operations disclosed in this document. Here, the processor (202) and memory (204) may be part of a communication modem / circuit / chip designed to implement wireless communication technology. A transceiver (206) may be connected to the processor (202) and may transmit and / or receive wireless signals through at least one antenna (208). The transceiver (206) may include a transmitter and / or receiver. The transceiver (206) may be interchangeable with a radio frequency (RF) unit. In this disclosure, a wireless device may mean a communication modem / circuit / chip.

[0099] Hereinafter, 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., functional layers such as PHY (physical), MAC (media access control), RLC (radio link control), PDCP (packet data convergence protocol), RRC (radio resource control), and SDAP (service data adaptation protocol). At least one processor (202) may generate at least one PDU (Protocol Data Unit) and / or at least one SDU (service data unit) according to the descriptions, functions, procedures, proposals, methods and / or operation sequences disclosed in this document. At least one processor (202) may generate messages, control information, data, or information according to the descriptions, functions, procedures, proposals, methods and / or operation sequences disclosed in this document. At least one processor (202) may generate a signal (e.g., baseband signal) including a PDU, SDU, message, control information, data, or information according to the functions, procedures, proposals, and / or methods disclosed in this document and provide it to at least one transceiver (206). At least one processor (202) may receive a signal (e.g., baseband signal) from at least one transceiver (206) and may obtain a PDU, SDU, message, control information, data, or information according to the descriptions, functions, procedures, proposals, methods, and / or operation sequences disclosed in this document.

[0100] At least one processor (202) may be referred to as a controller, microcontroller, microprocessor, or microcomputer. 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 at least one processor (202). The descriptions, functions, procedures, proposals, methods, and / or operation sequences 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. Firmware or software configured to perform the descriptions, functions, procedures, proposals, methods, and / or operation sequences disclosed in this document may be included in at least one processor (202) or stored in at least one memory (204) and driven by at least one processor (202). The descriptions, functions, procedures, proposals, 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.

[0101] At least one memory (204) may be connected to at least one processor (202) and may store various forms of data, signals, messages, information, programs, codes, instructions, and / or commands. At least one memory (204) may be composed of ROM (read-only memory), RAM (random access memory), EPROM (erasable programmable read-only memory), flash memory, hard drive, registers, cache memory, computer read storage media, and / or combinations thereof. At least one memory (204) may be located inside and / or outside of at least one processor (202). Additionally, at least one memory (204) may be connected to at least one processor (202) via various technologies, such as wired or wireless connections.

[0102] At least one transceiver (206) may transmit user data, control information, wireless signals / channels, etc., as mentioned in the methods and / or operation flowcharts, etc. of this document to at least one other device. At least one transceiver (206) may receive user data, control information, wireless signals / channels, etc., as mentioned in the descriptions, functions, procedures, proposals, methods and / or operation flowcharts, etc. disclosed in this document from at least one other device. For example, at least one transceiver (206) may be connected to at least one processor (202) and may transmit and receive wireless signals. For example, at least one processor (202) may control at least one transceiver (206) to transmit user data, control information, or wireless signals to at least one other device. Additionally, at least one processor (202) may control at least one transceiver (206) to receive user data, control information, or wireless signals from at least one other device. Additionally, 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., as described in the descriptions, functions, procedures, proposals, methods, and / or operation sequence diagrams 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).To this end, at least one transceiver (206) may include an (analog) oscillator and / or filter.

[0103] The components of the wireless device described with reference to FIG. 2 may be referred to by other terms in terms of their function. For example, the processor (202) may be referred to as the control unit, the transceiver (206) as the communication unit, and the memory (204) as the storage unit. In some cases, the communication unit may be used to mean at least a part of the processor (202) and the transceiver (206).

[0104] The structure of the wireless device described with reference to FIG. 2 can be understood as the structure of at least part of various devices. For example, the structure of the wireless device exemplified in FIG. 2 may be at least part of the various devices described with reference to FIG. 1 (e.g., robot (100a), vehicle (100b-1, 100b-2), XR device (100c), portable device (100d), home appliance (100e), IoT device (100f), AI device / server (100g)). Furthermore, according to various embodiments, the device may include other components in addition to the components exemplified in FIG. 2.

[0105] For example, the device may be a portable device such as a smartphone, smartpad, wearable device (e.g., smart watch, smart glasses), or portable computer (e.g., 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., audio input / output port, video input / output port), and an input / output unit for inputting and outputting video information / signals, audio information / signals, data, and / or information input by a user.

[0106] For example, the device may be a mobile device such as a mobile robot, vehicle, train, manned / unmanned aerial vehicle (AV), or ship. In this case, the device may further include at least one of a drive unit comprising at least one of an engine, motor, power train, wheel, brake, and steering device of the device; a power supply unit that supplies power and includes a wired / wireless charging circuit, battery, etc.; a sensor unit that senses state 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 acquires position information of the moving body through a GPS (global positioning system) and various sensors.

[0107] For example, the device may be an XR device such as an HMD, a HUD (head-up display) equipped in a vehicle, a television, a smartphone, a computer, a wearable device, a home appliance, 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 acquires control information, data, etc. from the outside and outputs a generated XR object, and a sensor unit that senses state information, environment information, and user information of the device or the surroundings of the device.

[0108] For example, the device may be a robot that can be classified into industrial, medical, household, military, etc., 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 state information, environmental information, and user information of the device or its surroundings, and a drive unit that performs various physical actions, such as moving robot joints.

[0109] For example, the device may be an AI device such as a TV, projector, smartphone, PC, laptop, digital broadcasting terminal, tablet PC, wearable device, set-top box (STB), radio, washing machine, refrigerator, digital signage, robot, 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 state information, environmental information, and user information of the device or its surroundings, and a training unit that learns a model composed of an artificial neural network using training data.

[0110] The structure of the wireless device illustrated in FIG. 2 can be understood as part of a RAN node (e.g., 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 communication. However, if the front haul and / or back haul communication is based on wireless communication, at least one transceiver (206) illustrated in FIG. 2 is used for front haul and / or back haul communication, and the wired transceiver may not be included.

[0111] 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. In this case, 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). In this case, for example, the operation / function of FIG. 3 may be performed in the processor (202) and / or transceiver (206) of FIG. 2. Also, for example, the hardware elements of FIG. 3 may be implemented in the processor (202) and / or 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 embodiments described above.

[0112] A 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 transmission block (e.g., UL-SCH transmission block, DL-SCH transmission block). Here, the information block may include AI-related data (e.g., training data, AI model data, input data, output data, etc.), and the codeword may be an encoded bit sequence corresponding to the AI-related data. The wireless signal may be transmitted through various physical channels (e.g., PUSCH, PDSCH). Specifically, the codeword may be converted into a scrambled bit sequence by scramblers (310). The scrambled sequence used for scrambling is generated based on an initialization value, which 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 methods may include pi / 2-BPSK (pi / 2-binary phase shift keying), m-PSK (m-phase shift keying), m-QAM (m-quadrature amplitude modulation), etc.

[0113] A complex modulation symbol sequence can be mapped to at least one transmission layer by a layer mapper (330). Here, a transmission layer is a logical resource unit for mapping signals or data transmitted through spatial resources to antenna ports, and one transmission layer can correspond to one stream or one antenna port. Each complex modulation symbol included in the complex modulation symbol sequence is mapped to at least one transmission layer, thereby determining which antenna port it will be transmitted through. The modulation symbols of each transmission 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 an N×M precoding matrix W, where N is the number of antenna ports and M is the number of transmission layers. Here, the precoder (340) can perform precoding after performing transform precoding (e.g., a discrete Fourier transform (DFT)) on the complex modulation symbols. Additionally, the precoder (340) can perform precoding without performing transform precoding.

[0114] Resource mappers (350) can map the modulation symbols of each antenna port to time-frequency resources. The time-frequency resources may include multiple symbols (e.g., CP-OFDMA symbols, DFT-s-OFDMA symbols) in the time domain and multiple subcarriers in the frequency domain. Signal generators (360) generate radio signals from the mapped modulation symbols, and the generated radio 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.

[0115] The signal processing process for a received signal in a wireless device can be configured as the inverse of the signal processing process (310 to 360) of FIG. 3. For example, a wireless device (e.g., 200 in FIG. 2) can receive a wireless signal from the outside through an antenna port / transceiver. The received wireless signal can be converted into a baseband signal through a signal restorer. To this end, 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. Subsequently, the baseband signal can be restored into a codeword through a resource de-mapper process, a postcoding process, a demodulation process, and a de-scrambling process. The codeword can be restored into the original information block through decoding. Accordingly, a signal processing circuit (not shown) for a received signal may include a signal restorer, a resource de-mapper, a postcoder, a demodulator, a de-scrambler, and a decoder.

[0116] The signal processing circuit (300) described with reference to FIG. 3 is illustrated 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 less than the number of layers. Furthermore, at least one of the components illustrated in FIG. 3 may be omitted.

[0117] FIG. 4 illustrates a communication procedure between a terminal and a base station applicable to the present disclosure. FIG. 4 illustrates the operation of a terminal (410) and a base station (420) transmitting and / or receiving data, and the operation performed prior to this.

[0118] 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 may include a plurality of synchronization signals (e.g., primary synchronization signal, secondary synchronization signal) classified according to structure or use. Through this, the terminal (410) can identify the boundaries 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).

[0119] In step 403, the terminal (410) obtains system information transmitted from the base station (420). The system information is information related to the attributes, characteristics, and / or capabilities of the base station (420) required to connect to the base station (420) and use the service, and can be classified according to content (e.g., whether it is essential for connection), transmission structure (e.g., channel used, whether it is provided on-demand), etc., and can be classified, for example, into a master information block (MIB) and a system information block (SIB). If necessary, the terminal (410) may transmit a signal requesting the system information prior to receiving the system information. The system information may include information related to AI functions. For example, the system information is information required for operations 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. However, the request and provision of the system information may be performed after the random access procedure described later.

[0120] 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 for the random access procedure (e.g., random access preamble, RAR (random access response) message, etc.) based on information related to the random access channel of the base station (420) obtained through system information (e.g., channel location, channel structure, structure of supported preamble, etc.). For example, the terminal (410) may transmit a preamble (e.g., MSG1) through the random access channel, receive a RAR message (e.g., MSG2), transmit a message (e.g., MSG3) containing 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 can be transmitted and received as a single message, or MSG2 and MSG4 can be transmitted and received as a single message.

[0121] 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 the connection (e.g., a radio resource control (RRC) layer), a layer that handles mapping between logical channels and transmission 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 to establish a connection, signaling to determine settings related to communication, and signaling to indicate allocated resources. Additionally, the signaling of control information may be performed to convey information related to AI functions. For example, information related to AI functions is information necessary for operations 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, the information related to the AI ​​function signaled in step 407 can be combined and / or combined with the information related to the AI ​​function signaled in step 403, and both can be defined as having a hierarchical, mutually complementary, or substitute structure.

[0122] In step 409, the terminal (410) and the base station (420) transmit and / or receive data. That is, the terminal (410) and the base station (420) can process, transmit and / or receive data based on the signaling of control information. For example, when transmitting data, the terminal (410) or the base station (420) may 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) may perform at least one of signal extraction from resources, antenna-specific waveform demodulation, signal placement considering layer mapping, constellation demapping, descrambling, and channel decoding. Here, the transmitted data is AI-related data, and may include, for example, data for AI-based operations or data generated by AI-based operations.

[0123] Steps 401 through 409 described with reference to FIG. 4 must not necessarily be performed in the order exemplified in FIG. 4, and the order of at least some of the steps may vary. Additionally, at least some of steps 401 through 409 may be combined into a single step or omitted. That is, the steps exemplified in FIG. 4 may be performed in various modified forms.

[0124] 6G communication systems and core implementation technologies of 6G systems

[0125] 5G systems define various operating bands within FR1 (frequency range 1), which includes 410 MHz to 7125 MHz, and FR2 (frequency range 2), which includes 24,250 MHz to 71,000 MHz. Various frequencies are being discussed as operating bands for subsequent 6G systems, and the use of frequencies higher than those of 5G systems is also being considered for wider bandwidth and higher transmission speeds. As one example, the use of the THz (Terahertz) frequency band, which includes approximately 100 GHz to 10 THz, is being discussed. The THz frequency band is a band that possesses both the penetrability of radio waves and the directivity of optical waves, and communication using the THz frequency band is expected to play a transitional role from existing radio-based communication to optical-based communication.

[0126] As such, 6G systems utilizing the THz frequency band aim for i) very high data rates per device, ii) a very large number of connected devices, iii) global connectivity, iv) very low latency, v) reduced energy consumption of battery-free IoT devices, vi) ultra-reliable connectivity, and vii) connected intelligence with machine learning capabilities. The vision of 6G systems can be four aspects such as "intelligent connectivity," "deep connectivity," "holographic connectivity," and "ubiquitous connectivity," and 6G systems can be designed to satisfy requirements such as those shown in [Table 1] below.

[0127] Per device peak data rate1 TbpsE2E latency1 msMaximum spectral efficiency100 bps / HzMobility supportup to 1000 km / hrSatellite integrationFullyAIFullyAutonomous vehicleFullyXRFullyHaptic CommunicationFully

[0128] At this time, the 6G system may have key factors such as enhanced mobile broadband (eMBB), ultra-reliable low latency communications (URLC), 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 by a 6G system applicable to the present disclosure. Referring to FIG. 5, the 6G system is expected to have simultaneous wireless communication connectivity 50 times higher than that of a 5G wireless communication system. URLLC, a key feature of 5G, is expected to become an even more dominant technology in 6G communication by providing end-to-end latency of less than 1ms. In this case, 6G systems will have significantly superior volumetric spectral efficiency, unlike the frequently used area-spectral efficiency. Since 6G systems can provide very long battery life and advanced battery technology for energy harvesting, mobile devices in 6G systems may not need to be charged separately. New network characteristics in 6G may be as follows.

[0129] - Satellite Integrated Network: 6G is expected to be integrated with satellites to provide a global mobile population. Integrating terrestrial, satellite, and airborne networks into a single wireless communication system is crucial for 6G.

[0130] - Connected Intelligence: Unlike previous generations of wireless communication systems, 6G is innovative and will update wireless evolution from "connected things" to "connected intelligence." AI can be applied at each stage of the communication process (or at each step of the signal processing described below).

[0131] - 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.

[0132] - Ubiquitous Super 3D Connectivity: Connectivity to the network and core network functions of drones and very low Earth orbit satellites will create Super 3D connectivity in 6G ubiquitous.

[0133] Some general requirements regarding the new network characteristics of 6G mentioned above may be as follows.

[0134] - Small cell networks: The idea of ​​small cell networks was introduced to improve the quality of received signals in cellular systems as a result of increased throughput, energy efficiency, and spectrum efficiency. Consequently, small cell networks are an essential feature of communication systems for 5G and beyond 5G (5GB). Therefore, 6G communication systems also adopt the characteristics of small cell networks.

[0135] - Ultra-dense heterogeneous network: Ultra-dense heterogeneous networks will be another important characteristic of 6G communication systems. Multi-tier networks composed of heterogeneous networks improve overall QoS and reduce costs.

[0136] - High-capacity backhaul: Backhaul connections are characterized as high-capacity backhaul networks to support high-volume traffic. High-speed fiber optics and free-space optics (FSO) systems can be possible solutions to this problem.

[0137] - Radar technology integrated with mobile technology: High-precision localization (or location-based services) through communication is one of the functions of 6G wireless communication systems. Therefore, radar systems will be integrated with 6G networks.

[0138] - Softwarization and virtualization: Softwarization and virtualization are two important features that form the basis of the design process in 5GB networks to ensure flexibility, reconfigurability, and programmability. Additionally, billions of devices can be shared across a shared physical infrastructure.

[0139] To satisfy the aforementioned characteristics, technologies such as 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) may be adopted as core implementation technologies of the 6G system.

[0140] For example, THz communication can be utilized in 6G systems. THz communication is a communication that uses a spectrum in the 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 the THz wave is located in the intermediate region between the infrared band and the millimeter wave band; accordingly, the THz wave can be understood as a radio wave with the shortest wavelength and, at the same time, a light wave with the longest wavelength. As a result, the THz wave shares some characteristics of infrared and microwave waves, and specifically, can simultaneously possess the penetrability of electromagnetic waves and the directivity of light waves.

[0141] FIG. 7 illustrates a transmitter structure applicable to the present disclosure.

[0142] Referring to Fig. 7, in order to modulate data onto an optical signal, the optical source of a laser can be passed through an optical wave guide to change the phase of the signal. At this time, data is loaded by changing electrical characteristics through a microwave contact, etc. Therefore, the optical modulator output is formed as a modulated waveform.

[0143] Data may be provided by 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, for example, information for configuring an AI model, input / output data for tasks of an 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 interact with the data signal generator.

[0144] An O / E converter can generate THz pulses based on optical rectification by a nonlinear crystal, O / E conversion by a photoconductive antenna, emission from a bundle of relativistic electrons, etc. THz pulses generated in such a manner can have a length ranging from femtoseconds to picoseconds. The O / E converter performs down-conversion by utilizing the non-linearity of the device.

[0145] When considering the usage of the THz spectrum, it is highly likely that multiple contiguous GHz bands will be used for fixed or mobile service applications for THz systems. According to outdoor scenario criteria, available bandwidth can be classified 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 composed of multiple band chunks can be considered. As an example of the above framework, if the length of the THz pulse for a single carrier is set to 50 ps, ​​the bandwidth (BW) becomes approximately 20 GHz.

[0146] Effective down-conversion from the infrared band to the THz band depends on how the nonlinearity of the photoelectric converter (O / E converter) is utilized. In other words, to achieve down-conversion to the desired THz band, it is required to design an O / E converter with the most ideal nonlinearity for transferring to that specific band. If an O / E converter that does not match the target frequency band is used, there is a high probability of errors occurring regarding the amplitude and phase of the corresponding pulse.

[0147] In a single-carrier system, a THz transceiver system can be implemented using a single photoelectric converter. Depending on the channel environment, in a multi-carrier system, as many photoelectric converters as there are carriers may be required. This phenomenon will be particularly pronounced in multi-carrier systems utilizing multiple broadbands according to the plans related to the aforementioned spectrum applications. In this regard, a frame structure for the multi-carrier system may be considered. A signal down-frequency converted based on a photoelectric converter can be transmitted in a specific resource region (e.g., a specific frame). The frequency domain of the specific resource region may include multiple chunks. Each chunk may consist of at least one component carrier (CC).

[0148] AI technology can be introduced in 6G systems. Efficient resource management and optimization are required to maintain connectivity between various services and devices. AI technology may include techniques capable of performing 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, designed to discover patterns in input data or perform predictions. To create such an AI / ML model, an AI / ML model training procedure is required to build the model by learning the relationship between input and output in a data-driven manner. Various learning algorithms, such as supervised learning, unsupervised learning, and reinforcement learning, can be utilized as training algorithms. Users can input specific data into a trained AI / ML model to generate output, and the procedure of obtaining output data by inputting input data into the AI / ML model can be referred to as AI / ML 'inference' or 'prediction'.

[0149] Network control parameters can be obtained as output through AI / ML inference using trained AI / ML models. Users can improve network efficiency by utilizing these output parameter values. For example, AI technology can be applied 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.

[0150] In this case, 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 may be referred to as a two-sided AI / ML model or a two-sided model. In this case, the UE may perform the first part of the inference first, and the base station may perform the remaining inference, and vice versa. As another example, all inference may be performed by the UE, and such an AI / ML model may be referred to as a UE-side AI / ML model or a UE-side model.

[0151] In addition, life cycle management (LCM) for AI / ML models can be performed. Life cycle management may include model training, model deployment, model inference, model monitoring, and model updating. To this end, support may be required for data collection, model training, functionality / model identification, model delivery / transfer, model inference operations, functionality / model selection / enable / disable / fallback, functionality / model monitoring, model updating, and UE capabilities.

[0152] 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 the application of AI / ML technology applicable to the present disclosure. First, a data collection function (810) generates training data (801), monitoring data (803), and / or inference data (805) containing processed input data by performing data preparation on input data collected from objects (e.g., UE, RAN node, network node, etc.). A model training function (820), having received the training data (801) from the data collection function (810), performs training on an AI / ML model using the training data (801) and provides the trained / updated model (813) to a model repository (840). The model repository (840) can store and retain the received trained / updated model (813).

[0153] A management function (830) may be used to control AI / ML model training. The management function (830) may control the operation of AI / ML models 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 receive inference output (809) from the inference function (840). The management function (830) performs the role of managing the inference operation so that it can be performed efficiently based on the data received from the data collection function (810) and the inference function (840). 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 operation. Here, the performance feedback may be used to direct the learning goal or as a reward for reinforcement learning. Additionally, the management function (830) can provide management instructions (811) that instruct the inference function (840) to select AI / ML models or AI / ML-based functions to use, enable / disable them, or switch to non-AI / ML operations.

[0154] The inference function (840) generates an inference output (809) by performing inference and / or prediction using 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 transmission / delivery request signal (815) to the model repository function (850) to request the necessary AI / ML model, and the model repository function (850) can transmit the corresponding AI / ML model to the inference function (840) via a model transmission / delivery signal (817). Thus, the inference function (840) can perform inference using the AI / ML model (817) according to the received management instructions (811).

[0155] Additionally, the management function (830) can trigger or perform a specified task / action based on the inference output (809). Thus, the management function (830) can trigger a task / action on other objects (e.g., at least one UE, at least one RAN node, at least one network node, etc.) or on itself. Any one of the functions exemplified in FIG. 8 described above may be performed by two or more entities among the RAN, network node, network operator's OAM, or UE in collaboration. This may be referred to as a split AI operation.

[0156] To use an AI / ML model, not all of the functions (810 to 850) illustrated in FIG. 8 must be used, and the method of combining them is not limited to a specific method. Therefore, 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. Additionally, the model storage function (850) may be included in the memory (204) of FIG. 2.

[0157] 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 a network node. Here, RAN node 1 and RAN node 2 may also transmit data collected from a UE (e.g., UE measurements related to RSRP, RSRQ, SINR of a serving cell and neighboring cells, UE location, velocity, etc.) 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 continue to perform 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 the UE and RAN Node 2. In Step 5, RAN Node 1 generates output data (e.g., prediction or decision) by performing AI model-based inference using the received inference data. In Step 6, if applicable, RAN Node 1 may transmit model performance feedback to the network nodes. In Step 7, RAN Node 1, RAN Node 2, and the UE (or 'RAN Node 1 and UE', or 'RAN Node 1 and RAN Node 2') perform an action based on the output data. For example, in the case of a load balancing action, 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 the network nodes.

[0158] Network nodes can manage AI models based on feedback information regarding the inference results of AI models. For example, network nodes can perform additional training on AI models or generate additional information about AI models (e.g., performance information, accuracy information, etc.). If additional training is performed on AI models, network nodes can distribute the updated AI models to RAN node 1.

[0159] As explained with reference to Fig. 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. Generally, model training requires a large amount of computational resources because it involves optimization using large amounts of data and complex algorithms. In contrast, inference is a process of drawing conclusions about new data using an already trained model, and therefore requires relatively fewer computational resources compared to model training. Therefore, by using the procedure of Fig. 9, model training can be performed through network nodes if the computational resources of the UE or RAN nodes are insufficient. Additionally, security regarding the AI ​​model can be ensured because the AI ​​model is not exposed to the UE.

[0160] FIG. 9 illustrates a case where the model training function (820) is included in a network node and the 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. Subsequently, RAN node 1 receives inference data for AI model inference from the UE and RAN node 2. RAN node 1 generates output data by performing AI model-based inference using the received inference data. Based on the output data, the UE, RAN node 1, and RAN node 2 can perform communication-related operations (e.g., handover, cell change). Subsequently, the UE and RAN node 2 can transmit feedback regarding the operations to RAN node 1. Therefore, RAN Node 1 can train the AI ​​model and update the AI ​​model it will use through feedback information regarding the inference results of the AI ​​model. According to the aforementioned method, since signaling with the network is not required for AI model training and inference, the network load or the latency to train the AI ​​model or receive inference results can be reduced. Additionally, since the UE performs inference using the AI ​​model, the UE's personal information is not transmitted to network nodes, etc. Consequently, security regarding personal information can be enhanced.

[0161] 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 can generate output data by performing inference based on the received AI model. At this time, the data for inference can be received from the RAN node or data acquired by the UE itself can be used. The UE and the RAN node can perform communication-related operations based on the output data generated by inference. Subsequently, the UE can send feedback regarding the operation to the RAN node. Thus, through feedback information regarding the inference results of the AI ​​model, the RAN node can train the AI ​​model and distribute the updated AI model to the UE. According to the method described above, the load on the RAN node can be reduced by having the model training function (820) in the RAN node and the model inference function (840) in the UE perform inference. In addition, if the UE performs inference using data acquired independently, even if the UE loses its connection to the RAN node after receiving the AI ​​model, the UE can continue to perform inference using the received AI model and operate based on the inference results.

[0162] According to the aforementioned framework and procedure, 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 aforementioned framework and procedure, various data such as input data, training data, and inference data are introduced, and the specific details of the aforementioned data may vary depending on the task in which the AI ​​model is utilized. For example, information used in the various embodiments of the present disclosure described below may be included in the aforementioned data.

[0163] FIG. 10 illustrates an AI technology-based communication procedure applicable to the present disclosure. The detailed procedure illustrated in FIG. 10 may be combined with various embodiments of the present disclosure described below. For example, data generated according to various embodiments of the present disclosure may be used for operations (e.g., setup, training, inference, and / or data transmission / reception) in at least one of the detailed procedure illustrated in FIG. 10. As another example, the result of the inference illustrated in FIG. 10 may be used to transmit and / or receive data according to various embodiments of the present disclosure.

[0164] Referring to FIG. 10, in step S1001, at least one of the UE (1010), RAN node (1020), and network node (1030) performs an initial connection 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), RAN node (1020), and network node (1030) performs a configuration procedure. Through the configuration procedure, parameters, resources, connections, and / or entities necessary to perform subsequent procedures at layers between the UE (1010) and the RAN node (1020) and / or at least one layer between the UE (1010) and the network node (1030) may be determined and / or created. At this time, the configuration procedure may be performed based on information, status, and / or characteristics of the AI ​​model used for subsequent training and inference.

[0165] In step S1005, at least one of the UE (1010), RAN node (1020), and network node (1030) performs a model training procedure. At least one of the UE (1010), RAN node (1020), and network node (1030) may collect training data and perform training 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.

[0166] In step S1007, at least one of the UE (1010), RAN node (1020), and network node (1030) performs a task using a trained model. That is, the task may be performed by the result of inference and / or prediction using the trained model. For example, the task may be a procedure belonging to a communication protocol, a preliminary operation for subsequent data transmission and / or reception, related to data transmission and / or reception, or related to data processing (e.g., encoding, decoding, etc.).

[0167] In step S1009, at least one of the UE (1010), RAN node (1020), and 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 the transmission and / or reception of data, in which case this step may be omitted as it is part of step 1007.

[0168] Specific embodiments of the present disclosure

[0169] The present disclosure proposes a procedure for reusing discarded quantum states in a dual-select quantum entanglement distillation system utilizing quantum entanglement. In a dual-select quantum entanglement distillation system, there are cases where a corresponding quantum entanglement state must be discarded based on the measurement results of the quantum state after generating, transmitting, and distilling protocols. Therefore, by reusing the quantum states that need to be discarded, the procedure of additionally generating and transmitting quantum states can be omitted, thereby increasing the efficiency of quantum communication. However, an entanglement distillation protocol (EDP) that uses only reusable qubits requires a large number of reusable qubits. Therefore, a method for performing the entanglement distillation protocol by simultaneously utilizing the initial qubit that passed through the quantum channel and the reusable qubit, rather than the reusable qubit, can be proposed. The present disclosure proposes a technique for efficiently determining the location where reusable qubits are used in an entanglement distillation protocol. The present disclosure proposes a method for determining the location of reusable qubits such that the yield has a maximum value.

[0170] The following describes the components of a quantum communication system and protocols that can be used in recycling procedures.

[0171] The definitions of symbols or abbreviations used in this disclosure are as follows.

[0172] -EPP: Entanglement Purification Protocol

[0173] - EDP: entanglement distillation protocol

[0174] - LOCC: local operator and classical communication

[0175] - QSDC: quantum secure direct communication

[0176] - F: fidelity of initial mixed state

[0177] - p succ : success probability

[0178] - F threshold : channel threshold

[0179] - p g : CNOT gate error rate

[0180] - p m : measurement error rate

[0181] - F target : target fidelity

[0182] - ρ init : EPR pairs transmitted from quantum channel

[0183] - F init : initial fidelity of EPR pair transmitted from quantum channel

[0184] - ρ reuse : reused EPR pairs

[0185] - F init : fidelity of reused EPR pair

[0186] Entanglement

[0187] Entanglement is a property that plays a very important role in distinguishing quantum systems from classical information. Entanglement refers to a state where the results of different observations are closely related to each other. The entangled state in a quantum system acts more strongly than any correlation existing in classical mechanics. Two qubits can be represented in Hilbert space as a superposition of the four fundamental quantum states. Here, the four fundamental quantum states are It includes. The fundamental quantum states of two qubits can be represented through tensor operations on the fundamental states of individual qubits. When the states of two qubits cannot be represented by the tensor product of a single qubit, such qubit states are called entangled states. As representative examples of entangled qubits, there are four cases referred to as EPR (Einstein-Podolsky-Rosen) states, which are as shown in [Equation 1] below.

[0188]

[0189] In [Mathematical Formula 1] It can be used when transmitting classical information 00, and It can be written as, It can be used when transmitting classical information 10, and It can be written as, It can be used when transmitting classical information 01, and It can be written as, It can be used when transmitting classical information 11, and It can be denoted as such. The matching relationship between quantum states and classical information can be defined differently from what was previously described.

[0190] The above EPR state is also called the Bell state, and in each qubit, the measurement result of the qubit located ahead always affects the measurement of the qubit located behind. In addition, the above four pure states are all maximally entangled states and form the vertical basis of the 2-qubit Hilbert space.

[0191] Continuous quantum error

[0192] In conventional information systems, information consists of '0' and '1', and errors are represented when '0' changes to '1' or '1' changes to '0'. Qubit It can be thought of as a single point existing on the surface of a Bloch sphere; when an error in a conventional information system occurs at a qubit, this is referred to as a bit-flip error. Such an error means that the value of 'a' changes to the value of 'b', which implies that when measuring a qubit, the measurement probability has changed from the initial value due to the error. Other forms of errors distinct from those in conventional information systems include class There is a phase flip error in which the phase between changes by 180 degrees. Errors can occur with arbitrary phases along the X-axis or Z-axis, and thus quantum errors can have continuous phases.

[0193] quantum error channel

[0194] FIG. 11 illustrates an example of a quantum channel model based on environmental decoherence in a system applicable to the present disclosure.

[0195] Similar to classical communication, quantum communication procedures can be affected by the quality of transmitted information due to incompleteness existing in the real environment. Interaction with this environment causes irreversible changes in quantum states, which is called decoherence. Environmental decoherence constitutes a major cause of quantum state corruption and can occur not only in quantum memory but also during quantum transmission or quantum processing. Figure 11 is a quantum channel model widely used for modeling environmental decoherence.

[0196] Environmental decoherence can be described as unwanted interactions between a qubit and its environment, more specifically as entanglement, which disrupts the coherent superposition of the fundamental quantum state. For example, a qubit (or quantum system) loses energy due to interactions with its environment; environmental decoherence can occur when the qubit's excited state collapses due to spontaneous photon emission, or when photons are lost or absorbed during transmission through an optical fiber. This type of decoherence process can be modeled using an amplitude damping channel. Another example of environmental decoherence is a model known as dephasing or phase damping, which is characterized by the loss of quantum information without energy loss and can occur, for instance, in cases of photon scattering or perturbations of electronic states caused by stray charges.

[0197] However, for an N-qubit system, the amplitude attenuation channel or phase attenuation channel model results in a resulting system of 2 N Because it requires a Hilbert space of dimension, simulating such channels classically may not be feasible. For efficient classical simulation, amplitude and phase decay channels are Pauli channels It can be approximated as the density operator The input state having is mapped to a state as shown in [Equation 2] below.

[0198]

[0199] In [Mathematical Formula 2], corresponds to a single-qubit Pauli operator and ε is the probability of Pauli X, Pauli Y, and Pauli Z errors occurring. Bit flip errors corresponding to the Pauli X channel and bit-phase flip errors corresponding to the Pauli Y channel are related to amplitude decay, while phase flip errors corresponding to the Pauli Z channel are caused by phase decay. The most practical quantum systems are asymmetric channels, which are channels where one of bit flip, phase flip, or bit-phase flip errors predominates. Bit flip, phase flip, and bit-phase flip errors occur with equal probability ( A special case of a Pauli channel is called a depolarizing channel and can be mathematically expressed as [Equation 3] below.

[0200]

[0201] If one of the qubits in the state passes through the depolarization channel, fidelity Werner state organized as Define as shown in [Equation 4] below.

[0202]

[0203] Furthermore, quantum channels can consider not only quantum states but also errors occurring in operators utilized in quantum circuits. Typically, errors and measurement errors related to the CNOT (controlled NOT operation) (=U) operator are mapped as shown in [Equation 5] below. At this time represents the Pauli I, X, Y, Z operators.

[0204]

[0205] In [Mathematical Formula 5], means the error pattern, and Is It refers to the probability of an error occurring, and means a measurement operator that includes measurement error, and represents the measurement error rate.

[0206] Quantum Entanglement Distillation Protocol (EDP)

[0207] The quantum entanglement distillation protocol is a technique that utilizes local operator and classical communication (LOCC) with multiple entangled states of low fidelity to share a small number of entangled states of high fidelity among multiple parties.

[0208] Various protocols have been developed for entanglement distillation, including recurrence, QPA (quantum privacy amplification), breathing, and hashing. Among these, recurrence and QPA protocols use classical communication bidirectionally from Alice to Bob and from Bob to Alice, while breathing and hashing protocols use classical communication unidirectionally from Alice to Bob. Generally, two-way protocols have the advantage of being able to operate even in poor channel environments compared to unidirectional protocols, while unidirectional protocols have the advantage of utilizing fewer resources compared to two-way protocols.

[0209] High-fidelity EPR states or entangled states generated by the entanglement distillation protocol can be utilized for quantum teleportation or direct quantum communication, quantum key distribution, distributed quantum computing, etc.

[0210] QPA protocol or single selection protocol

[0211] FIG. 12 illustrates an example in which Alice and Bob perform a 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 to probabilistically generate one EPR state with high fidelity.

[0212] As the first step, Alice and Bob operate a unitary operator as shown in [Equation 6] below on the individual qubits of each EPR pair.

[0213]

[0214] In [Mathematical Equation 6], represents the unitary operation that Alice performs, and represents the unitary operation that Bob operates.

[0215] The unitary course and They convert to each other. That is, The subsequent operations correct X and Y errors well but do not correct Z errors well, so the purpose is to convert the Z error of the state after each round into a Y error to correct it in subsequent rounds.

[0216] In the second step, Alice and Bob perform a CNOT operator between the two EPR pairs. Finally, they measure the EPR state operated as the target qubit using the Z basis and share the measurement value via classical communication. If the shared measurement values ​​are the same, Alice and Bob determine that the EPR state operated as the control qubit has higher fidelity and utilize it thereafter; if the shared measurement values ​​differ, they discard the EPR state operated as the control qubit. Therefore, the QPA protocol succeeds probabilistically based on the measurement results, and the probability of success (p succ ) is determined by the initial fidelity (F or Finit).

[0217] When the initial EPR state passes through a symmetric depolarizing channel, the entanglement state after passing through the channel is as shown in [Equation 7] below.

[0218]

[0219] The probability of success p when performing a single round utilizing the Werner state of fidelity F succ and output fidelity F' is as shown in [Equation 8] below.

[0220]

[0221] Additionally, to achieve high fidelity, each round can be performed repeatedly, and when performing n rounds, at least 2 n The EPR status of dogs is utilized.

[0222] Depending on memory availability in the QPA protocol, each round of the QPA protocol can be connected serially rather than in parallel to operate in pumping mode. When operating in entanglement pumping mode, instead of proceeding to a new round using the EPR state output from each round, the round proceeds by utilizing the output EPR state of one round and the initial EPR state; thus, there is an advantage in that the number of quantum memories used is reduced. However, if the increase in fidelity is low and the fidelity reaches a saturation state, it must be switched to a round output EPR pair.

[0223] recurrence protocol

[0224] The recurrence protocol, similar to the QPA protocol, is a bidirectional protocol that utilizes two EPR states in each round to probabilistically generate a single high-fidelity EPR state. The difference is that it performs a twirling operation rather than a unitary operation in the first step. In the first process, Alice and Bob probabilistically apply a twirling operator to the individual qubits of each EPR pair. [Equation 9] below represents the twirling operation.

[0225]

[0226] In [Equation 9], Bx represents an operator that rotates by π / 2 around the X-axis, By represents an operator that rotates by π / 2 around the Y-axis, and Bz represents an operator that rotates by π / 2 around the Z-axis.

[0227] The Twiring process takes an arbitrary mixed state M as a Werner state It is a process to change to.

[0228] In the second step, Alice and Bob perform a CNOT operator between the two EPR pairs. Finally, they measure the EPR state operated as the target using the Z basis and share the measurement value via classical communication. If Alice and Bob determine from the shared measurement that the EPR state operated as the control qubit has higher fidelity, they utilize the EPR state operated as the control qubit; if the shared measurement value is different, they discard the EPR state operated as the control qubit. Therefore, the recurrence protocol succeeds probabilistically based on the measurement result, and the probability of success (p succ ) is determined by the initial fidelity. When a single round is performed using the Werner state of fidelity F, the probability of success is as shown in [Equation 10] below.

[0229]

[0230] Additionally, to achieve high fidelity, each round can be performed repeatedly, and when performing n rounds, at least 2 n The EPR status of dogs is utilized.

[0231] When a single round is performed using the Werner state of fidelity F, the output fidelity F' is as shown in [Equation 11] below.

[0232]

[0233] Depending on memory availability in the recurrence protocol, each round of the recurrence protocol can be connected serially rather than in parallel to operate in pumping mode. When operating in entangled pumping mode, instead of proceeding to a new round using the EPR state output from each round, the round proceeds by utilizing the output EPR state of one round and the initial EPR state; thus, there is an advantage in that the number of quantum memories used is reduced. However, if the increase in fidelity is low and the fidelity reaches a saturation state, it must be switched to a round output EPR pair.

[0234] Due to the difference in the operators used in the first process, when an arbitrary state is used as the input state, it has lower fidelity performance than the QPA protocol.

[0235] double selection protocol

[0236] FIG. 13 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 a recurrence or QPA protocol, but is a protocol that generates one entanglement state by utilizing three EPR states instead of utilizing two EPR states in each round.

[0237] In each round, the double selection protocol procedure can be performed as follows.

[0238] Step S1301: Each sender and receiver (e.g., Alice and Bob) has three entanglement states (ρ (0) , ρ (1) , ρ (2) ) among ρ (0) As the control qubit, ρ (1) Perform CNOT with as the target qubit for each.

[0239] Step S1303: Each sender and receiver ρ (2) As the qubit of the position to the control bit, ρ (1) Perform a CNOT with the qubit of the position as the target bit.

[0240] Step S1305: Each sender and receiver ρ (1) Measure the qubit of the position using the Z basis, and ρ (2) Measure the qubit of the position using the X basis.

[0241] Step S1307: Each transmitter and receiver shares measurement results with each other, and if the transmitter's X basis measurement result matches the receiver's X basis measurement result and the transmitter's Z basis measurement result matches the receiver's Z basis measurement result, then ρ (0) The qubit at the position is preserved. In other cases, where at least one of the X basis measurement result or the Z basis measurement result is inconsistent, ρ (0) Discard the qubit at the position.

[0242] If additional rounds are performed, the transmitter and receiver may apply a Hamadad operator to each input state, change the positions of the control bits and target bits of the CNOT, and convert the measurement basis to repeat steps S1301 through S1307.

[0243] The aforementioned dual-selection protocol is known to have high channel thresholds and maximum fidelity, and a wide gate working range compared to QPA or recurrence protocols.

[0244] Here, the channel threshold refers to the input fidelity (ρ) when the EPR state is preserved in the EDP (entanglement distillation protocol) or EPP (entanglement purification protocol). (0) , ρ (1) It refers to the minimum required fidelity of the input state to be higher than the fidelity of the etc.

[0245] When multiple rounds are performed, the H operator may be applied to each output state. In this disclosure, the twirling version of double selection means performing the twirling operator before each round is performed, and then performing the double selection circuit.

[0246] Recycling of entangled state in the EDP protocol

[0247] The fidelity in the case where the measurement results are inconsistent in a gate error environment is shown as in FIGS. 14 to 17. In FIGS. 14 to 17, the x-axis represents the initial fidelity, and the y-axis represents the fidelity of the output state.

[0248] FIG. 14 is P according to one embodiment of the present disclosure. g =P m When =0, an example of fidelity according to measurement results in the Single Selection (QPA) protocol is illustrated. In Fig. 14, Coincidence means that the measurement results match, No means that the measurement results do not match, and F threshold represents the channel threshold.

[0249] FIG. 15 is P according to one embodiment of the present disclosure. g =P m When =0, an example of fidelity according to measurement results in a dual-selection protocol is illustrated. In FIG. 15, MZ and MX Coincidence means that all measurement results match, No coincidence means that both Z and X measurements do not match, MX means that only the X measurement results match, MZ means that only the Z measurement results match, and F threshold represents the channel threshold.

[0250] FIG. 16 is P according to one embodiment of the present disclosure. g =P m When = 0.2, an example of fidelity according to measurement results in a single-selection protocol is illustrated. In Fig. 16, Coincidence means the case where the measurement results match, No means the case where the measurement results do not match, y=x means the point where the input fidelity and output fidelity are the same without undergoing distillation, and F threshold represents the channel threshold.

[0251] FIG. 17 is P according to one embodiment of the present disclosure. g =P m When = 0.2, an example of fidelity according to measurement results in a dual-selection protocol is illustrated. In FIG. 17, MZ and MX Coincidence signifies the case where all measurement results match, No coincidence signifies the case where both Z and X measurements do not match, MX signifies the case where only the X measurement results match, MZ signifies the case where only the Z measurement results match, y=x signifies the point where the input fidelity and output fidelity are the same without undergoing distillation, and F threshold represents the channel threshold.

[0252] The fidelity in the absence of gate errors for the single-selection (QPA) and double-selection protocols is shown as in FIGS. 14 and FIGS. 15, respectively. Werner state W F When performing entanglement distillation using, F threshold =0.5, and entanglement distillation operates efficiently in an environment of initial fidelity of 0.5 or higher. In cases where the measurement results are inconsistent, the fidelity is always 0.5 or lower, and there is no case of recycling.

[0253] In the presence of gate errors in single-selection and double-selection protocols, the fidelity is represented as shown in FIGS. 16 and FIGS. 17, respectively. Werner state W F When performing entanglement distillation using , the entanglement distillation is F in single selection threshold =0.612, and can operate efficiently in an initial fidelity environment of 0.612 or higher and 0.93 or lower.

[0254] In the case of single selection, within the range 0.612 ≤ F < 0.93, the fidelity when measurement results do not match is always 0.612 or less, so there are no cases of recycling. However, F in double selection threshold = 0.553, and entanglement distillation can operate efficiently in an initial fidelity environment between 0.553 and 0.984. In the case of dual selection, within certain fidelity ranges, if the fidelity is 0.553 or higher where specific measurement results are inconsistent, the corresponding entanglement state can have its fidelity improved through an additional dual-selection EDP process; however, in existing techniques, such entanglement states are discarded without being utilized. Therefore, a method to recycle entanglement states scheduled for discarding can be considered. That is, for F' ≥ F generated when measurement results are inconsistent in an EDP with CNOT and measurement errors, threshold A technique for recycling entanglement states satisfying can be proposed.

[0255] The following methods can be proposed for utilizing recycled qubits. For example, if no gate error exists, a reusable entangled state is generated from input states of different fidelities, and the corresponding recycled qubits can be collected to perform EDP. As another example, an EPR state can be recycled based on the measurement result in a GHZ state, and the recycled qubits can be collected to generate a GHZ state.

[0256] FIG. 18 illustrates an example of signaling of a dual-select EDP utilizing reuse according to one embodiment of the present disclosure. Referring to FIG. 18, after sharing measurement results using classical channels and quantum channels, the output quantum state can be recycled in addition to being preserved or discarded.

[0257] In step S1801, the sender (1810) and the receiver (1820) share configuration information. A connection establishment procedure using a classical channel may be performed first to share the configuration information. Therefore, after the connection establishment procedure, the sender (1810) can transmit the configuration information to the receiver (1820) using the classical channel. The classical channel is a channel different from the channel transmitting both, and may be implemented as a wireless channel, a wired channel, etc.

[0258] The configuration information may include information regarding the resource to which the measurement results are transmitted or the resource to which processing information of the output quantum state is transmitted. Additionally, the configuration information includes whether recycling is not used, and if recycling is used, the threshold value F that serves as the recycling criterion. threshold It may include information about or information about the EDP protocol to be used for recycling. For example, the configuration information includes information about the quantum channel, such as the fidelity F for the entanglement state and the error rate of the quantum operation. It may include.

[0259] In step S1803, the sender (1810) transmits a quantum entangled state. As previously described, the quantum entangled state may utilize an EPR state. The quantum entangled state is transmitted through a quantum channel. For example, the sender (1810) may keep one qubit of the quantum pair of entangled states for himself and transmit the remaining qubit to the receiver (1820) through the quantum channel.

[0260] In steps S1805 and S1807, the transmitter / receiver (1810, 1820) performs an EDP circuit and performs measurements. The EDP circuit may utilize the aforementioned dual-select EDP circuit.

[0261] In step S1809, the receiver (1820) transmits the measurement results to the transmitter (1810). The measurement results may include results regarding the X basis measurement and Z basis measurement of the dual-select EDP circuit. The measurement results may be transmitted over a classical channel, and information regarding the classical channel may be included in the setting information of step S1801. The measurement results may be transmitted in the form of an index using a table, and a codebook may be set for this purpose.

[0262] In step S1811, the transmitter (1810) compares the measurement results and selects one of preservation, reuse, or discard. For example, the transmitter (1810) determines whether to preserve the unmeasured quantum state based on the received measurement results and its own measurement results. If the quantum state is not preserved, the transmitter (1810) estimates the fidelity of the unmeasured quantum state and the channel threshold F threshold Decide whether to reuse or discard by comparing with.

[0263] In step S1813, the sender (1810) transmits the result determined among the determined preservation / reuse / discard to the receiver (1820). The result determined may be transmitted over a classical channel, and information regarding the classical channel may be included in the setting information of step S1801.

[0264] In step S1815, the sender / receiver (1810, 1820) performs a subsequent procedure of the quantum state based on the determined result. Thus, any one of the preservation / reuse / discard procedures may be performed. If reuse is determined, additional EDP or the start of an EDP may be transmitted to the receiver (1820). The configuration information for the additional EDP or EDP may be included in the configuration information of step S1801 or may be transmitted to the receiver (1820) via a separate message.

[0265] The additionally performed EDP is not limited to a specific method. For example, the additionally performed EDP can be determined as any one of the aforementioned recurrence protocol, single-choice protocol, or double-choice protocol.

[0266] Hashing protocol

[0267] FIG. 19 illustrates an example of a QECCs-based hashing protocol according to an embodiment of the present disclosure. A hashing protocol is a unidirectional protocol and is a technique that distills into an entangled state by utilizing a decoding circuit of quantum error correction codes, etc. In the first step, Alice and Bob use a circuit related to quantum error correction codes (QECCs) encoding and decoding ( ) is performed on each EPR state, and a specific qubit is measured similarly to syndrome extraction. In the second process, Alice shares the measurement results with Bob, and Bob performs a correction operator based on the product pattern of his measurement results and Alice's measurement results. The correction operator is determined by the correction operator based on 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 above a threshold value, the unmeasured EPR state has enhanced fidelity.

[0268] 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 to the H transformation of the fixed operator, a decoding circuit for an arbitrary error correction code is utilized. Although it is a CSS state similar to the 3-qubit GHZ state used in multi-party applications, since it is an H-variant state (CSS-H variant), a decoding circuit for the CSS quantum error correction code must be utilized; for the Non-CSS state, the CSS-H code—that is, a quantum error correction code where logical H is expressed in the form of a tensor product of individual (transversal) H—must be utilized. Here, the CSS state is each fixed operator It refers to a state that can be expressed by one of the Pauli operators (X, Y, or Z).

[0269] Breeding protocol

[0270] Breeding protocols are unidirectional protocols, similar to hashing protocols. In breathing protocols This is a protocol for improving n > m low-fidelity EPR states to high-fidelity by utilizing m pure entanglements, where Alice and Bob share n pure entanglements. In this case, to distill a single EPR state, Von-Neumann entropy A 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.

[0271] To execute the breathing 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. In the second step, Alice shares the measurement results with Bob, and Bob performs a correction operator based on the product pattern of his measurement results and Alice's measurement results. If the initial fidelity is above a threshold, the unmeasured EPR states have a fidelity of 1.

[0272] The fidelity performance of the protocol output value can be determined according to the method of performing the BXOR process, and the BXOR circuit can be determined based on the decoding circuit of the quantum error correction code during the BXOR detection process.

[0273] The aforementioned hashing protocol and breathing protocol have a high yield (the number of EPR states required to obtain one EPR state with Fidelity 1) relative to QPA or recurrence, and the yield is expressed as [Equation 12] below.

[0274]

[0275] In [Equation 12], represents Von-Neumann entropy.

[0276] Breeding / hashing protocols can be utilized with QPA / recurrence as needed.

[0277] Distinction between unidirectional and bidirectional entanglement distillation protocols (EDPs).

[0278] The bidirectional (recurrence or QPA protocol) or unidirectional EDP technique consists of a transmitter / receiver, a quantum channel, and a classical channel, as shown in FIGS. 20 and 22.

[0279] (1) Bidirectional EDP technique

[0280] FIG. 20 illustrates an example of the structure of a single round of a bidirectional EDP technique according to an embodiment of the present disclosure. In a single round, the bidirectional EDP technique operates as follows.

[0281] In step S2001, the transmitter (Alice) uses a nonlinear element to generate two EPR states.

[0282] In step S2003, the transmitter transmits one qubit of each EPR state to the receiver (Bob) (a total of 2). At this time, the quantum channel includes the generation defect of the EPR state, wired and wireless photon channels, quantum memory error channels, etc.

[0283] In step S2005, the sender and receiver combine two EPR states as a unitary operation to perform the operation. At this time, if a Werner state is not generated after the quantum channel, the Werner state Unitary operation for conversion and perform CNOT operations.

[0284] In step S2007, the sender and the receiver measure some qubits. In step S2005, the qubit used as the target qubit for the CNOT operation is measured. FIG. 21 illustrates an example of the process in which the sender and the receiver measure qubits according to an embodiment of the present disclosure.

[0285] In step S2009, the receiver transmits its measurement result (1 bit) to the sender via the classical channel.

[0286] In step S2011, the transmitter 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 transmitter and receiver discard the EPR states not used for measurement and repeat the process from steps S2001 to S2009. If the measurement results match, the corresponding qubit is preserved.

[0287] If an EPR state with higher fidelity is required, the transmitter and receiver perform the process of steps S2003 through S2011 using the qubits preserved in a single round. When performing n rounds, at least 2 n The EPR state must be shared between the transmitter and receiver, and additional qubits are required based on the measurement results. Finally, one high-fidelity EPR state is generated.

[0288] (2) Unidirectional EDP technique

[0289] FIG. 22 is a drawing illustrating an example of the structure of a unidirectional EDP technique in a system applicable to the present disclosure.

[0290] In step S2201, for a unidirectional EDP utilizing [[n,k,d]] quantum error correction codes, the transmitter (Alice) uses a nonlinear element to generate n EPR states.

[0291] In step S2203, the transmitter sends one qubit of each EPR state to the receiver (Bob) (a total of n). At this time, the quantum channel includes the generation defect of the EPR state, wired and wireless photon channels, quantum memory error channels, etc.

[0292] In step S2205, the sender and receiver perform a decoding circuit or BXOR circuit of the agreed [[n,k,d]] quantum error correction code as a unitary operation in the case of unidirectional EDP.

[0293] In step S2207, the transmitter and receiver each measure (nk) qubits. At this time, the location of the measured qubits is determined based on the characteristics of the BXOR circuit or the [[n,k,d]] quantum error correction code.

[0294] In step S2209, the receiver transmits the measurement result ((nk) bits) to the sender via the classical channel.

[0295] In step S2211, the transmitter estimates a syndrome or error from the receiver's measurement result and performs a correction operation for error correction on the k qubits that were not measured in step S2207. The correction operator is determined according to the product pattern of the measurement results, and is a Pauli operator One of them operates on the sender's qubit among a pair of EPR states.

[0296] Finally, in the case of a recurrence or QPA bidirectional EDP, one high-fidelity EPR state is preserved, and in the case of a unidirectional EDP using [[n,k,d]] error correction code, k high-fidelity EPR states are preserved.

[0297] Quantum entanglement distillation techniques can correct channel errors in the entanglement state shared by Alice and Bob through the above process. This stems from the process of transferring a portion of the entanglement held by a majority of entanglement states to a minority of entanglement states, and classical channels are utilized for this purpose.

[0298] As such, EDP aims to create an entangled state with high fidelity. Currently known QPA / recurrence protocols have the limitation that they require a lot of resources to generate the target fidelity, and quantum error correction code-based hashing / breeding protocols have the limitation that they only operate at high initial fidelity.

[0299] Adaptive mode EDP protocol

[0300] FIG. 23 illustrates an example of the basic structure of an adaptive mode EDP technique according to one embodiment of the present disclosure. In order to reduce the resource requirements of the existing QPA technique and to extend the fidelity range in which the error correction code-based EDP operates, the method of FIG. 23 is applied in which a decoding circuit of the quantum error correction code or a QPA circuit is optionally utilized in step S2305 (i.e., the unitary operation process), but a discarding process similar to bidirectional EDP is performed for some syndrome patterns of QECCs in step S2311 (i.e., the correction operation / discarding step).

[0301] FIG. 24 illustrates an example of a 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.

[0302] In step S2401, if the QPA mode is selected as the adaptive mode, the bidirectional EDP protocol of FIG. 20 is executed. The following description is the process of the QECCs-based bidirectional EDP technique as the adaptive mode, and the process of distinguishing between the QPA mode and the QECCs-based bidirectional EDP mode will be described later in the fidelity-based parameter estimation process below.

[0303] In step S2403, when using [[n,k,d]] QECCs, the transmitter (Alice) generates n EPR states using nonlinear elements.

[0304] In step S2405, the transmitter sends one qubit of each EPR state to the receiver (Bob). At this time, the quantum channel includes the generation defect of the EPR state, wired and wireless photon channels, quantum memory error channels, etc.

[0305] In step S2407, the sender and receiver perform the decoding circuit of the [[n,k,d]] QECCs, which is agreed upon for the unitary operation, as a unitary operation.

[0306] In step S2409, the sender and receiver each measure (nk) qubits. At this time, the location of the measured qubit is determined based on the characteristics of [[n,k,d]] QECCs.

[0307] In step S2411, the receiver and the sender transmit the measurement results to each other. At this time, each transmits (nk) bits through the classical channel.

[0308] In step S2413, the sender and receiver multiply their own measurement results with the received counterpart's measurement results. Based on the pattern of the multiplied value, they perform correction operations on the k EPR states that were not measured in step S2409, and then either preserve or discard the EPR states. If the EPR states are discarded, steps S2403 through S2411 are performed again. Alice's measurement results, When is Bob's measurement result, the product of the measurement results( If ) belongs to the promised pattern S, step S2415 is performed.

[0309] In step S2415, the transmitter performs a correction operation on its qubit among the k unmeasured EPR states. At this time, the probability of performing the correction operation is p succ It is defined as. The correction operation is According to the pattern It is determined as one of the following and operates on the transmitter's qubit among the EPR pair states of the unmeasured EPR state.

[0310] Variables determining pattern S is correctable through the [[n,k,d]] quantum error correction code Error to be corrected in an EDP utilizing QECCs in adaptive mode among n errors (t corr It is based on ) and is agreed upon in advance between the sender and receiver. Error to be corrected (t corr ) is defined as in [Equation 13] below.

[0311]

[0312] Mean Fidelity-Based Parameter Estimation Process

[0313] When QECCs are utilized in adaptive mode, the fidelity of the EPR state generated after the EDP process is the target fidelity (F target To utilize the minimum EPR state (fidelity F) while satisfying ), the parameters n, k, and d of QECCs and the parameter d of the adaptive mode corr or t corr To estimate, an optimization process according to the following [Equation 14] is performed.

[0314]

[0315] The number of qubits utilized after round n of the result fidelity of the QPA protocol and the final fidelity are determined as shown in [Equation 15] below.

[0316]

[0317] In [Equation 15], p succ,i represents the probability of success in the i-th round, respectively, and represents the fidelity after the i-th round.

[0318] When QECCs are utilized in adaptive mode, the fidelity is as shown in [Equation 16] below.

[0319]

[0320] In [Equation 16], p succ and It has a bound as shown in [Mathematical Formula 17] below.

[0321]

[0322] For convenience of explanation, the method of preparing and distributing qubits of each EPR state between a sender (Alice) and a receiver (Bob) is described as preparing qubits of the EPR state at the sender and transmitting one qubit from each EPR state from the sender to the receiver. However, the qubit generation and distribution methods applicable to the present disclosure are not limited thereto and various methods may be applied. As an example, a method of preparing an EPR state at a third-party node and transmitting it to a first node (e.g., Alice) and a second node (e.g., Bob) may be used in combination with or as an alternative to the procedures described in the present disclosure. As another example, a method of preparing an EPR state at the receiver and transmitting one qubit from the EPR state to the sender may be applied in the same way.

[0323] In addition, depending on the environment, the parameter estimation process can be performed in one of the following scenarios ①, ②, or ③.

[0324] ① When the base station and the terminal share a table based on initial fidelity

[0325] ② Cases where the base station and terminal each perform parameter estimation based on initial fidelity in an environment where tables are not shared

[0326] ③ Cases where the base station performs parameter estimation and informs the terminal of parameter values ​​in an environment where tables are not shared

[0327] In [Equation 14], 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, if a constraint (n≤N) occurs on the number of EPR states that can be transmitted and received at once, optimization is performed using the following [Equation 18].

[0328]

[0329] The look-up table corresponding to the optimal EDP protocol and spec can be determined in various ways, and the look-up table includes the initial fidelity (F) and the target fidelity F target In addition, it may be individually determined according to the number (N) of EPR states that can be transmitted and received. The present disclosure may assume that the base station and the terminal can all possess individual look-up tables in a pre-agreed manner.

[0330] EDP ​​and fidelity-based parameter estimation processes utilizing adaptive mode

[0331] FIG. 25 illustrates an example of the overall procedure of an adaptive mode EDP technique according to one embodiment of the present disclosure. Specifically, FIG. 25 is an overall block diagram integrating the entanglement distillation technique through the aforementioned QPA and the entanglement distillation technique through bidirectional (2-way) QECCs.

[0332] In step S2501, under an environment where initial fidelity and target fidelity are given as constraints, it is determined through the prediction of final resource consumption whether to perform entanglement distillation for the base station and terminal, respectively, via QPA or via bidirectional QECCs. When utilizing bidirectional QECCs EDP, the base station and terminal use QECCs parameters and t corr They share. When using QPA, the base station and the terminal share the number of QPA rounds.

[0333] If bidirectional QECCs are utilized, the base station and the terminal perform step S2503. Step S2503 can perform the process of the QECCs-based bidirectional EDP technique described in FIG. 24. Accordingly, steps S2403 through S2415 can be performed by the base station and the terminal.

[0334] If QPA is utilized, the base station and the terminal perform step S2505. Step S2505 may be performed using the bidirectional EDP protocol technique described in FIG. 20. Accordingly, steps S2001 to S2011 may be performed by the base station and the terminal.

[0335] Minimum Fidelity Sharing in EDP Using Adaptive Mode

[0336] When executing a single round of the EDP protocol in QPA, one high-fidelity EPR pair is generated by utilizing two low-fidelity EPR pairs. At this time, to determine whether a high-fidelity EPR pair has been generated, the transmitter and receiver each measure the single EPR pair they possess and share the measurement results. That is, as shown in Fig. 21, the transmitter and receiver each measure the second qubit and the measurement result ( Shares ). If so, preserve one unmeasured EPR pair; otherwise, discard one unmeasured EPR pair. In contrast, when performing a QECCs-based bidirectional protocol, the syndrome ( ) is t corr Even if included in the set of syndromes presumed to be errors below, the fidelity of the preserved EPR pairs varies depending on the pattern of the syndrome.

[0337] Specific syndrome (e.g.,) rather than average fidelity due to the entire syndrome pattern ) generates EPR pairs with lower fidelity, and thus the present disclosure provides a method for additionally sharing fidelity according to a specific syndrome in adaptive mode. Subsequently, based on the shared minimum fidelity, the transmitter and receiver discard the shared EPR state or utilize the EPR state to perform EDP as needed.

[0338] FIG. 26 illustrates an example of an adaptive mode-based EDP technique procedure considering minimum fidelity according to one embodiment of the present disclosure. Referring to FIG. 26, the transmitter and receiver may additionally share fidelity according to a specific syndrome in adaptive mode and perform additional EDP procedures.

[0339] In step S2601, it is determined whether to perform entanglement distillation via QPA or via bidirectional QECCs for the base station and the terminal, respectively. The criteria for determining the entanglement distillation method may be determined based on average fidelity. For example, the entanglement distillation method may be determined by predicting the final resource consumption in an environment where initial fidelity and target fidelity are given as constraints. The process of dividing the QPA mode and the QECCs-based bidirectional EDP mode will be described later in the process of estimating QECCs parameters based on minimum fidelity.

[0340] If the bidirectional QECCs mode is selected as the adaptive mode, step S2603 is performed, and if the QPA mode is selected, steps S2619 through S2627 are performed. Steps S2619 through S2627 can be performed in the manner described above in steps S2001 through S2009 of FIG. 20. Subsequently, the transmitter and receiver compare their own measurement result bits with the other party's measurement result received via the classical channel; if the measurement results do not match, they discard the EPR state not used for measurement and perform steps S2619 through S2627 again. If the measurement results match, they preserve the EPR state not used for measurement. The case where the 2-way QECCs mode is selected is described below.

[0341] In step S2603, when using the [[n,k,d]] quantum error correction code, the transmitter (Alice) uses a nonlinear element to generate n EPR states.

[0342] In step S2605, the transmitter transmits one qubit of each EPR state to the receiver (Bob). At this time, the quantum channel may include the generation defect of the EPR state, wired and wireless photon channels, quantum memory error channels, etc.

[0343] In step S2607, the sender and receiver perform a decoding circuit of the [[n,k,d]] quantum error correction code promised for unitary operation.

[0344] In step S2609, the sender and receiver each measure (nk) qubits. At this time, the location of the measured qubit is determined based on the characteristics of the [[n,k,d]] quantum error correction code.

[0345] In step S2611, the receiver transmits the measurement result of (nk)bits to the sender via the classical channel.

[0346] In step S2613, the sender multiplies its own measurement result with the received counterparty's measurement result, and based on the pattern of the multiplied value, performs a correction operation on the k EPR states that were not measured in step S2609, and then either preserves or discards the EPR states. If the EPR states are discarded, steps S2603 through S2611 are performed again.

[0347] Alice's measurement results and Bob's measurement results Regarding, the product of the measurement results ( If ) belongs to the promised pattern S, step S2615 is performed.

[0348] In step S2615, the transmitter performs a correction operation on its qubit among the k unmeasured EPR states. The correction operation is According to the pattern It is determined as one of the following and is performed on the sender's qubit among the EPR pair states of the unmeasured EPR state. If the EPR state is preserved during the execution of steps S2613 to S2615, the sender estimates the fidelity of k EPR states based on the product of the measurement results. The sender transmits the estimated fidelity to the receiver via the classical channel to share it. The method for estimating the minimum fidelity will be described later. At the same time, the sender notifies the receiver that the EPR state is preserved.

[0349] For convenience of explanation, the method of preparing and distributing qubits of each EPR state between a sender (Alice) and a receiver (Bob) is described as preparing qubits of the EPR state at the sender and transmitting one qubit from each EPR state from the sender to the receiver. However, the qubit generation and distribution methods applicable to the present disclosure are not limited thereto and various methods may be applied. As an example, a method of preparing an EPR state at a third-party node and transmitting it to a first node (e.g., Alice) and a second node (e.g., Bob) may be used in combination with or as an alternative to the procedures described in the present disclosure. As another example, a method of preparing an EPR state at the receiver and transmitting one qubit from the EPR state to the sender may be applied in the same way.

[0350] Additionally, in step S2611, if Alice and Bob share measurement results with each other, they can each estimate the minimum fidelity. Furthermore, it is self-evident that if Alice and Bob transmit measurement results to each other from both sides, calculate the syndromes respectively, and then Bob (or Alice) performs a correction operation, Alice (or Bob) can estimate the minimum value.

[0351] In step S2617, after performing the adaptive mode, the transmitter and receiver perform additional communication for minimum fidelity sharing. Subsequently, they decide whether to discard or preserve the EPR state preserved in the previous step as needed. 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 entanglement state previously shared via the EDP protocol is high, even entanglement pairs that do not satisfy the target fidelity may be preserved. For example, when an EPR entanglement state is required after a total of 10 distillation protocols, when sharing the 10th entanglement state, if the fidelity is sufficiently high considering the fidelity of the preceding 9, the last EPR entanglement state may be preserved even if its fidelity does not reach the target fidelity.

[0352] [[n,k,d]],t corr Minimum Fidelity Estimation Techniques for Using QECCs Bidirectionally

[0353] When utilizing bidirectional QECCs in adaptive mode, [[n,k,d]], t that satisfy target fidelity on average corr A parameter estimation process exists. However, depending on the syndrome measurement results, there are cases where target fidelity is not satisfied; therefore, an additional process is required to provide fidelity corresponding to each syndrome after its occurrence. The following describes a method for estimating fidelity when a specific syndrome occurs.

[0354] F=F init In the initial fidelity of In the event of a weight error syndrome, the minimum fidelity (F' of the output state) min ) has a lower bound as shown in [Equation 19] below, and in this disclosure, output fidelity is estimated through said lower bound.

[0355]

[0356] p is the probability of performing a correction operation succ It is defined as. Success probability (p succ In the case of ), it is estimated as shown in [Equation 20] below, in the same way as when existing QECCs are utilized in adaptive mode.

[0357]

[0358] Minimum fidelity based n,k,d,t corr Parameter estimation process

[0359] When QECCs are utilized in adaptive mode, the minimum fidelity of the EPR state generated after the EDP process is the target fidelity (F target) To utilize the minimum EPR state (fidelity F) while satisfying , the parameters n, k, and d of QECCs and the parameter t of the adaptive mode corr or or t corr The following optimization process is performed to estimate.

[0360]

[0361] In [Equation 21], the minimum estimated fidelity F' min It can be estimated through [Equation 19].

[0362] FIG. 27 illustrates an example of the entire process of a minimum fidelity-based parameter estimation and an adaptive mode-based EDP technique according to an embodiment of the present disclosure. Referring to FIG. 27, parameter estimation of the minimum fidelity-based adaptive mode and correction operations based on the corresponding parameters can be performed, or the EPR state can be discarded and the protocol can be executed again.

[0363] In step S2701, under an environment where initial fidelity and target fidelity are given as constraints, it is determined through the prediction of final resource consumption whether to perform entanglement distillation for the base station and terminal, respectively, via QPA or via 2-way QECCs. When utilizing 2-way QECCs EDP, the base station and terminal use QECCs parameters and t corr Shares. Here, QECCs parameters and t corr As mentioned above, it can be determined based on minimum fidelity. When utilizing QPA, the base station and the terminal share the number of QPA rounds.

[0364] If 2-way QECCs are utilized, the base station and the terminal perform step S2703. Step S2703 may perform the process of the QECCs-based bidirectional EDP technique described in FIG. 24. Accordingly, steps S2403 through S2415 may be performed by the base station and the terminal.

[0365] If QPA is utilized, the base station and the terminal perform step S2705. Step S2705 may be performed using the bidirectional EDP protocol technique described in FIG. 20. Accordingly, steps S2001 to S2011 may be performed by the base station and the terminal.

[0366] Entanglement State Recycling in EDP Using Bidirectional QECCs

[0367] As mentioned above, when performing EDP in adaptive mode based on minimum fidelity, the fidelity values ​​of unmeasured entanglement pairs differ depending on the syndrome of QECCs.

[0368] When a discarded syndrome is measured, a technique may be considered to utilize unmeasured EPR pairs additionally instead of discarding them. In the case of a bidirectional QECCs EDP that reuses entanglement states, the parameters n, k, d, t corr In addition to t reuseAs parameters are introduced, t reuse represents the maximum weight of the estimation error that allows the entanglement state to be reused.

[0369] Bidirectional QECCs EDP protocol that recycles entanglement state

[0370] FIG. 28 illustrates an example of the entire process of a Two-way QECCs EDP protocol that recycles entangled qubits according to one embodiment of the present disclosure.

[0371] As mentioned above, EPR reuse criteria are selected by utilizing various standards (e.g., t reuse (Select) and the formula used in the optimization process can also be modified. Referring to Fig. 28, the existing optimization is performed in the same way as the existing adaptive mode (i.e., the optimization formula is applied in the same way as before), and a protocol for recycling entangled pairs based on measurement results can be performed.

[0372] As described above, the process of the adaptive mode-based EDP technique may involve a mode selection process. For example, if the QPA mode is selected as the adaptive mode, the bidirectional EDP protocol of FIG. 20 is executed. FIG. 28 describes a procedure for reusing the EPR state when the QECCs-based bidirectional EDP technique is selected as the adaptive mode.

[0373] In step S2801, parameters regarding selection and reuse of the QECCs-based bidirectional EDP mode are determined. To distinguish between the QPA mode and the QECCs-based bidirectional EDP mode, the aforementioned mean fidelity-based parameter estimation process or the minimum fidelity-based n,k,d,t is used. corr A parameter estimation process can be performed. The parameter regarding reuse is t, which is the maximum weight parameter of the estimation error that allows the entanglement state to be reused. reuse may be included. Therefore, t reuseTo select parameters, criteria for reusing the entanglement state can be determined. FIG. 28 shows that when the [[n,k,d]] code is used, the output fidelity F' is equal to the input fidelity F init Greater than t reuse Illustrate an example of a case where is set.

[0374] In step S2803, when utilizing the [[n,k,d]] quantum error correction code, the transmitter (Alice) utilizes a nonlinear element to generate n EPR states.

[0375] In step S2805, the transmitter sends one qubit of each EPR state to the receiver (Bob). At this time, the quantum channel includes the generation defect of the EPR state, wired and wireless photon channels, quantum memory error channels, etc.

[0376] In step S2807, the sender and receiver perform a decoding circuit of the [[n,k,d]] quantum error correction code promised for the Unitary Operation operation as a unitary operation.

[0377] In step S2809, the sender and receiver each measure (nk) qubits. At this time, the location of the measured qubit is determined based on the characteristics of the [[n,k,d]] quantum error correction code.

[0378] In step S2811, the receiver transmits the measurement result of (nk)bits to the sender via the classical channel.

[0379] In step S2813, the sender multiplies its own measurement result with the received counterparty's measurement result and, depending on the pattern of the multiplied value, performs a correction operation on k EPR states that were not measured in step S2809, and then decides whether to (a) preserve, (b) perform additional EDP on the unmeasured EPR states, or (c) discard the EPR states. If the EPR states are discarded (i.e., case (c)), steps S2803 through S2811 are performed again. Alice's measurement results, When is Bob's measurement result, the product of the measurement results( If ) belongs to the promised pattern S, step S2815 is performed.

[0380] if If it does not fall under S, the decision to perform EDP may be additionally determined based on various criteria (i.e., in case (b) or (c)). For example, the decision to perform EDP may 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 (b)), and step S2817 may be performed. If the fidelity of the unmeasured qubit is less than the initial fidelity, the EPR state is discarded (i.e., in case (c)), and steps S2803 through S2811 are performed again. At this time, the aforementioned [[n,k,d]],t corr When QECCs are utilized in a two-way manner, the fidelity of unmeasured qubits can be estimated based on the weight w of the error associated with the syndrome measured in the aforementioned minimum fidelity estimation technique.

[0381] In step S2815, the transmitter performs a correction operation on its qubit among the k unmeasured EPR states (i.e., case (a)). The correction operation is According to the pattern It is determined as one of the following and operates on the transmitter's qubit among the EPR pair states of the unmeasured EPR state.

[0382] If the EPR state is preserved, the sender estimates the fidelity of k EPR states based on the product of measurement results and transmits the estimated fidelity to the receiver via the classical channel for sharing (minimum fidelity sharing is optional; it is unnecessary when based on average fidelity). At the same time, the sender notifies the receiver that the EPR state is preserved.

[0383] In step S2817, if the EPR state is reused, EDP is performed with the unmeasured qubit.

[0384] For convenience of explanation, the method of preparing and distributing qubits of each EPR state between a sender (Alice) and a receiver (Bob) is described as preparing qubits of the EPR state at the sender and transmitting one qubit from each EPR state from the sender to the receiver. However, the qubit generation and distribution methods applicable to the present disclosure are not limited thereto and various methods may be applied. As an example, a method of preparing an EPR state at a third-party node and transmitting it to a first node (e.g., Alice) and a second node (e.g., Bob) may be used in combination with or as an alternative to the procedures described in the present disclosure. As another example, a method of preparing an EPR state at the receiver and transmitting one qubit from the EPR state to the sender may be applied in the same way.

[0385] Additionally, in step S2811, it is evident that Alice and Bob transmit the measurement results to each other from both sides, and after each calculates the syndrome, Bob (or Alice) performs a correction operation and can estimate the fidelity value for Alice (or Bob).

[0386] Also t reuseIt is self-evident that Alice and Bob can decide whether to perform EDP by calculating fidelity based on the measured syndrome without initially agreeing on parameters and not performing the protocol, and by checking whether the criteria for reusing the initial entangled state are satisfied.

[0387] Additional resource reduction techniques in bidirectional QECCs EDP

[0388] (n,k,d,t corr In bidirectional QECCs EDP utilizing ) t corr A technique to correct partial errors with a weight of +1 can be considered. Through this, the fidelity of the output entanglement state is (n,k,d,t corr Although the EDP of bidirectional QECCs using ) becomes lower, the probability of success may increase.

[0389] Parameter α determination technique

[0390] The parameter α is t corr It refers to the number of error syndromes with a weight of +1 that are preserved after correction without discarding the EPR state. (n,k,d,t corr When bidirectional QECCs parameters are utilized, α can be determined using the following [Equation 22] to consume minimal resources while satisfying the goal fidelity.

[0391]

[0392] In [Equation 22], represents the fidelity of the output EPR state when k additional syndromes are corrected, and can be determined as shown in [Equation 23] below.

[0393]

[0394] In [Equation 23], is (n,k,d,t corr ) refers to the probability of success in two-way QECCs EDP, and is (n,k,d,t corr) refers to the output fidelity in two-way QECCs EDP, and is (n,k,d,t corr +1) Refers to the probability of success in two-way QECCs EDP, and is (n,k,d,t corr +1) Refers to the output fidelity in two-way QECCs EDP.

[0395] Analysis of output status

[0396] The Werner state can be expressed as shown in [Equation 24] below.

[0397]

[0398] If, additionally, depending on the syndrome pattern in which a number of errors are corrected and the form of the QECCs utilized, the output entanglement state is non-Werner (i.e., as in [Equation 25]) (If ) a Bell diagonal state W can be generated.

[0399]

[0400] In this case, if additional EDP is performed, EDP performance may be degraded. Additionally, if additional operations are performed by utilizing the output entanglement state, computation may increase. Therefore, if you wish to transform into a Werner state, you can perform the following method.

[0401] When the sender and receiver perform twirling using [Equation 9], the input state It can be changed as shown in [Equation 26] below.

[0402]

[0403] In [Equation 26], B x represents an operator that rotates by π / 2 around the X-axis, and B y represents an operator that rotates by π / 2 around the Y-axis, and B zrepresents an operator that rotates by π / 2 around the Z-axis. If EDP is performed, EDP ​​can be performed by utilizing a quantum error correction code having different X, Y, and Z error correction capabilities depending on the value of . Or of [Equation 27] 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.

[0404]

[0405] Procedure for additional resource reduction in bidirectional QECCs EDP

[0406] FIG. 29 illustrates an example of a procedure for additional resource reduction in a bidirectional QECCs EDP according to one embodiment of the present disclosure.

[0407] In step S2901, the transmitter has bidirectional QECCs EDP parameters (n, k, d, t corr ) parameters initial fidelity (F init ), Goal fidelity (F target Estimated based on ).

[0408] In step S2903, the transmitter determines the number of syndromes α to be additionally corrected and α syndrome patterns.

[0409] In step S2905, the transmitter (Alice) generates n EPR states using a nonlinear element.

[0410] In step S2907, the transmitter sends one qubit of each EPR state to the receiver (Bob). At this time, the quantum channel includes the generation defect of the EPR state, wired and wireless photon channels, quantum memory error channels, etc.

[0411] In step S2909, the sender and receiver perform the [[n,k,d]] quantum error correction code circuit promised for the Unitary Operation operation as a unitary operation.

[0412] In step S2911, the sender and receiver each measure (nk) qubits. At this time, the location of the measured qubit is determined based on the characteristics of the [[n,k,d]] quantum error correction code.

[0413] In step S2913, the receiver transmits the measurement result of (nk)bits to the sender via the classical channel.

[0414] S2915 The sender multiplies its own measurement result by the receiving party's measurement result Determines. If If is included in syndrome pattern S, step S2917 is performed. If If it is not included in the syndrome pattern S, the transmitter may discard the EPR state and perform steps S2905 through S2915.

[0415] In step S2917, the transmitter performs a correction operation on the k EPR states that were not measured in step S2911, based on the pattern of the multiplied values. At this time, the number of syndrome patterns S on which the correction operation is performed is It can become a dog. Correction operation is According to the pattern It is determined as one of the EPR pair states of the unmeasured EPR state and is applied to the transmitter's qubit.

[0416] In step S2919, the transmitter and receiver tween or the aforementioned to make the Werner state. ...performs. Also, the transmitter and receiver are in a Bell diagonal state. It can be saved and used in the future. Step S2919 may be performed optionally depending on the situation.

[0417] For convenience, the method by which the sender (Alice) and the receiver (Bob) prepare and distribute qubits of each EPR state is described as preparing the qubits of the EPR state at the sender and transmitting one qubit from each EPR state from the sender to the receiver. However, the qubit generation and distribution methods applicable to the present disclosure are not limited thereto and various methods may be applied. As an example, the method of preparing an EPR state at a third-party node and transmitting it to a first node (e.g., Alice) and a second node (e.g., Bob) may be used in combination with or as an alternative to the procedures described in the present disclosure. As another example, the method of preparing an EPR state at the receiver and transmitting one qubit from the EPR state to the sender may be applied in the same way.

[0418] Additionally, in step S2913, it is evident that Alice and Bob transmit the measurement results to each other from both sides, and after each calculates the syndrome, Bob (or Alice) performs a correction operation and can estimate the fidelity value for Alice (or Bob).

[0419] Also, if necessary, the weight of the error is t reuse In cases below, A protocol for recycling entanglement states for dog syndrome patterns can be additionally performed.

[0420] The following describes the procedure for an EDP protocol utilizing Bell diagonal state transformation.

[0421] Bell diagonal state transformation method

[0422] The bell diagonal state can be transformed according to each unitary using the following first to fourth transformation methods.

[0423] The first transformation method is as shown in [Equation 28] below. is utilized.

[0424]

[0425] In [Equation 28], is. Through the first transformation method, While and Conversion between them can be performed.

[0426] The second transformation method is as follows [Equation 29] is utilized.

[0427]

[0428] In [Equation 29], is. Through the second transformation method, While , Conversion between them can be performed.

[0429] The third transformation method is as shown in [Equation 30] below is utilized.

[0430]

[0431] In [Equation 30], is. Through the third transformation method, While , Conversion between them can be performed.

[0432] The fourth transformation method is as shown in [Equation 31] below. It is utilized.

[0433]

[0434] In [Equation 31], is. Through the fourth transformation method, While and Conversion between them can be performed.

[0435] and The Bell diagonal state can be freely transformed using operators. Additionally, the Bell diagonal state can be transformed into a Werner state by utilizing Twiring and Pauli Y.

[0436] In addition, considering the global phase, in front of each unitary Includes The same result can be obtained even if is used.

[0437] 2-1 EDP using operator adaptation

[0438] The Z basis measurement of the CNOT and target qubits changes the state of the qubits as shown in [Equation 32] below.

[0439]

[0440] That is, the transmitter and receiver are fixed as shown in Fig. 12 Rather than performing, in accordance with the target performance as shown in Fig. 30 ...can be performed, or an operator adaptation technique, which is a technique that performs twirling as shown in Fig. 31, can be performed. Additionally, due to the characteristics of 2-1 EDP performance, Alternatively, a technique of selecting between twirling can also be performed.

[0441] For example, the initial state In this case, the QPA protocol is always p succ Only Bell diagonal states with fidelity F'=0.692 can be generated with a probability of =0.625, and recurrence is always p succ A Bell diagonal state with F'=0.67 fidelity can be generated with a probability of =0.64. When a computational adaptation technique is utilized, p succ A Bell diagonal state with a fidelity of F'=0.733 can be generated with a probability of =0.58.

[0442] Also, the initial state In this case, improved performance cannot be obtained with the QPA protocol, but when computational adaptation techniques are utilized, If you do it through p succ A Bell diagonal state with a fidelity of F'=0.733 can be generated with a probability of 0.58. The computational adaptation method is not limited to the example described above. Therefore, by utilizing unitary, states with different fidelities can be generated with different success probabilities.

[0443] FIG. 32 illustrates an example of a 2-1 EDP protocol utilizing an operation adaptation technique according to one embodiment of the present disclosure. Referring to FIG. 32, changes in the state of a qubit can be performed by applying different operations depending on the situation.

[0444] In step S3201, through channel estimation The coefficient of the state is determined.

[0445] In step S3203, the transmitter, based on the target output state or the appropriate operator among twirling Select

[0446] In step S3205, the sender generates two EPR states.

[0447] In step S3207, the transmitter sends one qubit of each EPR state to the receiver (Bob). Thus, a total of two qubits are transmitted. The transmitted qubits undergo a quantum channel, and the quantum channel includes the generation defect of the EPR state, wired and wireless photon channels, quantum memory error channels, etc.

[0448] In step S3209, the sender and receiver are the operators determined in process S3203 Perform operations on each qubit using .

[0449] In step S3211, two entangled states are combined and measured as the Z basis for the CNOT and the target qubit of the CNOT.

[0450] In step S3213, the transmitter 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.

[0451] If the shared measurement result is different, the entangled state used as the control qubit is discarded and can be performed again from step S3205.

[0452] For the sake of convenience of explanation, the method by which the sender (Alice) and the receiver (Bob) prepare and distribute qubits of each EPR state is described as a method in which the sender prepares the qubits of the EPR state and transmits one qubit from each EPR state from the sender to the receiver. However, the qubit generation and distribution methods applicable to the present disclosure are not limited thereto and various methods may be applied. As an example, a method of preparing an EPR state at a third-party node and transmitting it to a first node (e.g., Alice) and a second node (e.g., Bob) may be used in combination with or as an alternative to the procedures described in the present disclosure. As another example, a method of preparing an EPR state at the receiver and transmitting one qubit from the EPR state to the sender may be applied in the same way.

[0453] Also, in this disclosure, the same Although the state was considered as an input value, in order to generate the target output state even for different bell diagonal states or the appropriate operator among the twirling It is obvious that you can choose.

[0454] After EDP is performed as in the aforementioned techniques, the generated qubits are based on the measurement results F targetIt can be recycled even if it does not satisfy the condition. For example, if no gate errors exist, a recyclable entangled state is generated from input states of different fidelities, and EDP can be performed by collecting the corresponding recyclable qubits. As another example, an EPR state is recycled based on the measurement result in the GHZ state to generate a GHZ state again, and by performing EDP using the generated GHZ state, F init Above GHZ states may be generated.

[0455] In a dual-select EDP circuit, F init =0.9, F target =0.95, p g In the case where =0.02, F reuse A reusable qubit with a fidelity of = 0.60809 can be generated. By utilizing the double-choice EDP (Twirling version), F init To generate an entangled state with a fidelity of 0.9 or higher, a total of 7 rounds are required, and 5.9644×10⁻⁶ 5 Recyclable qubits are needed. Also, F target To generate an entangled state with a fidelity of 0.95 or higher, a total of 8 rounds are required, and 2.4423 × 10⁻⁶ 6 Recyclable qubits are needed. F init =0.7, F target =0.95, p g Under the condition =0.03, F reuse Recyclable qubits with a fidelity of =0.65 can be generated, and F utilizing the double-choice EDP (Twirling version) init To generate an entangled state with a fidelity of =0.7 or higher, a total of 2 rounds and 65.9 reusable qubits are required. Also, F target To generate an entangled state with a fidelity of 0.95 or higher, a total of 9 rounds are required, and 1.0185 × 10⁻⁶ 7A number of recyclable qubits are required. As previously mentioned, many qubits are required for recycling, and a technique is needed to utilize an appropriate number of recyclable qubits. Accordingly, the present disclosure proposes a technique to utilize an appropriate number of recyclable qubits.

[0456] Method for utilizing recycled qubits to reduce the frequency of quantum channel usage

[0457] In the dual-select EDP (twirling version) circuit, F init =0.9,F target =0.95,p g When = 0.02, by performing 2 rounds, 17.97 entangled states (ρ) passed through the channel init Using ), F'=0.9623(>F target An entangled state ) can be generated. FIG. 33a illustrates an example of a structure of qubits for performing a double-select EDP using one recycled qubit in the first round according to an embodiment of the present disclosure. FIG. 33b illustrates an example of a structure of qubits for performing a double-select EDP using one recycled qubit in the second round according to an embodiment of the present disclosure. FIG. 34 illustrates an example of a structure for performing a double-select EDP with two rounds according to an embodiment of the present disclosure. FIG. 33a and FIG. 33b illustrate an example in which one initial qubit is replaced by a recycled qubit in the double-select EDP of FIG. 34. In FIG. 33a and FIG. 33b, the solid circle represents ρ init It represents the state, and the dotted circle is ρ reuse It signifies the state. The square block in each round represents a dual-select EDP (Twirling version) circuit. The inputs of the dual-select EDP circuit are, in order from top to bottom, ρ in Fig. 13. (0) ,ρ (1) ,ρ (2) It means p i represents the probability that the EDP of the i-th round will succeed, and p i' represents the probability that the EDP succeeds when a reused qubit is utilized in the i-th round. For example, p1' is ρ (0) =ρ reuse ,ρ (1) =ρ (2) =ρ init In this case, it represents the probability that the twirling version of the double selection EDP will succeed. The reusable qubit can be utilized in the first round as shown in FIG. 33a or in the second round as shown in FIG. 33b. When the reusable qubit is utilized in the second round, at least one EDP of the first round can be omitted as shown in FIG. 33b.

[0458] Referring to Fig. 33a, one F reuse =0.60809 Recycled qubit(ρ reuse When ) is used, 18.75 ρ init By utilizing this, an entangled state with F'=0.9451 can be generated. In this case, ρ reuse Utilizing this generates an entangled state with an output fidelity F' that fails to satisfy the target fidelity in two rounds. Therefore, the number of times the quantum channel is used increases despite the use of reusable qubits. Consequently, the reusable qubit ρ reuse If the quantum channel is misused, the number of times the channel is used may increase, the target fidelity may not be satisfied, or the number of times the channel is used may increase while the target fidelity is not satisfied.

[0459] Therefore, by deploying recycled qubits in an appropriate manner, the number of quantum channel uses (ρ to generate one output entangled state) init It is necessary to arrange recycled qubits to have a fidelity greater than the output fidelity while reducing the number of . Therefore, the present disclosure relates to ρ reuse ρ appropriately init We propose a technique that utilizes recycled qubits to replace the quantum channel and satisfy output fidelity while reducing the number of uses.

[0460] Recycled qubit placement method for yield optimization

[0461] Metrics for evaluating entangled distillation protocols include output fidelity, threshold, and yield. This disclosure proposes evaluating entangled distillation protocols based on yield. This disclosure proposes ρ, a reusable qubit, in a direction that optimizes yield. reuse The initial qubit ρ that passed through the quantum channel init We propose a technique to replace it. Here, the reused qubit may be an output qubit that failed in the entanglement distillation protocol. Therefore, F, the fidelity of the reused qubit, is reuse is the fidelity of the initial qubit F init It has a smaller value. Therefore, using reusable qubits reduces the fidelity of the output qubit. The reduced output fidelity is F target If the above fidelity is achieved, reusable qubits can be used to replace qubits that have passed through the quantum channel. Therefore, by utilizing the techniques proposed in this disclosure, the quantum channel can be utilized efficiently.

[0462] F init and F target Given this case, the yield can be defined as [Equation 33] below.

[0463]

[0464] In [Equation 33], n A (F init , F target ) represents the total number of rounds of the EDP protocol, and N A represents the number of qubits used in the n-th round EDP, and p A (F (n-1) ) represents the probability of success of the nth round for the output fidelity in (n-1) rounds.

[0465] For example, as shown in FIG. 34, the total number of qubits is the initial qubit ρinit In the case where it consists only of, the yield is is. As another example, as shown in Fig. 33a, the reusable qubit ρ reuse When utilized, the yield And, as shown in Fig. 33b, the reusable qubit ρ reuse When utilized, the yield is. Here, ρ reuse The cost of is set to 0, but is not limited to this. For example, ρ reuse The cost of is ρ reuse It can be set as the probability of generation.

[0466] To optimize the yield, an optimization function can be defined as shown in [Equation 34] below.

[0467]

[0468] In [Equation 34], Y w reuse The maximum value of Y w.o reuse If it is smaller, it may imply a case where using reusable qubits cannot achieve a fidelity higher than the target output. Therefore, in this case, after performing EDP by aggregating reusable qubits, ρ reuse After increasing the fidelity of [Equation 34], search for a location to optimize the yield again.

[0469] As shown in FIG. 34, for a double-select EDP consisting of 2 rounds, the reusable qubit ρ reuse There are 9 replaceable positions in Round 1 and 3 positions in Round 2. For a double-choice EDP consisting of n rounds, ρ reuse The total number of replaceable locations There are positions. F init 0.9, F target =0.95, p g =0.02, F reuse Up to 2 ρs at =0.608 reuse The yield and output fidelity when utilized are as shown in [Table 2] below.

[0470] Use ρreuse numberF init F reuse Yield^(-1)F'roundF'>F target Reuse Location 00.90.60817.97180.96235721-10.90.60818.75090.88294320110.90.60817.96870.9456120210.90.60817.85830.94998720310.90.60820.04590.9492920410.90.60818.21680.95974421510.90.60818.03990.96043421610.90.60820.04590.95387921710.9 0.60818.21680.96066121810.90.60818.03990.96110921910.90.60815.04750.784231201010.90.60817.59740.930295201110.90.60817.59740.941555201220.90.60817.69580.848061201220.90.60817.61690.851671201320.90.60820.59160.86214820142… … 20.90.60817.39490.954162215620.90.60818.44080.957588215820.90.60818.26520.958156215920.90.60820.03430.950279216720.90.60818.26520.958399216820.90.60818.09040.958936216920.90.60819.36010.95021217920.90.60817.39490.9570421892… …

[0471] In [Table 2], use ρ reuse The number is ρ used in the EDP protocol. reuse It means the number of, and F init represents initial fidelity, and F reuserepresents the fidelity of reusable qubits, Yield^(-1) represents the reciprocal of the yield, F' represents the output fidelity, and round represents the total round of the double-choice EDP. F'>F target represents whether the output fidelity is greater than or equal to the target fidelity, where F'>F target It is denoted as 1 if satisfied, and 0 if not satisfied. The reuse location is ρ reuse This indicates the location where it is used, and the number corresponding to that location is indicated as in FIG. 35. That is, the reuse location is indicated as '1' for the qubit (3501) located at the top of the first round, and as '12' for the qubit (3512) located at the bottom of the second round. When two or more rounds of EDP are performed, the same notation is used. That is, they are indicated in ascending order from the qubit located at the top of the first round to the qubit located at the bottom of the nth round.

[0472] Referring to [Table 2], F'≥F target In the case where two reusable qubits are utilized at the positions of the 5th qubit (3505) and the 6th qubit (3606) within the range satisfying , Y w reuse is maximized, and ρ reuse 0.6 ρ compared to a technique that does not utilize init It uses less and shows a yield improvement of 3.3%.

[0473] As shown in [Table 2] above, a method can be used to investigate all possible locations where reusable qubits can be used and select the location with the best yield. However, when many rounds of EDP are utilized, a lot of resources may be consumed in a brute-force search. Below, a method for efficiently searching for the location of reusable qubits is described.

[0474] To efficiently search for the locations of reusable qubits, the following Steps 1 through 3 may be performed. In the following, it is assumed that in a situation where a dual-choice EDP consisting of n rounds is performed, the number of reusable qubits used is limited to a maximum of m. Here, m can be determined in advance by the quantum communication operator. The locations where reusable qubits can be located in a dual-choice EDP consisting of n rounds are There are. For example, a reusable qubit is an unused vector It can be determined as follows. The initial candidate set of reusable qubits that is not used, S0, can be determined as {(0,0,0,0,0,0,0,0,0,0,0,0)}.

[0475] Step 1: First, the quantum device uses a single reusable qubit ρ reuse When using , F'≥F target Search for a location p1 that satisfies [Equation 35]. A vector regarding reusable qubits can be defined as shown below.

[0476]

[0477] The vector is It consists of components, and when a reusable qubit is used at the p1th position, if the target fidelity requirement is satisfied, the nth component is determined to be '1' and the remaining components are determined to be '0'. The quantum device generates vectors for all p1s and determines a set S1 containing the corresponding vectors. For convenience of explanation, it is assumed below that the quantum device performs a double-choice EDP consisting of 2 rounds as shown in FIG. 35, and that a total of 12th positions (3501 to 3512 in FIG. 35) have been searched. It is assumed that when a single reusable qubit is used at 5th to 9th positions (3505 to 3509 in FIG. 35) through the search, the target fidelity requirement is satisfied. That is, p1 can have values ​​of 5, 6, 7, 8, and 9, and the first candidate set S1 containing vectors indicating one reusable qubit is determined as {(0,0,0,0,1,0,0,0,0,0,0,0), (0,0,0,0,0,1,0,0,0,0,0,0), (0,0,0,0,0,0,1,0,0,0,0,0), (0,0,0,0,0,0,0,1,0,0,0,0), (0,0,0,0,0,0,0,0,1,0,0,0)}.

[0478] Step 2: The quantum device searches for candidate locations for multiple reusable qubits. The locations of multiple reusable qubits can be determined by combinations of the locations of single reusable qubits. For example, if p1 has values ​​5, 6, 7, 8, and 9, at least one ordered pair among (5, 6), (5, 7), (5, 8), (5, 9), (6, 7), (6, 8), (6, 9), (7, 8), (7, 9), and (8, 9) may indicate the locations of multiple reusable qubits. When multiple reusable qubits are used, if reusable qubits are used at the corresponding locations, F' ≥ F target If satisfied, the corresponding locations are valid.

[0479] To determine the locations of these multiple qubits, the locations where the reusable qubits will be used can be determined by utilizing a vector regarding the reusable qubits based on a vector as follows. For the convenience of explanation, the k-th candidate set is defined below as containing at least one vector indicating the locations of k reusable qubits. At this time, the vector included in the k-th candidate set It can be determined based on the sum of vectors included in the k-1 candidate set as shown in [Equation 36] below.

[0480]

[0481] Determined through [Equation 36] Regarding, For position j, ρ reuse By replacing with F'≥F target Check if F'≥F target If so, the k-th candidate set v' is added to it. Through this, the quantum device for k from 1 to m can decide. represents the size of v, and It is the same as.

[0482] Therefore, based on the first candidate set S1 described above, the second candidate set S2 can be determined as {(0,0,0,0,1,1,0,0,0,0,0,0), (0,0,0,0,1,0,0,1,0,0,0,0), (0,0,0,0,1,0,0,0,1,0,0,0), (0,0,0,0,0,1,1,0,0,0,0,0), (0,0,0,0,0,1,0,1,0,0,0,0), (0,0,0,0,0,1,0,0,1,0,0,0), (0,0,0,0,0,0,1,0,0,0), (0,0,0,0,0,0,0,1,0,1,0,0,0), (0,0,0,0,0,0,0,0,1,1,0,0,0)}.

[0483] Step 3: The quantum device determines the locations where reusable qubits will be used based on the yield. For example, the quantum device replaces the reusable qubits at the locations indicated by the 14 vectors included in S0, S1, and S2, respectively, and compares the yields. As a result, the fifth and sixth locations (3505 to 3509 in FIG. 35) having the best yield can be determined as the locations where reusable qubits are used.

[0484] When determining the optimal locations for reusable qubits through the procedure described in Steps 1 through 3 above, the optimal locations can be derived by examining only 1+12+10=23 locations. Conversely, if all location combinations are examined through a brute-force search, 1+12+66 = 79 location combinations must be investigated, requiring more computational power.

[0485] If extended to m=3, for v ∈ { (0,0,0,0,1,1,0,1,0,0,0,0), (0,0,0,0,1,1,0,0,1,0,0,0), (0,0,0,0,1,0,0,1,1,0,0,0), (0,0,0,0,0,1,1,0,1,0,0,0), (0,0,0,0,0,1,0,1,1,0,0,0)}, F'≥F target S2 is formed by comparing with , and 5 locations must be investigated, whereas 220 locations must be investigated when proceeding with a complete investigation, so using the technique proposed in this disclosure can more efficiently determine the locations of reusable qubits.

[0486] FIG. 36 illustrates an example of a procedure for searching for the location of a reusable qubit according to one embodiment of the present disclosure. FIG. 36 illustrates a method performed by a device included in a quantum network (e.g., 1010, 1020, 1030 of FIG. 10). In the description with reference to FIG. 36, the operating entity is referred to as a quantum device, and the quantum device is a device included in a quantum network and can perform the roles of a transmitting node and a receiving node. In FIG. 36, the quantum device has an initial fidelity F init , Target fidelity F target , fidelity F of reusable qubits reuse , operator error rate p g , number of rounds n of the entanglement distillation protocol round It is assumed that it has been obtained in advance.

[0487] Referring to FIG. 36, in step S3601, the quantum device determines the maximum number m of reusable qubits to use. The quantum device gives the initial fidelity F to another device init , Target fidelity F target , fidelity F of reusable qubits reuse , operator error rate p g , number of rounds n of the EDP protocol round and can share the maximum number m of reusable qubits.

[0488] In step S3603, the quantum device determines the location of a single reusable qubit based on the target fidelity. If one of the initial qubits is replaced by a reusable qubit, the quantum device derives the output fidelity F', and then F'≥F target Can determine candidate locations for reusable qubits that satisfy the condition.

[0489] In step S3605, the quantum device determines the locations of m reusable qubits based on the locations of (m-1) reusable qubits. If the output fidelity when a single reusable qubit at a specific location is used does not satisfy the target fidelity condition, the output fidelity for a combination of locations including that location does not satisfy the target fidelity condition. Therefore, based on the locations of the 1 reusable qubit determined in step S3603, the locations of 2 reusable qubits can be determined. Similarly, based on the locations of 2 reusable qubits, the locations of 3 reusable qubits can be determined. By repeating this process, the locations of m reusable qubits can be determined based on the locations of (m-1) reusable qubits.

[0490] In step S3607, the quantum device derives and compares the yield for each of the determined candidate positions. It may derive and compare the yield for cases where zero reusable qubits are used or m reusable qubits are used. Here, it may be determined based on the cost of the qubits and the success rate of the sub-entanglement distillation protocol.

[0491] In step S3609, the quantum device determines the final location of the reused qubits based on the yield. The final location where the reused qubits are used can be determined as the location with the highest yield.

[0492] FIG. 37 illustrates an example of signaling for searching for the location of a reusable qubit according to one embodiment of the present disclosure. Referring to FIG. 37, a transmitting node (3710) and a receiving node (3720) can perform an entanglement distillation protocol using a reusable qubit. To perform FIG. 37, the transmitting node (3710) and the receiving node (3720) may first perform an initial access procedure (e.g., a random access procedure). In FIG. 37, the initial fidelity F init , Target fidelity F target, fidelity F of reusable qubits reuse , operator error rate p g , number of rounds n of the EDP protocol round It is assumed that the maximum number m of reusable qubits that can be used has been obtained in advance by the transmitting node (3710) or the receiving node (3720).

[0493] Referring to FIG. 37, in step S3701, the transmitting node (3710) and the receiving node (3720) share configuration information related to the reusable qubit. The configuration information related to the reusable qubit may include at least one of an initial fidelity, a target fidelity, the fidelity of the reusable qubit, an operator error rate, the number of rounds of the EDP protocol, or the maximum number of reusable qubits available. The configuration information related to the reusable qubit may be shared in various ways. For example, the transmitting node (3710) or the receiving node (3720) may determine the configuration information related to the reusable qubit and transmit it to the other node. For another example, a separate control node may determine the configuration information related to the reusable qubit and transmit it to the transmitting node (3710) or the receiving node (3720).

[0494] In step S3703, the transmitting node (3710) transmits a qubit having an EPR state to the receiving node (3720). The qubit in the EPR state is transmitted through a quantum channel, and the transmitted qubit can be estimated to have an initial fidelity value of a specific value. At this time, the transmitting node (3710) and the receiving node (3720) may first perform a separate measurement procedure to determine the initial fidelity.

[0495] In step S3705, the transmitting node (3710) searches for the location of the reusable qubit based on yield. The reusable qubit may be used in a number less than or equal to the maximum number of reusable qubits included in the configuration information. The location of the reusable qubit may be determined first by a location where a single reusable qubit can be used, and based on the location where a single reusable qubit can be used, a location where multiple reusable qubits can be used may be determined. The transmitting node (3710) searches for candidate locations where the output fidelity is greater than or equal to the target fidelity even when the reusable qubit is used. The location of the reusable qubit may be determined as the location with the highest yield among the searched candidate locations.

[0496] In step S3707, the transmitting node (3710) transmits the location of the reusable qubit to the receiving node (3720). Subsequently, the receiving node (3720) replaces the initial qubit of the EPR state transmitted through the quantum channel with the reusable qubit at the location of the reusable qubit in the entanglement distillation protocol.

[0497] In step S3709, the transmitting node (3710) and the receiving node (3720) perform an entanglement distillation protocol based on the initial qubit and the reused qubit. The entanglement distillation protocol is not limited to a specific protocol. For example, the entanglement distillation protocol performed in step S3709 may use a dual-select entanglement distillation protocol.

[0498] For the sake of convenience of explanation, it has been described that the transmitting node (3710) searches for the location of the reusable qubit, but the procedure for searching for the location of the reusable qubit, which is step S3705, can be performed by the receiving node (3720). In this case, step S3707 requires the receiving node (3720) to transmit the location of the reusable qubit to the transmitting node (3710).

[0499] In the present disclosure, the aforementioned substitution means replacing an existing one with another to perform the same function or role, and the replacement of an initial qubit with a reusable qubit means that a reusable qubit is used instead of an initial qubit in the input of an entanglement distillation protocol. Although the replacement of an initial qubit with a reusable qubit is given as an example in the present disclosure, the form in which an initial qubit is changed to a reusable qubit is not limited to a specific form. For example, an initial qubit may be replaced or exchanged with a reusable qubit. If the receiving node (3720) has quantum memory, the receiving node (3720) first places the initial qubits within the entanglement distillation protocol and replaces some of them with reusable qubits. Subsequently, the receiving node (3720) stores the replaced initial qubits and can use the stored initial qubits for other entanglement distillation protocols, etc.

[0500] Furthermore, parameter values ​​related to the quantum channel, such as initial fidelity, can be assumed to remain unchanged within a specific time interval. Therefore, the location where a reusable qubit is used can be fixedly set within a specific time interval based on the assumed initial fidelity. To measure the initial fidelity value, a procedure to measure characteristics related to the quantum channel may be performed first. The procedure for measuring characteristics related to the quantum channel is not limited to a specific form. For example, the procedure for measuring characteristics related to the quantum channel can be performed periodically, aperiodically, or semi-periodically.

[0501] FIG. 38 illustrates another example of signaling for searching for the location of a reusable qubit according to one embodiment of the present disclosure. Referring to FIG. 38, a transmitting node and a receiving node may perform an entanglement distillation protocol using the reusable qubit. To perform FIG. 38, the transmitting node and the receiving node may first perform an initial connection procedure (e.g., a random access procedure). In FIG. 38, the initial fidelity F init, Target fidelity F target , fidelity F of reusable qubits reuse , operator error rate p g , number of rounds n of the entanglement distillation protocol round It is assumed that the maximum number m of reusable qubits that can be used has been obtained in advance by the transmitting node or the receiving node.

[0502] Referring to FIG. 38, in step S3801, the transmitting node (3810) and the receiving node (3820) share configuration information related to the reusable qubit, and in step S3803, the transmitting node (3810) transmits a qubit having an EPR state to the receiving node (3820). Steps S3801 and S3803 of FIG. 38 can be performed in the same way as steps S3701 and S3703.

[0503] In steps S3805 and S3807, the transmitting node (3810) and the receiving node (3820) each search for a reusable qubit location based on yield. Since the configuration information related to the reusable qubit is shared, the transmitting node (3810) and the receiving node (3820) have the same parameters (e.g., initial fidelity F). init , Target fidelity F target , fidelity F of reusable qubits reuse , operator error rate p g , number of rounds n of the entanglement distillation protocol round The location of the same reusable qubit can be obtained using the maximum number of reusable qubits (m) that can be used. Therefore, unlike FIG. 37, the procedure for transmitting the location of the reusable qubit can be omitted.

[0504] In step S3809, the transmitting node (3810) and the receiving node (3820) perform an entanglement distillation protocol based on the initial qubit and the reused qubit. Since the reused qubit is used, the yield of the entanglement distillation procedure can be increased. Therefore, the consumption of the initial qubit transmitted through the quantum channel can be reduced.

[0505] Although FIGS. 37 and 38 describe that at least one of the transmitting node or the receiving node searches for the location of the reusable qubit, this is not limited thereto. If there is a separate control node, the control node may obtain parameter values ​​for determining the location of the reusable qubit, determine the location of the reusable qubit, and then transmit the location of the reusable qubit to the transmitting node or the receiving node. In this case, the location of the reusable qubit may be included in configuration information related to communication. Which node determines the location of the reusable qubit may be configured differently depending on the communication operator. For example, the node determining the location of the reusable qubit may be determined based on the resources available to each node.

[0506] FIG. 39 illustrates an example of a procedure in which a transmitting node performs an entanglement distillation protocol based on reusable qubits according to one embodiment of the present disclosure. FIG. 39 illustrates a method performed by a device included in a quantum network (e.g., Alice in FIG. 12, Alice in FIG. 13, the transmitter (1810) in FIG. 18, the transmitter in FIG. 20, the transmitter in FIG. 22, the transmitting node (3710) in FIG. 37, and the transmitting node (3810) in FIG. 38). In the description with reference to FIG. 39, the operating entity is referred to as the transmitting node. The transmitting node is a node that transmits specific information using quantum communication and can be various communication devices such as a terminal, a base station, or a repeater. For convenience of explanation, the transmitting node is described below as performing the role of a base station and the receiving node as performing the role of a terminal, but this is not limited thereto.

[0507] Referring to FIG. 39, in step S3901, the transmitting node performs an initial connection procedure. The transmitting node performs the initial connection procedure with the receiving node and can establish a connection with the receiving node. To perform the initial connection procedure, the transmitting node may transmit system information to the receiving node. The system information may be transmitted via a master information block (MIB) and a system information block (SIB). The initial connection procedure may include a random access procedure. The transmitting node receives a signal for initial connection (e.g., a random access preamble) from the receiving node and can transmit a response signal for the signal for initial connection to the receiving node.

[0508] In step S3903, the transmitting node acquires a reusable qubit. The transmitting node and the receiving node may perform an entanglement distillation procedure. Whether the qubits are reused may be determined based on the measurement results of the entanglement distillation procedure. Here, among the output qubits of the entanglement distillation procedure, this refers to a qubit that has a fidelity lower than the target fidelity but can achieve the target fidelity condition if reused. The entanglement distillation procedure may include a double-choice entanglement distillation procedure and is not limited to a specific protocol. The fidelity of the reusable qubit may be lower than the fidelity of the initial qubits received through the quantum channel.

[0509] In step S3905, the transmitting node transmits configuration information related to the reusable qubit to the receiving node. The configuration information related to the reusable qubit may include at least one of the initial fidelity, target fidelity, fidelity of the reusable qubit, operator error rate, the number of rounds of the entanglement distillation protocol, and the maximum number m of reusable qubits that can be used. Here, the initial fidelity may refer to the fidelity of the initial qubits transmitted through the quantum channel in step S3907 below, or a representative value thereof. The configuration information may be assumed to be valid only for a pre-set time interval. For example, the following procedure may be performed assuming that the initial fidelity does not change during a specific time interval. After the first time interval, the initial fidelity for the second time interval may be measured through a quantum channel measurement procedure.

[0510] In step S3907, the transmitting node transmits at least one qubit to the receiving node. The transmitting node may generate pairs of qubits in an EPR state for the receiving node and transmit one qubit among the qubits included in each pair of qubits through the quantum channel.

[0511] In step S3909, the transmitting node transmits the location of the reused qubit. Here, the location of the reused qubit may include at least one of the locations of qubits used as inputs to an entanglement distillation protocol having n rounds. The transmitting node may determine the location of the reused qubit based on configuration information related to the reused qubit.

[0512] In step S3911, the transmitting node performs an entanglement distillation procedure based on the reused qubit. The transmitting node may perform the entanglement distillation procedure after replacing the initial qubit corresponding to the location of the reused qubit with the reused qubit. Because the reused qubit is used, the consumption of the initial qubit transmitted through the quantum channel can be reduced.

[0513] FIG. 40 illustrates an example of a procedure in which a receiving node performs an entanglement distillation protocol based on reusable qubits according to one embodiment of the present disclosure. FIG. 40 illustrates a method performed by a device included in a quantum network (e.g., Bob in FIG. 12, Bob in FIG. 13, the receiver (1810) in FIG. 18, the receiver in FIG. 20, the receiver in FIG. 22, the receiving node (3720) in FIG. 37, and the receiving node (3820) in FIG. 38). In the description with reference to FIG. 40, the operating entity is referred to as the receiving node. The receiving node is a node that transmits specific information using quantum communication and can be various communication devices such as a terminal, a base station, or a repeater. For convenience of explanation, the receiving node is described below as performing the role of a terminal, but is not limited thereto.

[0514] Referring to FIG. 40, in step S4001, the receiving node performs an initial connection procedure. The receiving node performs the initial connection procedure with the transmitting node and can establish a connection with the transmitting node. To perform the initial connection procedure, the receiving node may receive system information from the receiving node. The system information may be transmitted via a master information block (MIB) and a system information block (SIB). The initial connection procedure may include a random access procedure. The receiving node transmits a signal for initial connection (e.g., a random access preamble) to the transmitting node and receives a response signal for the signal for initial connection from the transmitting node.

[0515] In step S4003, the receiving node acquires a reusable qubit. The transmitting node and the receiving node may perform an entanglement distillation procedure. Whether the qubits are reused may be determined based on the measurement results of the entanglement distillation procedure. Here, among the output qubits of the entanglement distillation procedure, this refers to a qubit that has a fidelity lower than the target fidelity but can achieve the target fidelity condition if reused. The entanglement distillation procedure may include a double-choice entanglement distillation procedure and is not limited to a specific protocol. The fidelity of the reusable qubit may be lower than the fidelity of the initial qubits received through the quantum channel.

[0516] In step S4005, the receiving node receives configuration information related to the reusable qubit from the transmitting node. The configuration information related to the reusable qubit may include at least one of an initial fidelity, a target fidelity, the fidelity of the reusable qubit, an operator error rate, the number of rounds of the entanglement distillation protocol, and a maximum number m of reusable qubits that can be used.

[0517] In step S4007, the receiving node receives at least one qubit from the transmitting node. The at least one qubit may include one of the qubits included in the qubit pair of the EPR state.

[0518] In step S4009, the receiving node receives the location of the reused qubit. Here, the location of the reused qubit may include at least one of the locations of qubits used as inputs to an entanglement distillation protocol having n rounds.

[0519] In step S4011, the receiving node performs an entanglement distillation procedure based on the reused qubit. The receiving node may perform the entanglement distillation procedure after replacing the initial qubit corresponding to the location of the received reused qubit with the reused qubit.

[0520] In this disclosure, the term "reusable qubit" as described above is used to refer to an output qubit that does not satisfy the target fidelity after performing an entanglement distillation protocol, but can satisfy the target fidelity if an additional entanglement distillation protocol is performed on that output qubit; however, it is not limited thereto. That is, this disclosure may be applied equally in cases where a low-fidelity qubit having a fidelity lower than that of the initial qubit can be used in any procedure. In this case, the cost of the low-fidelity qubit may be determined by the communication operator when calculating the yield. The term "reusable qubit" as described above may be referred to as a recycled qubit, a low-fidelity qubit, a reprocessed qubit, or a term having an equivalent technical meaning. Although the cost of the reusable qubit in this disclosure is set to '0', the cost may be changed to a different value by the communication operator, just as with the low-fidelity qubit.

[0521] The performance of the dual-selective entanglement distillation protocol using reusable qubits proposed in this disclosure is described below. In the dual-selective entanglement distillation protocol (Twirling version), the reusable qubit ρ reuse The yield when utilizing [ ] can be shown as in [Table 3] to [Table 16] below. In [Table 3] to [Table 16], the number of candidates is ρ investigated when using the proposed technique. reuse It refers to the number of positions, and uses ρ reuse The number is ρ used in the EDP protocol. reuse It means the number of, and F init represents initial fidelity, and F reuse represents the fidelity of reusable qubits, Yield^(-1) represents the reciprocal of the yield, F' represents the output fidelity, and round represents the total round of the dual-select entanglement distillation protocol. F'>F targetrepresents whether the output fidelity is greater than or equal to the target fidelity, where F'>F target It is denoted as 1 if satisfied, and 0 if not satisfied. The reuse location is ρ reuse It signifies the location where it is used, and the index values ​​corresponding to the location can be assigned in ascending order from the qubit located at the top of the first round to the qubit located at the bottom of the nth round in the same way as in Fig. 35.

[0522] Tables 3 through 7 below show the operator error rates p g Represents the yield performance when =0.01. F target When = 0.95, ρ as shown in [Tables 3] to [Table 5] below. reuse The locations of can be explored and the reusable location can be determined.

[0523] candidate (investigative use) ρ reuse SuF init F reuse Yield^(-1)F'roundF'>F target Reuse Location Full Survey Proposal Technique 100.70.5083795.45880.9559741-12012010.70.5083798.72270.95543541277140495020.70.5083799.82610.9546294126, 2728084016170030.70.5083802.79360.9538284124, 26, 27

[0524] candidate (investigative use) ρ reuse SuF init F reuse Yield^(-1)F'roundF'>F targetReuse Location Enumeration Survey Proposal Technique 100.90.559915.44890.97394321-121210.90.559915.83920.960494213663620.90.559915.95070.967039215, 62203530.90.559916.30160.955341217, 8, 94951040.90.559916.03670.954889215, 6, 8, 9792052

[0525] candidate (investigative use) ρ reuse SuF init F reuse Yield^(-1)F'roundF'>F target Reuse Location Full Survey Proposal Technique 100.80.4830393.492750.96625831-393910.80.4830395.913390.96366631974143520.80.4830397.367490.957612318, 99139306730.80.48303100.01540.951908316, 8, 9822511493140.80.48303102.01530.9632783116, 17, 18, 33

[0526] F target When = 0.9, ρ as shown in [Table 6] below reuse The locations of can be explored and the reusable location can be determined.

[0527] candidate (investigative use) ρ reuse SuF init F reuse Yield^(-1)F'roundF'>F target Reuse Location Enumeration Survey Proposal Technique 100.80.4830324.32840.93267921-121210.80.4830325.92220.925576216661520.80.4830326.36050.909205215, 6220430.80.4830327.74220.898996206, 8, 949547925

[0528] F target When = 0.97, ρ as shown in [Table 7] below reuseThe locations of can be explored and the reusable location can be determined.

[0529] candidate (investigative use) ρ reuse SuF init F reuse Yield^(-1)F'roundF'>F target Reuse Location Full Survey Proposal Technique 100.90.559915.44890.97394321-121210.90.559916.0280.97248821666620.90.559916.62030.971091216, 9220034950479205

[0530] Tables 8 through 12 show the operator error rates p g Represents the yield performance when =0.02. F target When = 0.9, ρ as shown in [Tables 8] to [9] below. reuse The locations of can be explored and the reusable location can be determined.

[0531] candidate (investigative use) ρ reuse SuF init F reuse Yield^(-1)F'roundF'>F target Reuse Location Full Survey Proposal Technique 100.750.5734171.28240.92140231-393910.750.5734170.35010.91816231974152920.750.5734163.68530.9050073132, 339139397530.750.5734168.77610.906578313, 17, 18822511977740.750.5734160.18670.9057313117, 18, 35, 365757576251550.750.5734158.39220.9021213117, 18, 21 35, 36

[0532] candidate (investigative use) ρ reuse SuF init F reuse Yield^(-1)F'roundF'>F targetReuse Location Enumeration Survey Proposal Technique 100.830.5285524.40740.93179721-121210.830.5285524.70660.904845213662820.830.5285525.03520.911447215, 6220730.830.5285525.61730.903321215, 6, 9495140.830.5285524.45670.883723215, 6, 8, 9792520

[0533] F target When = 0.95, ρ as shown in [Table 10] to [Table 11] below. reuse The locations of can be explored and the reusable location can be determined.

[0534] candidate (investigative use) ρ reuse SuF init F reuse Yield^(-1)F'roundF'>F target Reuse Location Full Survey Proposal Technique 100.830.52855100.33420.9582331-393910.830.52855101.73220.95627231974130020.830.52855102.16730.951397318, 99139198230.830.52855103.74250.95106318, 9, 1882251750040.830.52855104.59410.950219318, 9, 17, 185757571521950.830.52855106.19330.950224318, 9, 18, 26, 27

[0535] candidate (investigative use) ρ reuse SuF init F reuse Yield^(-1)F'roundF'>F targetReuse Location Enumeration Survey Proposal Technique 100.90.60817.97180.96235721-121210.90.60818.03990.960434216661020.90.60817.39490.954162215, 6220530.90.60817.36480.95186215, 6, 9495140.90.60816.30340.944409205, 6, 8, 97925

[0536] F target When = 0.97, ρ as shown in [Table 12] below reuse The locations of can be explored and the reusable location can be determined.

[0537] candidate (investigative use) ρ reuse SuF init F reuse Yield^(-1)F'roundF'>F target Reuse Location Enumeration Survey Proposal Technique 100.90.60868.36080.97409531-393910.90.60868.50010.9735931974132520.90.60867.46690.9705413135, 369139231130.90.60867.46690.9705413122, 35, 36822511042140.90.60866.47810.9708453122, 23, 24, 365757573349850.90.60866.47810.9708453122, 23, 24, 25, 36

[0538] [Tables 13] through [Table 15] show the operator error rates p g Represents the yield performance when =0.03. F target When = 0.9, ρ as shown in [Table 13] to [Table 14] below. reuse The locations of can be explored and the reusable location can be determined.

[0539] candidate (investigative use) ρ reuse SuF init F reuse Yield^(-1)F'roundF'>F targetReuse Location Full Survey Proposal Technique 100.80.5709793.492750.96625831-393910.80.5709793.695520.96464331974166620.80.5709789.020050.9071353129, 309139760130.80.5709787.170780.9122463132, 33, 39822516207140.80.5709784.942850.9047263112, 32, 33, 3957575738244750.80.5709784.522720.9124343131, 32, 33, 35, 36

[0540] candidate (investigative use) ρ reuse SuF init F reuse Yield^(-1)F'roundF'>F target Reuse Location Full Survey Proposal Technique 100.850.5724525.76940.92480821-121210.850.5724525.51380.902964213661520.850.5724525.13520.906092215, 6220430.850.5724525.02120.900157215, 6, 949547925

[0541] F target When = 0.95, ρ as shown in [Table 15] below reuse The locations of can be explored and the reusable location can be determined.

[0542] candidate (investigative use) ρ reuse SuF init F reuse Yield^(-1)F'roundF'>F targetReuse Location Full Survey Proposal Technique 100.90.6833587.62470.95976931-393910.90.6833584.56720.952039313074149720.90.6833579.49740.953593132, 339139440530.90.6833576.4670.9524223132, 33, 36822512662240.90.6833574.588790.954193120, 21, 35, 3657575711266250.90.6833571.257850.9521313120, 21, 33, 35, 36

[0543] Referring to the aforementioned [Tables 3] through [Table 15], it can be seen that when using the technique for searching for the location of reusable qubits proposed in this disclosure, the yield increases and the number of searched locations decreases. Specifically, as shown in [Table 15], F init =0.9, F reuse =0.68335, F target =0.95, p g In the case where =0.03, 5 ρ reuse In the case of using, 16 or more ρ init It can be seen that usage can be reduced and the yield improves by 22.97%. Additionally, the number of searched reusable qubit positions decreases from 667,927 (39 + 741 + 9139 + 82,251 + 575,757) to 144,225 (39 + 497 + 4405 + 26,622 + 112,662), a 78% reduction. As shown in [Table 8], F init = 0.75, F reuse = 0.5734, F target = 0.9, p g When = 0.02, when 5 ρ_reuses are utilized, 12 or more ρ init It can be seen that usage can be reduced and the yield improves by 8.1%. In addition, the number of searched reusable qubit positions decreases from 667,927 to 86,835, a reduction of 87%. Also, as shown in [Table 6], F init =0.8, Freuse =0.48303, F target =0.9, p g If =0.01, F reuse ρ = 0.48303 reuse It can be confirmed that it cannot be utilized immediately by examining the number of positions of the 31 reusable qubits.

[0544] Hereinafter, examples of wireless device applications to which various embodiments of the present disclosure are applied will be described.

[0545] FIG. 41 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—example / service (see FIG. 1).

[0546] Referring to FIG. 41, the wireless device (200) corresponds to the wireless device (200) of FIG. 2 and may be composed of various elements, components, units / parts, 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 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 additional elements (240) and controls the overall operation of the wireless device. For example, the control unit (220) can control the electrical / mechanical operation of the wireless device based on a program / code / command / information stored in the memory unit (230). Additionally, the control unit (220) can transmit information stored in the memory unit (230) to an external entity (e.g., another communication device) via a wireless / wired interface through the communication unit (210), or store information received from an external entity (e.g., another communication device) via a wireless / wired interface through the communication unit (210) in the memory unit (230).

[0547] The additional element (240) may be configured in various ways depending on the type of 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 holographic device, a public safety device, an MTC device, a medical device, a fintech device (or financial device), a security device, a climate / environment device, an AI server / device (Fig. 1, 400), a base station (Fig. 1, 200), a network node, etc. Depending on the use—e.g., service—the wireless device may be movable or used in a fixed location.

[0548] In FIG. 41, 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 of them 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 the first unit (e.g., 230, 240) may be wirelessly connected via the communication unit (210). Additionally, each element, component, unit / part, and / or module within the wireless device (200) may include one or more additional elements. For example, the control unit (220) may be composed of one or more sets of 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.

[0549] Hereinafter, an implementation example of FIG. 41 will be described in more detail with reference to the drawings.

[0550] FIG. 42 illustrates an example of a portable device applicable to the present disclosure. The portable device may include a smartphone, a smartpad, a wearable device (e.g., a smartwatch, smart glasses), or a portable computer (e.g., a laptop). The portable device may be referred to as a Mobile Station (MS), a User Terminal (UT), a Mobile Subscriber Station (MSS), a Subscriber Station (SS), an Advanced Mobile Station (AMS), or a Wireless Terminal (WT).

[0551] Referring to FIG. 42, 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 part of the communication unit (210). Blocks 210 to 230 / 240a to 240c of FIG. 42 correspond to blocks 210 to 230 / 240 of FIG. 41, respectively.

[0552] 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 the components of the portable device (200) to perform various operations. The control unit (220) may include an AP (Application Processor). The memory unit (230) can store data / parameters / programs / code / commands required for the operation of the portable device (200). Additionally, the memory unit (230) can store input / output data / information, etc. The power supply unit (240a) supplies power to the portable device (200) and may include wired / wireless charging circuits, batteries, etc. The interface unit (240b) can support the connection between the portable device (200) and other external devices. The interface unit (240b) may include various ports (e.g., audio input / output ports, video input / output ports) for connection with external devices. The input / output unit (240c) can receive or output video information / signals, audio information / signals, data, and / or information input by 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, etc.

[0553] For example, in the case of data communication, the input / output unit (240c) acquires information / signals (e.g., touch, text, voice, image, video) input by the user, and the acquired 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 another wireless device or to a base station. Additionally, the communication unit (210) can receive wireless signals from another wireless device or base station and then restore the received wireless signals to their original information / signals. The restored information / signals are stored in the memory unit (230) and then can be output in various forms (e.g., text, voice, image, video, haptic) through the input / output unit (240c).

[0554] FIG. 43 illustrates an example of a vehicle or autonomous vehicle applicable to the present disclosure. The vehicle or autonomous vehicle may be implemented as a mobile robot, a vehicle, a train, an aerial vehicle (AV), a ship, etc.

[0555] Referring to FIG. 43, 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 part of the communication unit (210-1). Blocks 210-1 / 230-1 / 240a-1 to 240d-1 of FIG. 43 correspond to blocks 210 / 230 / 240 of FIG. 41, respectively.

[0556] 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 (Road Side Unit), etc.), and servers. The control unit (220-1) can perform various operations by controlling elements of the vehicle or autonomous vehicle (200-1). The control unit (220-1) may include an Electronic Control Unit (ECU). The driving unit (240a-1) can drive the vehicle or autonomous vehicle (200-1) on the ground. The driving unit (240a-1) may include an engine, motor, power train, wheels, brakes, steering device, etc. The power supply unit (240b-1) supplies power to the vehicle or autonomous vehicle (200-1) and may include wired / wireless charging circuits, batteries, 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 inclination sensor, a weight detection sensor, a heading sensor, a position module, a vehicle forward / reverse 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 technologies such as maintaining the driving lane, technologies for automatically adjusting speed such as adaptive cruise control, technologies for automatically driving along a predetermined path, and technologies for automatically setting a path and driving when a destination is set.

[0557] 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 path and a driving plan based on the acquired data. The control unit (220-1) can control the drive unit (240a-1) so that the vehicle or the autonomous vehicle (200-1) moves along the autonomous driving path according to the driving plan (e.g., speed / direction control). During autonomous driving, the communication unit (210-1) can acquire the latest traffic information data from an external server non-periodically and can acquire surrounding traffic information data from surrounding vehicles. Additionally, 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 path and the driving plan based on the newly acquired data / information. The communication unit (210-1) can transmit information regarding the vehicle location, autonomous driving path, driving plan, etc. to an external server. An external server can predict traffic information data in advance using AI technology, etc., based on information collected from vehicles or autonomous vehicles, and can provide the predicted traffic information data to vehicles 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 and control signals to the vehicle or autonomous vehicle (200-1) through the communication unit (210-2).

[0558] FIG. 44 illustrates an example of a vehicle applicable to the present disclosure. The vehicle may be implemented as a means of transport, a train, an aircraft, a ship, etc. Referring to FIG. 44, 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 FIG. 41, respectively.

[0559] 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 the 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 within the memory unit (230). The input / output unit (240a) may include a HUD. The position measurement unit (240b) can acquire position information of the vehicle (200). The position information may include absolute position information of the vehicle (200), position information within the driving line, acceleration information, position information relative to surrounding vehicles, etc. The position measurement unit (240b) may include GPS and various sensors.

[0560] For example, the communication unit (210) of the vehicle (200) can receive map information, traffic information, etc. from an external server and store it in the memory unit (230). The location measurement unit (240b) can acquire vehicle location information through GPS and various sensors and store it in the memory unit (230). The control unit (220) creates a virtual object based on map information, traffic information, and vehicle location information, etc., and the input / output unit (240a) can display the created virtual object on the glass window inside the vehicle (240a-1, 240a-2). In addition, the control unit (220) can determine whether the vehicle (200) is operating normally within the driving line based on the vehicle location information. If the vehicle (200) deviates abnormally from the driving line, the control unit (220) can display a warning on the glass window inside the vehicle through the input / output unit (240a). Additionally, the control unit (220) can broadcast a warning message regarding a driving abnormality to surrounding vehicles through the communication unit (210). Depending on the situation, the control unit (220) can transmit the vehicle's location information and information regarding the driving / vehicle abnormality to relevant authorities through the communication unit (210).

[0561] FIG. 45 illustrates an example of an XR device applicable to the present disclosure. The XR device may be implemented as an HMD, a Head-Up Display (HUD) equipped in a vehicle, a television, a smartphone, a computer, a wearable device, a home appliance, digital signage, a vehicle, a robot, etc.

[0562] Referring to FIG. 45, 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. 45 correspond to blocks 210 to 230 / 240 of FIG. 41, respectively.

[0563] The communication unit (210) can transmit and receive signals (e.g., media data, control signals, etc.) with external devices such as other wireless devices, mobile devices, or media servers. The media data may include video, images, sound, etc. The control unit (220) can control the components of the XR device (200a) to perform various operations. For example, the control unit (220) may be configured to control and / or perform procedures such as video / image acquisition, (video / image) encoding, metadata generation, and processing. The memory unit (230) may store data / parameters / programs / code / commands required for driving the XR device (200a) or creating an XR object. The input / output unit (240a) acquires control information, data, etc. from the outside and can output the created XR object. The input / output unit (240a) may include a camera, microphone, user input unit, display unit, speaker and / or haptic module, etc. The sensor unit (240b) can obtain XR device status, surrounding environment information, user information, etc. The sensor unit (240b) may include a proximity sensor, an illuminance sensor, an accelerometer, a magnetic sensor, a gyroscope, an inertial sensor, an RGB sensor, an IR sensor, a fingerprint recognition sensor, an ultrasonic sensor, a light sensor, a microphone and / or radar, etc. The power supply unit (240c) supplies power to the XR device (200a) and may include a wired / wireless charging circuit, a battery, etc.

[0564] For example, the memory unit (230) of the XR device (200a) may contain information (e.g., data, etc.) necessary for creating an XR object (e.g., AR / VR / MR object). The input / output unit (240a) may receive 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 operation command. For example, if the user intends to watch movies, news, etc. through the XR device (200a), the control unit (220) may transmit content request information to another device (e.g., mobile device (200b)) or a media server through the communication unit (230). The communication unit (230) may download / stream content such as movies, news, etc. from another device (e.g., 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 the content, and can generate / output an XR object based on information about the surrounding space or real object acquired through the input / output unit (240a) / sensor unit (240b).

[0565] Additionally, 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 acquire three-dimensional position information of the mobile device (200b), and then generate and output an XR object corresponding to the mobile device (200b).

[0566] FIG. 46 illustrates an example of a robot applicable to the present disclosure. Robots may be classified into industrial, medical, domestic, military, etc., depending on the purpose or field of use.

[0567] Referring to FIG. 46, 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. 46 correspond to blocks 210 to 230 / 240 of FIG. 41, respectively.

[0568] 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 the 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 acquire information from outside the robot (200) and output information to outside the robot (200). The input / output unit (240a) may include a camera, microphone, user input unit, display unit, speaker and / or haptic module, etc. 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 accelerometer, a magnetic sensor, a gyroscope, 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 movements, such as moving robot joints. Additionally, the driving unit (240c) may enable the robot (200) to travel on the ground or fly in the air. The driving unit (240c) may include an actuator, a motor, a wheel, a brake, a propeller, etc.

[0569] FIG. 47 illustrates an example of an AI device applicable to the present disclosure.

[0570] AI devices can be implemented as stationary devices 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, vehicles, etc.

[0571] Referring to FIG. 47, 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. 47 correspond to blocks 210 to 230 / 140 of FIG. 41, respectively.

[0572] The communication unit (210) can transmit and receive wired and wireless signals (e.g., sensor information, user input, learning model, control signal, etc.) with external devices such as other AI devices (e.g., 100a to 100f, 120 in FIG. 1) or AI servers (e.g., 100g in FIG. 1) using wired and wireless communication technology. To this end, the communication unit (210) can transmit information within the memory unit (230) to an external device or transmit signals received from an external device to the memory unit (230).

[0573] The control unit (220) can 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. The control unit (220) can perform the determined operation by controlling the components of the AI ​​device (200). For example, the control unit (220) can request, search, receive, or utilize data from the learning processor unit (240c) or the memory unit (230), and can control the components of the AI ​​device (200) to execute a predicted operation or an operation determined to be desirable among at least one executable operation. Additionally, the control unit (220) can collect historical information, including the operation content of the AI ​​device (200) or user feedback regarding the operation, and store it in the memory unit (230) or the learning processor unit (240c), or transmit it to an external device such as an AI server (Fig. 1, 100g). The collected historical information can be used to update the learning model.

[0574] 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 from the learning processor unit (240c), and data obtained from the sensing unit (140). Additionally, the memory unit (230) can store control information and / or software code required for the operation / execution of the control unit (220).

[0575] The input unit (240a) can acquire various types of data from outside the AI ​​device (200). For example, the input unit (220) can acquire training data for model training and input data to which the training model is applied. The input unit (240a) may include a camera, a microphone and / or a user input unit, etc. The output unit (240b) can generate output related to visual, auditory, or tactile senses, etc. 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), surrounding environment information of the AI ​​device (200), and user information using various sensors. The sensing unit (140d) may include a proximity sensor, an illuminance sensor, an accelerometer, a magnetic sensor, a gyroscope, an inertial sensor, an RGB sensor, an IR sensor, a fingerprint recognition sensor, an ultrasonic sensor, a light sensor, a microphone and / or radar, etc.

[0576] The learning processor unit (240c) can train a model composed of an artificial neural network using training 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 through the communication unit (210) and / or information stored in the memory unit (230). Additionally, the output value of the learning processor unit (240c) can be transmitted to an external device through the communication unit (210) and / or stored in the memory unit (230).

[0577] The proposed methods described above may be implemented independently, but they may also be implemented in the form of a combination (or merger) of some of the proposed methods. Rules may be defined so that the base station informs the terminal of the application status of the proposed methods (or information regarding the rules of the proposed methods) through a predefined signal (e.g., a physical layer signal or an upper layer signal).

[0578] The present disclosure may be embodied in other specific forms without departing from the technical ideas and essential features described herein. Accordingly, the above detailed description should not be interpreted restrictively in all respects and should be considered illustrative. The scope of the present disclosure shall be determined by a reasonable interpretation of the appended claims, and all modifications within the equivalent scope of the present disclosure are included within the scope of the present disclosure. Furthermore, embodiments may be constructed by combining claims that are not explicitly related in the claims, or new claims may be included by amendments made after filing.

[0579] One embodiment can be applied to various wireless access systems. Examples of various wireless access systems include the 3GPP (3rd Generation Partnership Project) or 3GPP2 system.

[0580] One embodiment can be applied not only to the various wireless access systems mentioned above, but also to all technical fields utilizing the various wireless access systems. Furthermore, the proposed method can be applied to mmWave and THz communication systems utilizing the ultra-high frequency band.

[0581] Additionally, some embodiments may be applied to various applications such as autonomous vehicles and drones.

Claims

1. Regarding the method, Step of performing a random access procedure with a second device; A step of transmitting setting information to the second device; Step of generating a first signal and a second signal; A step of transmitting the second signal to the second device; A step of determining at least one location within the first entanglement distillation protocol where a reusable qubit is used based on the yield of the first entanglement distillation protocol; and The method includes the step of obtaining a qubit having a fidelity greater than or equal to a first threshold by performing the above-mentioned first entanglement distillation protocol, wherein A method in which the first qubit included in the first signal is in a quantum entanglement state with the second qubit included in the second signal.

2. In Paragraph 1, A method further comprising the step of transmitting information related to at least one location where a reusable qubit is used to the second device.

3. In Paragraph 1, A step of determining the maximum number of locations where reusable qubits are used; A step of determining candidate location vectors indicating locations where reusable qubits less than or equal to the maximum number mentioned above are used; and The method further includes the step of deriving the yield of the first entanglement distillation protocol for each of the above candidate location vectors, The above at least one location is indicated by a candidate location vector having the largest yield among the candidate location vectors.

4. In Paragraph 3, The step of determining the above candidate location vectors is, A step of determining a first set of candidates including candidate location vectors indicating the location where a single reusable qubit is used; The method includes the step of determining a second candidate set including candidate location vectors indicating locations where multiple reusable qubits are used, The candidate location vector indicating the locations where the plurality of reusable qubits are used is determined based on the candidate location vector indicating the location where the single reusable qubit is used, and The above candidate position vectors include candidate position vectors of the first candidate set and the second candidate set.

5. In Paragraph 4, The first candidate set and the second candidate set are composed only of candidate location vectors that satisfy the fidelity condition, and The above fidelity condition is a method in which the output fidelity of the first entanglement protocol, performed based on the above candidate position vectors, is set to be greater than or equal to the target fidelity.

6. In Paragraph 1, A method in which at least one reusable qubit has a smaller fidelity than the first qubit included in the first signal.

7. In Paragraph 6, The above at least one reusable qubit is a method having a fidelity less than or equal to a second threshold among the qubits generated based on the second entanglement distillation protocol.

8. In Paragraph 7, The above second entanglement distillation protocol is a method comprising at least one of a single-selection entanglement distillation protocol, a dual-selection entanglement distillation protocol, and an adaptive mode-based entanglement distillation protocol.

9. In Paragraph 1, The above setting information includes at least one of initial fidelity, target fidelity, fidelity of reusable qubits, operator error rate, and the number of rounds of the entanglement distillation protocol.

10. In Paragraph 1, The above yield is determined based on the cost of the qubits and the success rate of the sub-entanglement distillation protocol, and The cost for the above-mentioned reusable qubit is set to 0, and A method in which the cost for the qubit included in the first signal is set to 1.

11. In Paragraph 1, The first entanglement distillation protocol comprises a plurality of sub-entanglement distillation protocols composed of a plurality of rounds, and The above second entanglement distillation protocol is a method consisting of a single round.

12. In Paragraph 1, The above quantum entanglement state is an EPR (Einstein-Podolsky-Rosen) state, a method.

13. Regarding the method, Step of performing a random access procedure with a first device; A step of receiving setting information from the first device; A step of receiving a second signal from the first device; A step of determining at least one location within the first entanglement distillation protocol where a reusable qubit is used based on the yield of the first entanglement distillation protocol; and The method includes the step of obtaining a qubit having a fidelity greater than or equal to a first threshold by performing the above-mentioned first entanglement distillation protocol, wherein A method in which the first qubit included in the first signal is in a quantum entanglement state with the second qubit included in the second signal.

14. In Paragraph 13, A method further comprising the step of receiving information related to at least one location where a reusable qubit is used from the first device.

15. In the first device, Transmitter / receiver; and It includes a processor coupled to the above-mentioned transmitter and receiver, The above processor is, Perform a random access procedure with the second device, Transmitting setting information to the second device, Generates a first signal and a second signal, and Transmitting the second signal to the second device, Based on the yield of the first entanglement distillation protocol, determine at least one location within the first entanglement distillation protocol where a reusable qubit is used, and By performing the above-mentioned first entanglement distillation protocol, the system is configured to obtain a qubit having a fidelity greater than or equal to a first threshold, wherein A first device in which the first qubit included in the first signal is in a quantum entanglement state with the second qubit included in the second signal.

16. In the second device, Transmitter / receiver; and It includes a processor coupled to the above-mentioned transmitter and receiver, The above processor is, Perform a random access procedure with the first device, Receives setting information from the first device, and Receiving a second signal from the first device, Based on the yield of the first entanglement distillation protocol, determine at least one location within the first entanglement distillation protocol where a reusable qubit is used, and By performing the above-mentioned first entanglement distillation protocol, the system is configured to obtain a qubit having a fidelity greater than or equal to a first threshold, wherein A second device in which the first qubit included in the first signal is in a quantum entanglement state with the second qubit included in the second signal.

17. In the terminal, At least one processor; It includes at least one computer memory connected to the at least one processor and storing instructions that direct operations as they are executed by the at least one processor, The above operations are, Step of performing a random access procedure with a second device; A step of transmitting setting information to the second device; Step of generating a first signal and a second signal; A step of transmitting the second signal to the second device; A step of determining at least one location within the first entanglement distillation protocol where a reusable qubit is used based on the yield of the first entanglement distillation protocol; and The method includes the step of obtaining a qubit having a fidelity greater than or equal to a first threshold by performing the above-mentioned first entanglement distillation protocol, wherein A terminal in which the first qubit included in the first signal is in a quantum entanglement state with the second qubit included in the second signal.

18. In a non-transitory computer-readable medium storing at least one instruction, It includes at least one instruction executable by a processor, The above at least one instruction is, the device, Perform a random access procedure with the second device, Transmitting setting information to the second device, Generates a first signal and a second signal, and Transmitting the second signal to the second device, Based on the yield of the first entanglement distillation protocol, determine at least one location within the first entanglement distillation protocol where a reusable qubit is used, and By performing the above-mentioned first entanglement distillation protocol, the system is configured to obtain a qubit having a fidelity greater than or equal to a first threshold, wherein A computer-readable medium in which the first qubit included in the first signal is in a quantum entanglement state with the second qubit included in the second signal.

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