Methods and apparatus for quantum key distribution

Abstract

This application provides a method and apparatus for quantum key distribution. The method includes: a first device sending k sets of quantum states to a second device through a quantum channel, the k sets of quantum states being associated with k arrays; the first device dividing p arrays of the k arrays into m groups, each of the m groups including at least two arrays; the first device acquiring m first transformation parameters, and transforming the first data of the first array in the i-th group and the second data of the second array in the i-th group according to the i-th first transformation parameter of the m first transformation parameters to obtain third data; finally, the first device determining a security key based on the third data. Based on the above scheme, the impact of rapid changes in channel transmittance on the system performance of a continuous variable quantum key distribution system can be reduced.

Description

Technical Field

[0001] This application relates to the field of quantum communication technology, and in particular to a method and apparatus for quantum key distribution. Background Technology

[0002] With the development of science and technology and the accelerating pace of informatization, communication is becoming increasingly frequent, leading to higher demands for communication security. Quantum secure communication, a novel communication technology developed in recent decades, is a product of combining quantum properties with traditional cryptography. It primarily utilizes the fundamental principles and characteristics of quantum mechanics to ensure communication security. Currently, the most practically applicable technology in quantum secure communication is quantum key distribution (QKD), which enables the unconditional distribution of symmetric keys while already sharing a partial security key. For a unidirectional QKD system, the implementation typically involves encoding the quantum state of a quantum optical signal at the transmitting end using a random key. After transmission through a quantum channel, the signal is detected by the receiver at the receiving end. Then, the transmitting and receiving ends undergo a series of post-processing steps, including data comparison, filtering, and negotiation, through a classical channel, ultimately enabling both parties to share a secure random key.

[0003] From the perspective of information encoding space, quantum key distribution (QKD) can be divided into two types: discrete-variable quantum key distribution (DV-QKD) and continuous-variable quantum key distribution (CV-QKD). DV-QKD typically achieves key distribution by encoding single-photon signals, requiring cryogenic single-photon detectors in fiber optic communication bands. CV-QKD, on the other hand, typically achieves key distribution by encoding coherent states (weak laser light). Its homodyne detectors do not require cryogenic control, and its structure and device characteristics allow for good compatibility with current wavelength division multiplexing (WDM) networks, making it more practical.

[0004] However, for CV-QKD systems, changes in channel transmittance, especially rapid and large-scale changes, can severely impact system performance. For example, when the quantum channel of a CV-QKD system is a spatial channel, the optical power received by the receiver varies randomly due to turbulence, atmospheric scintillation, and equipment movement. Similarly, when the quantum channel of a CV-QKD system is an overhead optical cable, rapid polarization rotation may lead to delayed polarization correction, ultimately altering the signal energy coupled to the receiver. In existing secure code rate assessment mechanisms, such channel power variations are treated as additional noise, causing a decrease in the secure code rate and consequently degrading system performance.

[0005] Therefore, it is desirable to provide a technique that can reduce the impact of rapid changes in channel transmittance on the system performance of CV-QKD systems. Summary of the Invention

[0006] This application provides a method for quantum key distribution that can reduce the impact of rapid changes in channel transmittance on the system performance of a continuous variable quantum key distribution system.

[0007] In a first aspect, a method for quantum key distribution is provided, comprising: a first device sending k sets of quantum states to a second device via a quantum channel, the k sets of quantum states being associated with k arrays; the first device dividing p arrays of the k arrays into m groups, each of the m groups comprising at least two arrays, where m is an integer greater than 1, p is less than or equal to k, and p is greater than or equal to 2m; the first device acquiring m first transformation parameters, the m first transformation parameters corresponding one-to-one with the m groups; the first device transforming the first data of the first array in the i-th group of the m groups and the second data of the second array in the i-th group according to the i-th first transformation parameter to obtain third data, the i-th first transformation parameter being determined based on a first transmittance and the transmittance of the first array and the second array, the i-th first transformation parameter corresponding to the i-th group, where i ∈ [1, m]; and the first device determining a security key based on the third data.

[0008] Therefore, the quantum key distribution method provided in this application can reduce the impact of channel transmittance fluctuations on the secure code rate by transforming data packets. At the same time, this method does not require discarding too much data, has low requirements for system capacity and parallel processing capabilities, and can reduce the uncertainty caused by channel attenuation.

[0009] It should be understood that the first device can be regarded as the transmitting device in the quantum key distribution process, and the second device can be regarded as the receiving device in the quantum key distribution process. The transmitting and receiving devices should adopt the same grouping method. The data in the group should include both transmitting and receiving data. For example, for the first array in the i-th group, the first data is the transmitting data in the first array. The first array also includes the receiving data corresponding to the first data. The first device transforms the transmitting data to obtain the transformed transmitting data, and then uses the transformed data to determine the security key.

[0010] In conjunction with the first aspect, in some implementations of the first aspect, the first device acquires m first transformation parameters, including: the first device receiving the m first transformation parameters from the second device; or, the first device determining the m first transformation parameters based on the first transmittance and the transmittance of at least two arrays of each of the m groups.

[0011] Based on the above scheme, the first device can obtain m first transformation parameters through the second device, or it can determine m first transformation parameters itself, so as to perform data transformation on the grouped data and reduce the impact of fluctuations in channel transmittance.

[0012] In conjunction with the first aspect, in some implementations of the first aspect, the first device divides p arrays out of the k arrays into m groups, including: the first device obtaining k transmittances of the k arrays; the first device dividing p arrays out of the k arrays into m groups according to the k transmittances of the k arrays, wherein in at least two arrays in each of the m groups, the transmittance of one array is greater than or equal to the first transmittance, and the transmittance of the other array is less than or equal to the first transmittance.

[0013] Based on the above scheme, the data can be grouped according to the k transmittance values ​​of the k arrays, such that the transmittance values ​​of each group are either greater than or less than the first transmittance value. This avoids the situation where the transmittance values ​​of the two arrays in each group are both less than the first transmittance value and must be discarded, thereby reducing the amount of data to be discarded.

[0014] In conjunction with the first aspect, in some implementations of the first aspect, the method further includes: the first device determining the first transmittance based on the k transmittances of the k arrays, wherein the absolute value of the difference between the number of transmittances greater than the first transmittance and the number of transmittances less than the first transmittance is less than a first threshold.

[0015] Based on the above scheme, the first transmittance can be determined according to the k transmittances of the k arrays, so that the number of transmittances greater than the first transmittance and the number of transmittances less than the first transmittance are basically the same. In this case, if combined with the above grouping scheme, each array can be basically grouped, thereby reducing the amount of data to be discarded.

[0016] In conjunction with the first aspect, in some implementations of the first aspect, the first transmittance is greater than or equal to the transmittance of one of the at least two arrays in the i-th group, and less than or equal to the transmittance of the other array in the at least two arrays. The i-th first transformation parameter, the first transmittance, the transmittance of the first array, and the transmittance of the second array satisfy the following relationship: Wherein, η1 represents the i-th first transformation parameter, Teff represents the first transmittance, T1 represents the transmittance of the first array, and T2 represents the transmittance of the second array.

[0017] In conjunction with the first aspect, in some implementations of the first aspect, the first data, the second data, the third data, and the i-th first transformation parameter satisfy the following relationship: Wherein, A1 represents the first data, A2 represents the second data, A′1 represents the third data, and η1 represents the i-th first transformation parameter.

[0018] In conjunction with the first aspect, in some implementations of the first aspect, the first transmittance is greater than or equal to the transmittance of one array of at least two groups in the i-th group, and less than or equal to the transmittance of the other array of at least two groups. The i-th first transformation parameter, the first transmittance, the transmittance of the first array, and the transmittance of the second array satisfy the following relationship: Wherein, η1 represents the i-th first transformation parameter, Teff represents the first transmittance, T1 represents the transmittance of the first array, and T2 represents the transmittance of the second array.

[0019] In conjunction with the first aspect, in some implementations of the first aspect, the first data, the second data, the third data, and the i-th first transformation parameter satisfy the following relationship: Wherein, A1 represents the first data, A2 represents the second data, A′2 represents the third data, and η1 represents the i-th first transformation parameter. In a second aspect, a method for quantum key distribution is provided, comprising: a second device receiving k sets of quantum states from a first device via a quantum channel, the k sets of quantum states being associated with k arrays; the second device dividing p arrays of the k arrays into m groups, each of the m groups comprising at least two arrays, where m is an integer greater than 1, p is less than or equal to k, and p is greater than or equal to 2m; the second device acquiring m second transformation parameters, the m second transformation parameters corresponding one-to-one with the m groups; the second device transforming the fourth data of the third array and the fifth data of the fourth array in the i-th group of the m groups according to the i-th second transformation parameter to obtain a sixth data, the i-th second transformation parameter being determined based on a first transmittance and the transmittance of the third and fourth arrays, the i-th second transformation parameter corresponding to the i-th group, where i ∈ [1, m]; and the second device determining a security key based on the sixth data.

[0020] This second device can be viewed as a receiving device in the quantum key distribution process.

[0021] It should be understood that the solutions of the first and second aspects can be implemented in combination. That is, in one case, the first device of the first aspect and the second device of the second aspect can be corresponding transmitting and receiving devices. In this case, the k arrays in the first aspect are the transmitting arrays, and the k arrays in the second aspect are the receiving arrays corresponding to the transmitting arrays.

[0022] In conjunction with the second aspect, in some implementations of the second aspect, the second device acquires m second transformation parameters, including: the second device receiving the m second transformation parameters from the first device; or, the second device determining the m second transformation parameters based on the first transmittance and the transmittance of at least two arrays of each of the m groups.

[0023] In conjunction with the second aspect, in some implementations of the second aspect, the second device divides the p arrays of the k arrays into m groups, including: the second device obtaining the k transmittances of the k arrays; the second device dividing the p arrays of the k arrays into m groups according to the k transmittances of the k arrays, wherein in each of the m groups, at least two arrays have a transmittance of one array greater than or equal to the first transmittance, and a transmittance of the other array less than or equal to the first transmittance.

[0024] In conjunction with the second aspect, in some implementations of the second aspect, the method further includes: the second device determining the first transmittance based on the k transmittances of the k arrays, wherein the absolute value of the difference between the number of transmittances greater than the first transmittance and the number of transmittances less than the first transmittance is less than or equal to a first threshold.

[0025] In conjunction with the second aspect, in some implementations of the second aspect, the first transmittance is greater than or equal to the transmittance of one of the at least two arrays in the i-th group, and less than or equal to the transmittance of the other array in the at least two arrays. The i-th second transformation parameter, the first transmittance, the transmittance of the first array, and the transmittance of the second array satisfy the following relationship:

[0026] In conjunction with the second aspect, in some implementations of the second aspect, the first data, the second data, the third data, and the i-th second transformation parameter satisfy the following relationship: Wherein, B1 represents the fourth data, B2 represents the fifth data, B′1 represents the sixth data, and η2 represents the i-th second transformation parameter.

[0027] In conjunction with the second aspect, in some implementations of the second aspect, the first transmittance is greater than or equal to the transmittance of one of the at least two arrays in the i-th group, and less than or equal to the transmittance of the other array in the at least two arrays. The i-th first transformation parameter, the first transmittance, the transmittance of the first array, and the transmittance of the second array satisfy the following relationship: Wherein, η2 represents the i-th second transformation parameter, Teff represents the first transmittance, T1 represents the transmittance of the first array, and T2 represents the transmittance of the second array.

[0028] In conjunction with the second aspect, in some implementations of the second aspect, the first data, the second data, the third data, and the i-th second transformation parameter satisfy the following relationship: Wherein, B1 represents the fourth data, B2 represents the fifth data, B′2 represents the sixth data, and η2 represents the i-th second transformation parameter. It should be understood that when the first aspect and the second aspect are implemented in combination, the grouping method in the first aspect and the grouping method in the second aspect should be the same. It should also be understood that the method by which the first device performs data transformation in the first aspect should correspond to the method by which the second device performs data transformation in the second aspect. For example, when, in the first aspect, the i-th first transformation parameter, the first transmittance, the transmittance of the first array, and the transmittance of the second array satisfy the following relationship: The first data, the second data, the third data, and the i-th first transformation parameter satisfy the following relationship: In the second aspect, the i-th second transformation parameter, the first transmittance, the transmittance of the first array, and the transmittance of the second array satisfy the following relationship: The first data, the second data, the third data, and the i-th second transformation parameter satisfy the following relationship: Wherein, A1 represents the first data, A2 represents the second data, A′1 represents the third data, η1 represents the i-th first transformation parameter, Teff represents the first transmittance, T1 represents the transmittance of the first array, T2 represents the transmittance of the second array, B1 represents the fourth data, B2 represents the fifth data, and B′1 represents the sixth data;

[0029] Alternatively, in the first aspect, the i-th first transformation parameter, the first transmittance, the transmittance of the first array, and the transmittance of the second array satisfy the following relationship: The first data, the second data, the third data, and the i-th first transformation parameter satisfy the following relationship: In the second aspect, the i-th second transformation parameter, the first transmittance, the transmittance of the first array, and the transmittance of the second array satisfy the following relationship: The first data, the second data, the third data, and the i-th second transformation parameter satisfy the following relationship: Wherein, η2 represents the i-th second transformation parameter, Teff represents the first transmittance, T1 represents the transmittance of the first array, T2 represents the transmittance of the second array, B1 represents the fourth data, B2 represents the fifth data, and B′2 represents the sixth data.

[0030] Thirdly, a method for quantum key distribution is provided, comprising: a first device sending k sets of quantum states to a second device through a quantum channel, the k sets of quantum states being associated with k arrays; the first device dividing the k arrays into m groups, where m is an integer greater than 1; the first device acquiring m first transformation parameters, the m first transformation parameters corresponding one-to-one with the m groups; the first device transforming the first data of the first array in the i-th group of the m groups and the second data of the second array in the i-th group according to the i-th first transformation parameter among the m first transformation parameters to obtain third data, the i-th first transformation parameter being determined based on a first transmittance and the transmittance of the first array and the second array, the i-th first transformation parameter corresponding to the i-th group, where i∈[1,m]; and the first device determining a security key based on the third data. In conjunction with the third aspect, in some implementations of the third aspect, the first device divides the k arrays into m groups, including: the first device obtaining the k transmittances of the k arrays; and the first device dividing the k arrays into m groups based on the k transmittances of the k arrays.

[0031] In conjunction with the third aspect, in some implementations of the third aspect, the method further includes: the first device determining a first transmittance based on the k transmittances of the k arrays, wherein the number of transmittances greater than the first transmittance and the number of transmittances less than the first transmittance are equal.

[0032] In conjunction with the third aspect, in some implementations of the third aspect, the method further includes: the first device determining a first transmittance based on the k transmittances of the k arrays, wherein the number of transmittances greater than the first transmittance is greater than the number of transmittances less than the first transmittance.

[0033] Combining the above implementation methods, let α be the number of transmittance values ​​greater than the first transmittance value among the k transmittance values, and β be the number of transmittance values ​​less than the first transmittance value, then α > β. In one possible solution, the first device discards α-β transmittance values ​​from the α arrays with transmittance values ​​greater than the first transmittance value, in which case k is greater than 2m; in another possible solution, the first device groups (or pairs) the α-β transmittance values ​​from the α arrays with transmittance values ​​greater than the first transmittance value with the vacuum state measurement results, in which case k is less than 2m.

[0034] In conjunction with the third aspect, in some implementations of the third aspect, the method further includes: the first device determining a first transmittance based on the k transmittances of the k arrays, wherein the number of transmittances greater than the first transmittance is less than the number of transmittances less than the first transmittance.

[0035] Combining the above implementation methods, let α be the number of transmittances greater than the first transmittance among the k transmittances, and β be the number of transmittances less than the first transmittance, then α < β. In one possible scheme, the first device discards β-α arrays of β transmittances less than the first transmittance, where k is greater than 2m; in another possible scheme, the first device saves β-α arrays of β transmittances less than the first transmittance, and these β-α arrays are used for data transformation in subsequent loop processes. In conjunction with the third aspect, in some implementations of the third aspect, the first transmittance is greater than or equal to the transmittance of one of the at least two arrays in the i-th group, and less than or equal to the transmittance of the other array. The i-th first transformation parameter, the first transmittance, the transmittance of the first array, and the transmittance of the second array satisfy the following relationship: Wherein, η1 represents the i-th first transformation parameter, Teff represents the first transmittance, T1 represents the transmittance of the first array, and T2 represents the transmittance of the second array.

[0036] In conjunction with the third aspect, in some implementations of the third aspect, the first data, the second data, the third data, and the i-th first transformation parameter satisfy the following relationship: Wherein, A1 represents the first data, A2 represents the second data, and A′1 represents the third data.

[0037] In conjunction with the third aspect, in some implementations of the third aspect, the first transmittance is greater than or equal to the transmittance of one of the at least two arrays in the i-th group, and less than or equal to the transmittance of the other array in the at least two arrays. The i-th first transformation parameter, the first transmittance, the transmittance of the first array, and the transmittance of the second array satisfy the following relationship: Wherein, η1 represents the i-th first transformation parameter, Teff represents the first transmittance, T1 represents the transmittance of the first array, and T2 represents the transmittance of the second array.

[0038] In conjunction with the third aspect, in some implementations of the third aspect, the first data, the second data, the third data, and the i-th first transformation parameter satisfy the following relationship: Wherein, A1 represents the first data, A2 represents the second data, A′2 represents the third data, and η1 represents the i-th first transformation parameter.

[0039] Fourthly, a quantum key distribution apparatus is provided, comprising: a transceiver module for transmitting k sets of quantum states to a second device via a quantum channel, the k sets of quantum states being associated with k arrays; a processing module for dividing p arrays of the k arrays into m groups, each of the m groups comprising at least two arrays, where m is an integer greater than 1, p is less than or equal to k, and p is greater than or equal to 2m; the processing module is further configured to acquire m first transformation parameters, the m first transformation parameters corresponding one-to-one with the m groups; the processing module is further configured to transform the first data of the first array in the i-th group of the m groups and the second data of the second array in the i-th group according to the i-th first transformation parameter in the m groups to obtain third data, the i-th first transformation parameter being determined based on a first transmittance and the transmittance of the first array and the second array, the i-th first transformation parameter corresponding to the i-th group, where i ∈ [1, m]; the processing module is further configured to determine a security key based on the third data.

[0040] In conjunction with the fourth aspect, in some implementations of the fourth aspect, the transceiver module is specifically used to: receive the m first transformation parameters from the second device; or, the processing module is specifically used to: determine the m first transformation parameters based on the first transmittance and the transmittance of at least two arrays of each of the m groups.

[0041] In conjunction with the fourth aspect, in some implementations of the fourth aspect, the processing module is specifically used to: obtain the k transmittances of the k arrays; divide the p arrays in the k arrays into m groups according to the k transmittances of the k arrays, wherein in each of the m groups, at least two arrays, one array has a transmittance greater than or equal to the first transmittance, and the other array has a transmittance less than or equal to the first transmittance.

[0042] In conjunction with the fourth aspect, in some implementations of the fourth aspect, the first transmittance is determined based on the k transmittances of the k arrays, and the absolute value of the difference between the number of transmittances greater than the first transmittance and the number of transmittances less than the first transmittance is less than a first threshold.

[0043] In conjunction with the fourth aspect, in some implementations of the fourth aspect, the first transmittance is greater than or equal to the transmittance of one of the at least two arrays in the i-th group, and less than or equal to the transmittance of the other array in the at least two arrays. The i-th first transformation parameter, the first transmittance, the transmittance of the first array, and the transmittance of the second array satisfy the following relationship: Wherein, η1 represents the i-th first transformation parameter, Teff represents the first transmittance, T1 represents the transmittance of the first array, and T2 represents the transmittance of the second array.

[0044] In conjunction with the fourth aspect, in some implementations of the fourth aspect, the first data, the second data, the third data, and the i-th first transformation parameter satisfy the following relationship: Wherein, A1 represents the first data, A2 represents the second data, A′1 represents the third data, and η1 represents the i-th first transformation parameter.

[0045] In conjunction with the fourth aspect, in some implementations of the fourth aspect, the first transmittance is greater than or equal to the transmittance of one of the at least two arrays in the i-th group, and less than or equal to the transmittance of the other array in the at least two arrays. The i-th first transformation parameter, the first transmittance, the transmittance of the first array, and the transmittance of the second array satisfy the following relationship: Wherein, η1 represents the i-th first transformation parameter, Teff represents the first transmittance, T1 represents the transmittance of the first array, and T2 represents the transmittance of the second array.

[0046] In conjunction with the fourth aspect, in some implementations of the fourth aspect, the first data, the second data, the third data, and the i-th first transformation parameter satisfy the following relationship: Wherein, A1 represents the first data, A2 represents the second data, A′2 represents the third data, and η1 represents the i-th first transformation parameter.

[0047] Fifthly, a quantum key distribution apparatus is provided, comprising: a transceiver module for receiving k sets of quantum states from a first device via a quantum channel, the k sets of quantum states being associated with k arrays; a processing module for dividing p arrays of the k arrays into m groups, each of the m groups comprising at least two arrays, where m is an integer greater than 1, p is less than or equal to k, and p is greater than or equal to 2m; the processing module is further configured to acquire m second transformation parameters, the m second transformation parameters corresponding one-to-one with the m groups; the processing module is further configured to transform the fourth data of the third array in the i-th group of the m groups and the fifth data of the fourth array in the i-th group according to the i-th second transformation parameter in the m groups to obtain a sixth data, the i-th second transformation parameter being determined based on a first transmittance and the transmittance of the third array and the fourth array, the i-th second transformation parameter corresponding to the i-th group, where i ∈ [1, m]; the processing module is further configured to determine a security key based on the sixth data.

[0048] In conjunction with the fifth aspect, in some implementations of the fifth aspect, the transceiver module is specifically used for: the second device receiving the m second transformation parameters from the first device; or, the processing module is specifically used for: determining the m second transformation parameters based on the first transmittance and the transmittance of at least two arrays of each of the m packets.

[0049] In conjunction with the fifth aspect, in some implementations of the fifth aspect, the processing module is specifically used to: obtain the k transmittances of the k arrays; divide the p arrays in the k arrays into m groups according to the k transmittances of the k arrays, wherein in each of the m groups, at least two arrays have a transmittance of one array greater than or equal to the first transmittance, and a transmittance of the other array less than or equal to the first transmittance.

[0050] In conjunction with the fifth aspect, in some implementations of the fourth aspect, the processing module is further configured to: the second device determine the first transmittance based on the k transmittances of the k arrays, wherein the absolute value of the difference between the number of transmittances greater than the first transmittance and the number of transmittances less than the first transmittance is less than or equal to a first threshold.

[0051] In conjunction with the fifth aspect, in some implementations of the fifth aspect, the first transmittance is greater than or equal to the transmittance of one of the at least two arrays in the i-th group, and less than or equal to the transmittance of the other array in the at least two arrays. The i-th second transformation parameter, the first transmittance, the transmittance of the first array, and the transmittance of the second array satisfy the following relationship: Wherein, η2 represents the i-th second transformation parameter, Teff represents the first transmittance, T1 represents the transmittance of the first array, and T2 represents the transmittance of the second array.

[0052] In conjunction with the fifth aspect, in some implementations of the fifth aspect, the first data, the second data, the third data, and the i-th second transformation parameter satisfy the following relationship: Wherein, B1 represents the fifth data, B2 represents the fifth data, B′1 represents the sixth data, and η2 represents the i-th second transformation parameter.

[0053] In conjunction with the fifth aspect, in some implementations of the fifth aspect, the first transmittance is greater than or equal to the transmittance of one of the at least two arrays in the i-th group, and less than or equal to the transmittance of the other array in the at least two arrays. The i-th second transformation parameter, the first transmittance, the transmittance of the first array, and the transmittance of the second array satisfy the following relationship: Wherein, η2 represents the i-th second transformation parameter, Teff represents the first transmittance, T1 represents the transmittance of the first array, and T2 represents the transmittance of the second array.

[0054] In conjunction with the fourth aspect, in some implementations of the fourth aspect, the first data, the second data, the third data, and the i-th second transformation parameter satisfy the following relationship: Wherein, B1 represents the fourth data, B2 represents the fifth data, B′2 represents the sixth data, and η2 represents the i-th second transformation parameter.

[0055] A sixth aspect provides an apparatus for quantum key distribution, including modules for performing various steps of the method as described in any one of the first to second aspects.

[0056] A seventh aspect provides a quantum key distribution apparatus, including at least one processor coupled to at least one memory, the at least one processor being configured to execute a computer program or instructions stored in the at least one memory to cause the communication apparatus to perform the method described in the first aspect or the second aspect.

[0057] Eighthly, a computer-readable storage medium is provided, on which a computer program is stored, which, when run on a computer, causes the computer to perform the method described in the first or second aspect.

[0058] Ninthly, a computer program product is provided, which includes computer program code that, when run on a computer, causes the method described in the first or second aspect to be executed.

[0059] In a tenth aspect, a chip system is provided, comprising: a processor for retrieving and running a computer program from a memory, causing a communication device equipped with the chip system to perform the method described in the first aspect or the second aspect. Attached Figure Description

[0060] Figure 1 This is an exemplary structural diagram of a system architecture applicable to embodiments of this application.

[0061] Figure 2 A schematic diagram of a unidirectional CV-QKD system.

[0062] Figure 3 This is an exemplary flowchart of a quantum key distribution method provided in an embodiment of this application.

[0063] Figure 4 This is an equivalent schematic diagram of a linear network provided in an embodiment of this application.

[0064] Figure 5 This is an equivalent schematic diagram of another linear network provided in the embodiments of this application.

[0065] Figure 6 This is an equivalent schematic diagram of another linear network provided in the embodiments of this application.

[0066] Figure 7 This is an equivalent schematic diagram of another linear network provided in the embodiments of this application.

[0067] Figure 8 This is an equivalent schematic diagram of another linear network provided in the embodiments of this application.

[0068] Figure 9 This is an exemplary flowchart of a quantum key distribution method provided in an embodiment of this application.

[0069] Figure 10 This is a schematic structural block diagram of a quantum key distribution device according to an embodiment of this application.

[0070] Figure 11 This is a schematic structural block diagram of a quantum key distribution device according to an embodiment of this application. Detailed Implementation

[0071] The technical solutions in this application will now be described with reference to the accompanying drawings.

[0072] Figure 1 This is an exemplary structural diagram of system architecture 100 applicable to embodiments of this application. System architecture 100 is a unidirectional CV-QKD system. The CV-QKD system includes two parts: hardware and data processing. The hardware part includes optical paths and circuits (optical modules and electrical modules) for generating, transmitting, receiving, and probing quantum signals. The hardware part can be considered as the part that completes the quantum process. The data processing part is responsible for processing the modulation data from the transmitter, the probe data from the receiver, evaluating security parameters, extracting the final security key, etc., and mainly operates in dedicated chips or general-purpose CPUs, GPUs, and other chips.

[0073] Figure 2 The system structure 200 shown is Figure 1 The diagram shows the system schematic of a unidirectional CV-QKD system. From... Figure 2 As can be seen, this CV-QKD system mainly includes a transmitter and a receiver, as well as channels 204 and 205 connecting the transmitter and receiver. Channel 204 is a quantum channel, and channel 205 is a classical channel. Both the transmitter and receiver entities are QKD terminals.

[0074] The transmitting end mainly includes three modules: a light source 201, a modulation module 202, and a post-processing module 203; the receiving end mainly includes four modules: a demodulation module 206, a detection module 207, a sampling module 208, and a post-processing module 209. The two post-processing modules at the transmitting and receiving ends communicate bidirectionally via a classical channel (channel 205) to complete each post-processing step.

[0075] After the electrical signal output by the balanced receiver is acquired by the receiving end, the initial data obtained through various data processing methods is usually called the raw key. Further post-processing is required to obtain the final secure key from the raw key. These post-processing steps typically include: measurement basis alignment and data filtering (sifting), parameter estimation (PE), error correction (EC), and privacy amplification (PA). Additionally, a secure message authentication step is also required in classic communication modules.

[0076] In the modulation module, there are various modulation methods depending on the protocol, the most common being Gaussian modulation and quadrature phase shift keying (QPSK) modulation. There are also various modulators to implement these modulation methods. For example, a cascaded phase modulator and intensity modulator can be used to prepare arbitrary coherent states in phase space through phase and intensity modulation; alternatively, an in-phase quadrature (IQ) modulator or a dual polarization-quadrature phase shift keying (DP-QPSK) modulator can be used to prepare arbitrary coherent states in one or two polarization directions.

[0077] When evaluating a CV-QKD system, two main aspects are considered: First, whether the system possesses complete security proofs; and second, the system's performance. System performance primarily includes the secure key generation rate over a given distance. The secure key generation rate represents the total number of bits of the effective shared key obtainable by both communicating parties per unit time, reflecting the efficiency of key distribution. This secure key generation rate can also be referred to as key rate, secure code rate, or generation rate; for convenience, it will be referred to as secure code rate below. System performance is affected by several factors, primarily: 1) internal system noise, such as modulation noise at the transmitter and detector noise at the receiver; 2) channel-introduced noise, such as background light noise in the channel; and 3) performance degradation caused by system instability, such as performance degradation due to excessively rapid polarization rotation of the signal in the channel causing the calibration module to lag behind, or a decrease in the secure code rate due to excessively rapid or large changes in channel attenuation. For CV-QKD systems, large and rapid changes in channel transmittance severely impact system performance, especially the secure code rate. For example, in space channels, the optical power received by the receiver varies randomly due to turbulence, atmospheric scintillation, and equipment movement. Similarly, in overhead optical cable conditions, rapid polarization rotation may delay correction, ultimately altering the signal energy coupled to the receiver. These channel power variations are treated as additional noise in the secure bit rate assessment mechanism, thus causing a decrease in the secure bit rate. A brief explanation of this issue follows.

[0078] In the security analysis of CV-QKD, the covariance matrix is ​​generally used to evaluate the security code rate of the system. A typical format of the covariance matrix is ​​as follows:

[0079]

[0080] Where T represents the channel's equivalent transmittance and ε represents the equivalent noise.

[0081] It should be noted that the above expression is only a typical form of covariance matrix, mostly used to calculate equivalent parameters. These equivalent parameters can be used to intuitively understand the system's security bitrate. In a real system, the covariance matrix should be derived from the statistical data of both the sender and receiver. The security bitrate can be directly calculated from the statistically derived covariance matrix, without necessarily requiring equivalent parameters.

[0082] It should also be noted that the reason for using the concept of equivalence is that the real system is quite complex, and a single statistical matrix (the covariance matrix is ​​a second-order statistic) cannot reflect every aspect of the channel. Therefore, the T and ε mentioned above are a kind of "guess" based on statistical results to infer the channel situation, and are equivalent concepts under a certain fixed expression format.

[0083] When the channel is a simple attenuation plus Gaussian white noise channel, the concepts of physical attenuation and noise of the channel can be precisely matched with the equivalent concepts mentioned above. Therefore, this equivalent concept allows people to intuitively perceive the "quality" of the channel, that is, to qualitatively judge the secure code generation rate of the system. For example, under the same equivalent noise conditions, the greater the equivalent transmittance, the "smaller" the attenuation of the channel can be considered, and therefore the higher the code generation rate of the system; similarly, under the same equivalent transmittance conditions, the smaller the equivalent noise, the higher the code generation rate of the system.

[0084] Assuming the protocol stipulates that a covariance matrix is ​​calculated (or a secure bitrate is calculated) only after accumulating enough data for a length of L periods, the data for L periods is divided into m parts, each part consisting of data for N periods, i.e., L = m × N. Each set of data for N periods can be called a group, and the m groups together constitute all the data needed for a covariance matrix calculation.

[0085] When the channel transmittance fluctuates rapidly, the transmittance experienced by each of the m packets will be different. Assume that the channel transmittance and noise experienced by the j-th packet are T... j and ε j By statistically analyzing the channel transmittance of all m packets, a probability distribution can be obtained. Assume the channel transmittance of a packet is T. i The probability is p i The transmittance of all channels is T i The groups form a whole, and its equivalent noise is denoted as ε. j Then the covariance matrix at this time will be expressed as:

[0086]

[0087] If strictly distinguishing T i Then it becomes difficult to obtain two groups with strictly equal transmittance. One interpretation is that two transmittance values ​​with small differences can be considered as the same value for statistical analysis. Another interpretation is that if no probability statistical distinction is made, and the covariance matrix is ​​calculated only using the parameters of each group, it is equivalent to... At this point, the equivalent channel transmittance T eff for:

[0088]

[0089] Equivalent noise ε eff for:

[0090]

[0091] It is not difficult to see that, due to ε eff There will be a significant increase. The larger the channel transmittance fluctuation range, the more T eff and The greater the difference, the greater the increase in equivalent noise, the worse the system performance, and even the inability to securely code.

[0092] T eff and Different phenomena can be called "disorder".

[0093] The problem of decreased secure code rate due to channel fluctuations is mainly caused by significant changes in channel transmittance within a short period. Therefore, the impact of channel transmittance changes on secure code rate can be reduced by limiting channel variations.

[0094] One approach is to reduce channel transmittance variation by discarding data packets whose transmittance deviates from a preset value.

[0095] Assuming the protocol stipulates that a covariance matrix calculation (or a secure bit rate calculation) is only performed after accumulating L periods of data, the L periods of data are divided into m parts, each containing N periods of data (L = m × N). Each N periods of data can be called a group, and these m groups constitute all the data needed for a single covariance matrix calculation. For each of these m groups, the channel transmittance Ti is calculated. When the channel transmittance fluctuates rapidly, Ti for the m groups changes continuously.

[0096] When the transmittance Ti of a certain data group deviates too much from the predetermined channel attenuation value, the data of that group is discarded. It should be noted that the predetermined channel attenuation value can be a threshold or a numerical range, and it can be set in various ways, such as using predicted values ​​or previous statistical values. Therefore, the data groups that are not discarded can be understood as those whose transmittance is within the preset range. When a sufficient length L of data is accumulated, the transmittance Ti of each group within that L-length of data will not differ significantly, and the additional increase in equivalent noise is controlled.

[0097] However, effectively controlling the magnitude of the additional equivalent noise requires the equivalent attenuation to be significantly smaller than the average attenuation, for example, the deviation should not exceed 0.5%, which would result in discarding a large amount of data. Furthermore, it is uncertain how long it will take to accumulate data of length L.

[0098] Another approach is to divide the data into different groups based on transmittance, grouping data from groups with similar transmittance together into a larger group, thus minimizing the fluctuation in channel transmittance within each larger group.

[0099] Assuming the protocol stipulates that a covariance matrix is ​​only calculated once after accumulating enough data for a length of L periods, the data for L periods is divided into m parts, each part consisting of data for N periods, i.e., L = m × N. Each set of data for N periods is called a group. Then, the m groups together constitute all the data needed for a single covariance matrix calculation.

[0100] For each N-cycle data group, the transmittance Ti is calculated, and the calculation is performed for a sufficiently long time (the calculation time exceeds the transmission time of L cycles of data, or the number of groups counted exceeds m groups).

[0101] Data with similar or identical data points Ti (a small range can be set) are grouped into a large group. If the length of data within a large group reaches L, the covariance matrix of the data within that large group is statistically analyzed, and the data proceeds to the post-processing stage to extract the security code. For large groups with a length less than L, the data is accumulated until it reaches a length of L before proceeding to the next step.

[0102] This approach does not require discarding data, but it does require storing a large amount of data. It requires accumulating data separately for different Ti (or different transmittance ranges), which will result in a significant waste of resources.

[0103] In view of this, embodiments of this application provide a method and apparatus for quantum key distribution, which can reduce the impact of channel transmittance variations in CV-QKD systems on the security code rate, while also reducing discarded data and wasted resources.

[0104] Figure 3 An exemplary flowchart of a quantum key distribution method 300 provided in an embodiment of this application is shown. It should be noted that method 300 includes:

[0105] S301, the first device sends k sets of quantum states to the second device, which are associated with k arrays.

[0106] For example, the first device generates k arrays #1 (e.g., k sets of random numbers), prepares quantum states based on these k arrays #1, obtains k sets of quantum states, and sends these k sets of quantum states to the second device. Correspondingly, the second device performs quantum state detection and records the detection results.

[0107] The first device can be considered the transmitting device in the quantum key distribution process, and the second device can be considered the receiving device. The first and second devices perform quantum data extraction respectively. For example, for the first device, the k arrays #1 initially generated by the first device enter the quantum data extraction module, which is used to output the k arrays #1 of the first device. For the first device, the quantum data extraction module is usually mapped from the k arrays #1 of the first device, or combined with some data filtering. It should be understood that the k arrays #1 are key sequences directly composed of the detection results, or the k arrays #1 can also be k sets of random numbers, without post-processing steps. For the second device, its data extraction module is generally more complex, mainly because the quantum signal has undergone channel phase drift, polarization drift, changes in the receiving local oscillator frequency, and sampling frequency differences, making the direct output of the detector not the expected quantum measurement result. At this time, the receiving end needs to process the original measurement data, such as clock recovery, phase recovery, filtering, etc., to extract the corresponding measurement results of the quantum signal and form the receiver's initial key data, i.e., the k arrays #2. The k arrays #1 are arrays associated with the k quantum states on the first device side, and the k arrays #2 are arrays associated with the k quantum states on the second device side. The k arrays #1 and k arrays #2 are in one-to-one correspondence. In other words, the k arrays #1 are the transmitting data, and the k arrays #2 are the receiving data corresponding to the transmitting data.

[0108] It should be understood that in some implementations, the second device requires a set of random numbers to assist in quantum state detection. Optionally, the second device can generate a set of random numbers for use in the subsequent quantum detection process before performing quantum state detection.

[0109] It should be noted that since channel transmittance changes over time, the channel transmittance experienced by each of these k arrays is almost different, which is the cause of "misalignment". Therefore, this application provides a data transformation method to avoid or mitigate the impact of channel transmittance on the secure code rate. In this method, we set a target equivalent transmittance, denoted as Teff, and then have the first device perform data transformation on the k arrays #1 and the second device perform data transformation on the k arrays #2, so that the equivalent transmittance between a portion of the data in the k arrays #1 and a portion of the data in the k arrays #2 after transformation is equal to Teff (or the absolute value of the difference between Teff and the equivalent transmittance is less than or equal to a set threshold). Thus, the "misalignment" is eliminated for this portion of data, which can be used in subsequent processing, while the remaining data can be discarded.

[0110] The following describes a possible transformation model for data transformation.

[0111] In practical systems, the secure code rate is usually calculated using the covariance matrix, which is obtained by statistically averaging the measurement results. From the perspective of entanglement equivalence protocols, statistical averaging can be viewed as a linear network (LN) that "uniformly" mixes quantum states of different periods together.

[0112] Figure 4 This is a schematic diagram of the equivalent of a linear network. Figure 4 In the diagram, LN1 and LN2 represent two different linear networks, A1 to A... N Representing the data transmitted from the sender within different periods, B1 to B N Representing the received data within different periods, B1 to B N With A1 to A N Each corresponds to one another.

[0113] A′1 to A′ N Representing A1 to A N The data after LN1 transformation satisfies the following relationship:

[0114]

[0115] B′1 to B′ N Representing B1 to B N The data after LN2 transformation satisfies the following relationship:

[0116]

[0117] The statistical average of equal rights can be seen as...

[0118] By comparing the covariance and variance terms of A′1 and B′1 after the linear transformation, it is not difficult to obtain:

[0119]

[0120] When η ij ≠ζ ij At that time, That is, when the two linear transformations are different, the channel transmittance perceived by different arrays will be different, which results in "misalignment"; while when η ij =ζ ij hour, At this point, the channel transmittance perceived by different arrays is the same.

[0121] Examining the CV-QKD protocol under the entanglement equivalence protocol, the weighted average of the statistical covariances can be viewed as LN1 = LN2, both being equally distributed. However, since each dual-mode entangled state experiences different channel transmittances after entering the channel, it is equivalent to performing an additional transformation N_B. i ,like Figure 5 As shown (for ease of explanation, Figure 5 (Considering only the effect of channel attenuation).

[0122] exist Figure 5 In the model shown, it is assumed that each set of data includes N arrays. Therefore, in this model, the first device prepares N bi-mode entangled states: ρ A1B01 ,ρ A2B02 , ..., ρ ANB0N The first device will A1~A N Retain, and keep pattern B 01 ~B 0N The data is transmitted into the channel. In this model, each entangled state corresponds to an array, and their transmittance through the channel varies. For example, if the system transmits quantum states at a repetition frequency of 1 GHz, the first device generates data at a corresponding rate, and the second device generates and records the detection results at a corresponding rate. Therefore, the first device will transmit 10 quantum states per second. 9 A quantum state. Assume now according to 10 6 If the size is grouped according to the time series, the data within 1 second can be divided into 1000 arrays. Therefore, each array contains 10... 6 A quantum state is equivalent to entangled state ρ AiB0i Repeat preparation 10 6 Next. B 01 ~B 0N After the monitoring operation in the channel (the monitoring operation here is only one example, and it may also be a joint operation between multiple modes), it reaches the second device, denoted as mode B1 to B. N Before the data transformation, the first device retained patterns A1 to A1. N The measurement is performed, and the result can be recorded as R. A ={x A1 p A1 x A2 p A2 , ..., x 4N p AN The second device receives modes B1 to B. N The measurement is performed, and the result can be recorded as R. B ={x B1 p B1 x B2 p B2 , ..., x BNp BN}

[0123] In the embodiments of this application, a data transformation process is added. In the entanglement protocol model, before the first and second devices perform measurements, they first confirm two sets of transformation parameters, thereby constructing two unitary transformations, LN1 and LN2. The specific unitary transformation can take many forms; here, we will use LN1 and LN2 as linear optical transformations as an example for explanation. The first device uses LN1 to transform modes A1 to A... N The transformation yields patterns A′1 to A′. N The second device uses LN2 for modes B1 to B. N • Perform transformations to obtain patterns B′1~B′ N Then the first device operates on A′1 to A′... N The measurement is performed, and the result can be recorded as R. A′ ={x A1 p A1 x A2′ p A2′ , ..., x AN′ p AN′}; The second device is for B′1~B′ N The measurement is performed, and the result can be recorded as R. B′ ={x B1 p B1 x B2′ p B2′ , ..., x BN′ p BN′}

[0124] exist Figure 5 In the transformation model shown, N_B i The other input Ei (i∈[1,N]) of (i∈[1,N]) represents other quantum states in the channel, such as quantum states introduced by the monitor or environmental noise. At this point, each N_B i Combining LN2 and LN2, we arrive at a new linear transformation LN2'. At this point, even considering only the terms related to the AB mode, LN2' and LN1 are no longer equal. One solution is to choose different LN1 and LN2 values ​​so that LN1 and LN2' exhibit the same attenuation effect in some modes. This ensures that A'... i With B′ i The transmittance perceived by the covariance and variance are the same or approximately equal.

[0125] The following is combined with Figure 6 This section introduces a specific transformation method. Figure 6In the equivalent transformation diagram shown, N=2, M=1, meaning there are only two entangled states. Only one of the entangled states is guaranteed to achieve the equivalent transmittance Teff in the transformed channel. LN1 and LN2 are chosen as two-port beamsplitter models, with the beamsplitter transmittance parameter of LN1 set to η2 and the beamsplitter transmittance parameter of LN2 set to η2. The transformation relationship of the regularized components between modes A1, A2, B1, B2 and A′1, A′2, B′1, B′2 is as follows:

[0126]

[0127] Where A1 represents the regular expression component of pattern A1. or A2 represents the regular expression component of pattern A2. or B1 represents the regular component of pattern B1. or B2 represents the regular component of pattern B2. or This also illustrates the transformation relationship between Gaussian measurement (such as heterodyne detection) data.

[0128] Combining the channel model, we can obtain:

[0129]

[0130] Therefore, we get:

[0131]

[0132] In one implementation, we require that the channel transmittance corresponding to the transformed modes A′2 and B′2 is the equivalent transmittance Teff. Under this condition, the statistical covariance and variance of B′2 and A′2 are calculated as follows:

[0133]

[0134] <B′2 2 >=[η2T2+(1-η2)T1]V+[η2(1-T2)V E1 +(1-η2)(1-T1)V E2 ]

[0135] At this point, the requirement is:

[0136]

[0137] T eff =η2T2+(1-η2)T1∈[T1, T2]

[0138] Then we can deduce that:

[0139]

[0140] <B′2 2 ) = T eff (V-1+ε eff )+1

[0141] (1-η1)η2T2=η1(1-η2)T1

[0142] The transformation parameters can then be determined:

[0143]

[0144] Regarding the parameter determination method described above, we will provide additional explanation for a special case. For example, consider the case where T1 = 0, meaning the channel corresponding to the first entangled state does not transmit any quantum state at all, or although the second device receives the quantum state after it has passed through the channel, it artificially sets it to "zero," i.e., treats it only as a vacuum state. In this case, η1 = 1, which is equivalent to not changing A2 at the transmitting end, while at the receiving end, B2 and a vacuum state are split. Since the vacuum state is not actually associated with any other mode, it could be that the first entangled state was not sent to the receiver (i.e., the second device), the second device intentionally replaced the received quantum state with a vacuum state, or the second device directly virtually generated an additional vacuum state locally to participate in the mode transformation.

[0145] Another implementation requires that the channel transmittance corresponding to the transformed A′1 and B′1 modes is the equivalent transmittance Teff. Under this condition, the statistical covariance and variance of B′1 and A′1 are calculated as follows:

[0146]

[0147] At this point, the requirement is:

[0148]

[0149] T eff =η2T1+(1-η2)T2∈[T1, T2]

[0150] (1-η1)η2T1=η1(1-η2)T2

[0151] Therefore, the transformation parameters can be determined as follows:

[0152]

[0153] In CVQKD, we use Gaussian measurements, so the linear transformation can be interchanged with the measurement, i.e., the measurement result R... A and R A′The data transformation relationship between them is related to the linear transformation LN1, i.e., R A′ =Z LN1 R A Similarly, we have R. B′ =Z LN2 R B .

[0154] Based on this, the following is combined with Figure 7 Introducing another data transformation model.

[0155] exist Figure 7 In the model shown, it is assumed that each set of data includes N arrays, that is, the first device in this model prepares N dual-mode entangled states: ρ A1B11 , ρ A2B12 , ..., ρ ANB1N The first device will A1~A N Retain, and keep pattern B 11 ~B 1N After performing a linear optical transformation LN1, mode B is formed. 01 ~B 0N and will pattern B 01 ~B 0N Send into channel. B 01 ~B 0N After the monitoring operation in the channel (the monitoring operation here is only one example, and it may also be a joint operation between multiple modes), it reaches the second device, denoted as mode B1 to B. N .

[0156] In this model, LN 1 occurs before the quantum state enters the channel and, in principle, cannot be adjusted based on channel parameters. However, considering the arbitrariness of the entanglement equivalence protocol—that is, the actual device inside the first device is invisible to the outside world—there are multiple equivalent implementation methods. Therefore, as long as the B transmitted into the channel is maintained... 01 ~B 0N Since LN 1 remains unchanged, it can actually be virtual and therefore can be remodeled and determined based on the equivalent channel transmittance of each group.

[0157] The following is combined with Figure 8 Another specific transformation method is introduced. We choose the case where N=2 and M=1, meaning there are only two entangled states, and only one of them is guaranteed to achieve the equivalent transmittance Teff in the transformed channel. LN1 and LN2 are chosen as two-port beamsplitter models, where the beamsplitter transmittance parameter of LN1 is set to η1, and the beamsplitter transmittance parameter of LN2 is set to η2. Then, in mode B... 11 B 12 B1, B2 and B 01 B 02The transformation relationship between the regular components of B′1 and B′2 is as follows:

[0158]

[0159] Among them, B 11 Representing B 11 Regular component operators of a pattern or B 12 Representing B 12 Regular component operators of a pattern or B1 represents the regular component of the B1 pattern. or B2 represents the regular component of the B2 pattern. or This also illustrates the transformation relationship between Gaussian measurement (such as heterodyne detection) data.

[0160] Combining the channel model, we can obtain:

[0161]

[0162] Therefore, we get:

[0163]

[0164] Furthermore:

[0165]

[0166] One implementation requires that the channel transmittance corresponding to the transformed A′1 and B′1 modes is the equivalent transmittance Teff. This requires:

[0167]

[0168] at this time,

[0169]

[0170] The transformation parameters can be derived as follows:

[0171]

[0172] Another implementation requires that the channel transmittance corresponding to the transformed A′2 and B′2 modes is the equivalent transmittance Teff. This requires:

[0173]

[0174] at this time,

[0175]

[0176] The transformation parameters can be derived as follows:

[0177]

[0178] It should be understood that any linear transformation can be simulated using a beam splitter network combined with phase shifting, a common approach in the field of optical quantum information processing. Therefore, transformation is also feasible for cases where N>2, and the number of arrays whose "misalignment" is eliminated after the transformation increases with N, thereby improving overall efficiency. Therefore, in specific applications, the embodiments of this application can select N according to the actual situation to balance computational complexity and overall efficiency.

[0179] by Figure 7 The model shown is used as an example for illustration:

[0180] Suppose that the unitary transforms of LN1 and LN2 with respect to N modes are denoted as U. LN1 and U LN2 The symplectic transformation matrices corresponding to the 2N regular components are denoted as S. LN1 and S LN2 .

[0181] Taking LN1 as an example, the 2N regularized components of the B01 to B0N modes With the 2N regularized components of pattern B11 to B1N The following conditions must be met:

[0182]

[0183] S LN1 There are a total of 4N 2 The parameters can be denoted as:

[0184]

[0185] Where W = 2N. As a symplectic transformation, it satisfies the following constraints:

[0186]

[0187] Where Ω is the following block matrix:

[0188]

[0189] I N It is an N×N identity matrix. The case of LN2 is similar and will not be described further.

[0190] If we only consider the individual impact of the monitor's monitoring on a certain mode Ai in the channel, the matrix corresponding to the monitoring operation can be simplified as the following block diagonal matrix:

[0191]

[0192] At this point, patterns B′1~B′ can be derived. N 2N regular components and The relationship between them is:

[0193]

[0194] Transformation: T ch =S LN2 T Eve S LN1 Assuming the misalignment of the first M modes is eliminated (any M modes can be adjusted to the first M modes by changing their positions), meaning the equivalent channel transmittance of these M modes is Teff, and we also want to minimize the additional noise, so T... ch It should have the following form:

[0195]

[0196] Among them, Z M,N-M E represents an M*NM matrix consisting entirely of zeros. N-M，M E represents any (NM)*M matrix. N-M，N-M Let S represent any matrix of (NM)*(NM). This gives S LN1 and S LN2 Given certain constraints, S satisfies both these constraints and the constraints of the symplectic transformation matrix itself. LN1 and S LN2 , which is the linear transformation matrix to be solved by the sender and receiver. Under certain conditions, M can take a maximum value of N-1.

[0197] The following section, in conjunction with S302 to S307, provides an exemplary description of a data transformation scheme utilizing the aforementioned data transformation model:

[0198] S302, the first device divides p arrays in k arrays #1 into m groups.

[0199] For example, the first device divides p arrays from the k arrays #1 into m groups #1, where each of the m groups #1 includes at least two arrays #1, m is an integer greater than 1, p is less than or equal to k, and p is greater than or equal to 2m. When p equals k, it means that the first device divides all arrays from the k arrays #1 into m groups #1; when p is less than k, the first device divides a portion of the arrays from the k arrays #1 into m groups #1.

[0200] S303, the second device divides p arrays in k arrays #2 into m groups.

[0201] For example, the second device divides p arrays from k arrays #2 into m groups #2, where each of the m groups #2 includes at least two arrays #2, m is an integer greater than 1, p is less than or equal to k, and k is greater than or equal to 2m. When p equals k, it means that the second device divides all arrays from k arrays #1 into m groups #1; when p is less than k, the second device divides a portion of the arrays from k arrays #1 into m groups #1.

[0202] It should be noted that the grouping method (or grouping rule) for the first and second devices is the same, that is, m groups #2 correspond to m groups #1. The following example uses the first device to illustrate one grouping method:

[0203] The first device acquires k transmittance values ​​from k arrays #1, or in other words, acquires k transmittance values ​​between k arrays #1 and k arrays #2. The first device can determine these k transmittance values ​​itself or receive them from the second device; this application does not limit this. This application does not limit the specific implementation method for determining these k transmittance values. For example, the transmittance values ​​of different arrays can be obtained by cross-correlation of the sender's data and the receiver's data. Specifically, the first device can estimate the transmittance of each array using random sampling. For example, the second device randomly selects a portion of data from each array and publishes it to the first device, then the first device can obtain an estimated value of the channel transmittance by comparing it with the measured data. This randomly sampled data needs to be discarded because it is publicly available. For example, the transmittance of the k arrays #1 can be estimated using pilot signals. Specifically, in each cycle, at a frequency outside the quantum signal frequency, the first device sends a pilot optical signal to the second device. This optical signal can adopt certain agreed-upon modulation methods. The second device can directly estimate the channel transmittance of the array based on the detection results, and then send the estimated channel transmittance to the first device. The first device then divides the p arrays in the k arrays #1 into m groups based on the k transmittances of the k arrays. Specifically, for example, the first device determines a first transmittance based on the k transmittances of the k arrays. This first transmittance can correspond to the equivalent transmittance Teff in the above model. This first transmittance can be manually set, and its value has a certain degree of selectivity. Generally, the first transmittance is between the maximum and minimum values ​​of the k transmittances of the k arrays #1. Preferably, the absolute value of the difference d between the number of transmittances greater than and less than the first transmittance is less than or equal to a first threshold. The first device divides multiple arrays in the k arrays into m groups based on the first transmittance and the k transmittances, such that the m groups include at least two arrays, and the transmittance of one array is greater than or equal to the first transmittance, while the transmittance of the other array is less than or equal to the first transmittance.

[0204] Let α be the number of transmittance values ​​greater than the first transmittance value among the k transmittance values ​​of array #1, and β be the number of transmittance values ​​less than the first transmittance value. Therefore, k = α + β.

[0205] In one scenario, when the difference d is greater than 0 (i.e., α > β), following the grouping method described above, there will be (α-β) arrays that cannot be grouped, and the transmittance of these (α-β) arrays is greater than the first transmittance. In this case, dividing p arrays from k arrays #1 into m groups can be equivalent to dividing β arrays from k arrays #1 into m groups, where p can be equal to β, and k is greater than p. For the remaining (α-β) arrays from these k arrays, one approach is for the first device to discard them; another approach is for the first device to group (or pair) these (α-β) arrays with the (α-β) groups of vacuum state measurement results. Here, the vacuum state measurement results can be considered as "virtual" channels with a transmittance of 0.

[0206] In another scenario, when the difference d is less than 0 and α < β, following the grouping method described above, there will be (β-α) arrays that cannot be grouped, and the transmittance of these (β-α) arrays is less than the first transmittance. In this case, dividing p arrays from k arrays #1 into m groups can be equivalent to dividing α arrays from k arrays #1 into m groups, where p can be equal to α, and k is greater than p. For the remaining (β-α) arrays from these k arrays, one approach is for the first device to discard them; another approach is for the first device to save these (β-α) arrays and perform secondary matching with other arrays in subsequent loops, i.e., grouping them together with other arrays in other loops.

[0207] In another case, when the difference d equals 0, i.e. α = β, all arrays can be grouped using the grouping method described above. In this case, there is no need to discard any arrays, and p equals k. This approach can save resources and improve efficiency.

[0208] S304, the first device acquires m first transformation parameters, which correspond one-to-one with m groups #1.

[0209] Here, m first transformation parameters are used by the first device to transform data in m groups #1. One possible implementation is that the first device receives these m first transformation parameters from a second device; another possible implementation is that the m first transformation parameters are determined based on a first transmittance and the transmittance of at least two arrays in each of the m groups #1. The first transmittance is between the maximum and minimum values ​​of the k transmittances in the k arrays; preferably, the absolute value of the difference between the number of transmittances greater than and less than the first transmittance is less than or equal to a first threshold, which can be any number greater than or equal to 0. It should be understood that the smaller the first threshold, the fewer arrays that cannot be paired, and the less data needs to be discarded; that is, the smaller the first threshold, the better. Therefore, the most preferred situation is that when k is even, the number of transmittances greater than and less than the first transmittance is exactly equal; when k is odd, the difference between the number of transmittances greater than and less than the first transmittance is 1.

[0210] S305, the second device acquires m second transformation parameters, which correspond one-to-one with m groups #2.

[0211] The m second transformation parameters here are used by the second device to perform data transformation on the m packets #2. Similarly, the second device may receive the m first transformation parameters from the first device, or it may determine the m first transformation parameters based on the first transmittance and the transmittance of at least two arrays of each packet #2.

[0212] The following explanation uses the calculation of the i-th first transformation parameter and the second transformation parameter corresponding to the i-th group out of m groups as an example. The i-th first transformation parameter can be determined based on the first transmittance and the transmittance of the first array and the second array, and the i-th second transformation parameter can be determined based on the first transmittance and the transmittance of the third array and the fourth array. Here, the first array and the second array are two arrays in the i-th group on the first device side, and the third array and the fourth array are two arrays in the i-th group on the second device side.

[0213] In one case (denoted as Case 1), when the first transmittance is greater than or equal to the transmittance of one of the at least two arrays in the i-th group of m groups, and less than or equal to the transmittance of the other array (i∈[1,m]), the first device and the second device can determine the i-th first transformation parameter and the i-th second transformation parameter respectively using the following formulas:

[0214]

[0215] Wherein, η1 represents the i-th first transformation parameter, η2 represents the i-th second transformation parameter, Teff represents the first transmittance, T1 represents the transmittance of the first array, and T2 represents the transmittance of the second array.

[0216] In another case (denoted as Case 2), when the first transmittance is greater than or equal to the transmittance of one of the at least two arrays in the i-th group of m groups, and less than or equal to the transmittance of the other array (i∈[1,m]), the first device and the second device can determine the i-th first transformation parameter and the i-th second transformation parameter respectively using the following formulas:

[0217]

[0218] S306, the first device transforms the first data of the first array in the first group of the m groups and the second data of the second array in the second group according to the i-th first transformation parameter among the m first transformation parameters to obtain the third data.

[0219] S307, the second device transforms the fourth data of the third array in the i-th group of the m groups and the fifth data of the fourth array in the i-th group according to the i-th second transformation parameter in the m groups to obtain the sixth data;

[0220] For example, in case 1 above, the first device and the second device can calculate the third data and the sixth data respectively using the following formulas:

[0221]

[0222] Wherein, A1 represents the first data, A2 represents the second data, A′1 represents the third data, B1 represents the fourth data, B2 represents the fifth data, B′1 represents the sixth data, η1 represents the i-th first transformation parameter, and η2 represents the i-th second transformation parameter.

[0223] For example, in case 2 above, the first device and the second device can calculate the third data and the sixth data respectively using the following formulas:

[0224]

[0225] Wherein, A1 represents the first data, A2 represents the second data, A′2 represents the third data, η1 represents the i-th first transformation parameter, B1 represents the fourth data, B2 represents the fifth data, and B′2 represents the sixth data.

[0226] Furthermore, the data from the first and second devices, after data transformation, enter the post-processing module and, through the post-processing procedure, output the final security key. The post-processing procedure may include, for example, the following steps:

[0227] The first device makes the judgment.

[0228] This step primarily involves parameter estimation. The transmitter uses the estimated key parameters to determine whether to continue the protocol or terminate the current loop and proceed to the next. For example, if the estimated channel noise is higher than a set threshold, the current loop terminates; if it is lower, the remaining steps of the current loop continue. After parameter estimation, the secure code rate can be calculated.

[0229] It should be understood that this application does not limit the method of judgment. For example, the threshold comparison can be performed by classifying the data into several equivalent parameters; or, equivalent excess noise can be compared; or, the statistical results of the covariance matrix can be directly compared.

[0230] The first device extracts the security key.

[0231] For example, if the sending end determines in S3 10 to continue with the remaining steps of the current loop, it can extract the security key. Security key extraction mainly includes steps such as error correction and security enhancement. After the security key extraction steps, the final security key can be output.

[0232] The second device makes the judgment.

[0233] The second device extracts the security key.

[0234] The specific process is similar to that of the first device, and will not be repeated here.

[0235] It should be noted that method 300 is a process within a single loop. Within this loop, the initial key data is transformed so that the transmittance of the transformed key data is within the Teff error range. Then, in the next loop, a similar data transformation is performed to ensure that the transmittance of the transformed key data is also within the Teff error range. This process is repeated multiple times until a data length of L is accumulated. This L-length data is the length of the data used to calculate the covariance matrix. Since this L-length data consists of the transformed data, its transmittance is always within the Teff error range.

[0236] When the number of arrays above and below Teff differs between different loops, they can be handled in different ways. For example, if the number of arrays above Teff is greater than the number of arrays below Teff, taking a transformation with N=2 and M=1 as an example, some arrays above Teff will not have matching arrays below Teff. In this case, these unmatched arrays can be discarded. Alternatively, the same number of vacuum state measurement results can be added, treating them as a "virtual" channel with 0 transmittance, and the transformation can still be performed using the above method. When the number of arrays above Teff is less than the number of arrays below Teff, some arrays below Teff will not be matched. These arrays can be discarded. Optionally, all arrays to be discarded can be temporarily stored and paired a second time with arrays in subsequent loops. If there are still unmatched arrays, they can still be stored and paired again with arrays in subsequent loops. For general systems, such back-and-forth fluctuations do not cause much memory consumption.

[0237] Therefore, the quantum key distribution method provided in this application can avoid the impact of changes in channel transmittance on the secure code rate. At the same time, it reduces the number of data packets, lowers the requirements for system storage capacity and parallel processing capabilities, and reduces the uncertainty caused by changes in channel attenuation.

[0238] Figure 9 A schematic flowchart of methods 400 and 500 provided in embodiments of this application is shown. Figure 9 As can be seen from (a), method 400 includes:

[0239] S401, the transmitting end sends 2m×N coherent states {|α} to the receiving end. A >}.

[0240] S402, the receiver acquires the quantum measurement results.

[0241] Suppose that within one period, the sending end generates two random numbers x. A and p A This determines the mean parameter α of a coherent state. A The sending end will transmit the coherent state {|α A The quantum state is transmitted to the receiving end via a quantum channel. Upon receiving the quantum state, the receiving end performs a heterodyne measurement to obtain the measurement result x. B and p B .

[0242] Here, we assume that N cycles form an array, and 2m arrays form a post-processing cycle. In a post-processing cycle, there are a total of 2m×N cycles.

[0243] For 2m×N cycles, the transmitting end generates 2m×N pairs of random numbers (i.e., 2m×N pairs of x). A and p A ), denoted as And based on this, 2m×N coherent states {|α A The quantum state is sent to the receiving end. Upon receiving the quantum state, the receiving end performs quantum measurements, obtaining 2m×N pairs of measurement results, denoted as... It should be noted that if the receiver is performing heterodyne detection, both x and p will have data; if the receiver is performing zero-difference detection, only one valid data will be obtained for each measurement, and the other data can be recorded as invalid and will not participate in subsequent processes.

[0244] Furthermore, the transmitting end and the receiving end obtain their respective transformation parameters η1 and η2.

[0245] One possible solution (denoted as Solution 1):

[0246] S403, the receiver obtains the channel transmittance Ti of 2m arrays.

[0247] For example, if the data from every N cycles is considered as an array, then there are 2m arrays in one post-processing cycle. The receiver estimates the channel transmittance Ti for each array. It should be understood that this application does not limit the method of estimating channel transmittance, and any scheme currently used to estimate channel transmittance should be within the protection scope of this embodiment. As an example, Ti for the 2m arrays can be determined by random sampling. For example, the transmitter randomly selects a portion of data from each array and publishes it to the receiver, so the receiver can obtain an estimated value Ti of channel transmittance by comparing it with the measurement data. This portion of randomly sampled data needs to be discarded because it is published. As another example, Ti for the 2m arrays can also be estimated by pilot signal assistance. For example, in each cycle, a pilot optical signal is also transmitted at a frequency other than the frequency of the quantum signal. This optical signal can adopt certain agreed modulation methods, so that the receiver can directly estimate the channel transmittance of the array through the detection results.

[0248] S404, the receiver determines the equivalent transmittance Teff.

[0249] For example, after the receiving end obtains Ti from 2m arrays, it determines Teff based on Ti from these 2m arrays.

[0250] It should be noted that the selection of Teff is somewhat arbitrary, as long as it lies between the maximum value Ti_max and the minimum value Ti_min among the 2m Ti values; the specific method is not limited. Several possible implementation methods are illustrated below:

[0251] In one example, the receiver arbitrarily selects a value between Ti_max and Ti_min as Teff; in another example, the receiver selects the average of Ti_max and Ti_min as Teff; in yet another example, the receiver selects a Teff such that the number of Ti values ​​greater than or equal to Teff and the number of Ti values ​​less than or equal to Teff among the 2m Ti values ​​are equal, or such that the absolute value of the difference between the number of Ti values ​​greater than or equal to Teff and the number of Ti values ​​less than or equal to Teff among the 2m Ti values ​​is less than or equal to a set threshold.

[0252] S405, the receiver divides every two arrays into a group and calculates the transformation parameters η1 and η2 for each group.

[0253] For example, the receiver divides the data into multiple packets, each packet containing two arrays, where the transmittance of the two arrays in each packet is one greater than or equal to Teff and the other less than or equal to Teff.

[0254] It should be noted that when the number of arrays with Ti greater than Teff in the 2m arrays exceeds the number of arrays with Ti less than Teff, several arrays with Ti greater than Teff will fail to complete pairing and subsequent data correction. In this case, one approach is to discard this part of the data directly; another approach is to accumulate this part of the data into the next processing cycle and process it together with the next 2m arrays. When the number of arrays with Ti greater than Teff is less than the number of arrays with Ti less than Teff, a similar approach can be used. However, it should be understood that in this case, Teff is larger, and the transformed data will have a higher security bitrate.

[0255] Therefore, the optimal situation is that the number of Ti values ​​greater than or equal to Teff and the number of Ti values ​​less than or equal to Teff in the 2m arrays are equal. At this point, the 2m arrays can be divided into m groups, with each group containing two arrays.

[0256] In this embodiment, the indices of the two arrays of the i-th group among the m groups are denoted as S. i_1 and S i_2 The estimated transmittance is denoted as T. i_1 and T i_2 Meanwhile, T i_1 and T i_2 Satisfy T i_1 <Teff <T i_2 .

[0257] For the sake of convenience, the following explanations will all use this optimal scenario as an example.

[0258] Furthermore, the receiving end calculates the transformation parameters η1 and η2 for each packet, meaning there are m η1 and η2 parameters in total. Here, η1 represents the transformation parameters of the transmitting end, and η2 represents the transformation parameters of the receiving end. The transmitting end transformation parameters and the receiving end transformation parameters of the i-th group are denoted as η1 and η2 respectively. i_1 and η i_2 .

[0259] For example, a parameter transformation method using the two dual-mode entangled state modes described above, and specifically for S... i_2 Once the transformation parameters are determined, then:

[0260]

[0261] Then, following this scheme, m pairs of transformation parameters for m groups can be determined.

[0262] S406, the sending end divides every two arrays into a group.

[0263] It should be understood that the sending end should group data in the same way as the receiving end; however, the sending end groups its own data, while the receiving end groups its own data. For the sake of simplicity, the specific grouping process will not be described in detail.

[0264] S407, the receiver sends the transmitter's transformation parameter η1 to the transmitter.

[0265] Another possible solution (denoted as Solution 2):

[0266] S408, the receiver acquires Ti from 2m packets.

[0267] It should be understood that S408 is similar to S403, and for the sake of brevity, it will not be explained again.

[0268] S409, the receiving end sends Ti of the 2m packets to the sending end.

[0269] For example, after the receiving end obtains Ti from 2m packets, it sends each Ti to the sending end.

[0270] S410, the sending end determines Teff.

[0271] S411, the receiver determines Teff.

[0272] It should be understood that S409, S410, and S405 are similar, the only difference being that S409 is executed by the sending end. Furthermore, the sending and receiving ends should use the same strategy to determine Teff, so that the Teff determined by the sending and receiving ends are equal. For example, the sending and receiving ends determine Teff according to preset rules, ensuring that the number of Ti values ​​greater than or equal to Teff and the number of Ti values ​​less than or equal to Teff among the 2m Ti values ​​are equal.

[0273] S4 1 2, the transmitter divides every two arrays into a group and calculates the transmitter transformation parameter η1 for each group.

[0274] S4 1 3, the receiver divides every two arrays into a group and calculates the receiver transformation parameter η2 for each group.

[0275] S413 and S405 are similar, except that in S412, the transmitting end only needs to calculate η1, and the receiving end only needs to calculate η2. Of course, the transmitting and receiving ends can calculate both η1 and η2; this application does not impose this limitation. It should be noted that in S412 and S413, the transmitting and receiving ends should divide the arrays in the same way, that is, the transmitting and receiving ends should divide the arrays according to the same preset rules to ensure that the groups of the transmitting and receiving ends are consistent.

[0276] Another possible solution (denoted as Solution 3):

[0277] S413, the sending end obtains Ti of 2m packets.

[0278] S414, the receiver acquires Ti from 2m packets.

[0279] For example, the transmitter and receiver each estimate Ti for 2m packets. The estimation method can employ random sampling; for instance, the transmitter randomly selects a portion of data from each packet and publishes it to the receiver, and the receiver also randomly selects a portion of data from each packet and publishes it to the transmitter (or the receiver publishes data from the same location as the transmitter's published data). Then, both parties can independently estimate the channel transmittance Ti for that packet based on the published data from the same location. This randomly sampled data needs to be discarded because it is publicly available.

[0280] S415-S418 are similar to S409-S412, so for the sake of brevity, they will not be explained again.

[0281] S4 1 9, the transmitting end transforms the transmitting end data according to η1.

[0282] S420, the receiving end transforms the receiving data according to η2.

[0283] Taking the i-th group as an example, the sending end transforms the parameter η according to the sending end. i_1 Data for groups Si_1 and Si_2 and The transformation yields two new groups of data. and

[0284] The receiver uses parameter η i_2 Data for groups Si_1 and Si_2 and The transformation yields two new groups of data. and

[0285] Based on the determined transformation parameter η i_1 η i_2 One method involves the sender and receiver discarding one packet while retaining only the data in the other. For example, discarding packet Si_1 and retaining packet Si_2; or vice versa. Alternatively, the sender and receiver may only transform the data in the packets that need to be retained, while leaving the other packet to be discarded untransformed.

[0286] For example, a data transformation scheme can be performed using the two entangled state models described earlier. When determining the transformation parameter η for Si_2 grouping... i_1 and η i_2 ,but:

[0287]

[0288] Among them, A i_2 This represents the data sent from the Si_2 packet, i.e. A i_1 This represents the data sent from the Si_1 packet, i.e. A′ i_2 This represents the new data obtained by transforming the data in Si_2 at the transmitting end, i.e. B i_2 This represents the received data in the Si_2 packet, i.e. B i_1 This represents the received data in the Si_1 packet, i.e. B′ i_2 This represents the new data obtained by transforming the data in Si_2 at the receiving end, i.e.

[0289] Alternatively, data changes can be made for the Si_1 group:

[0290]

[0291] Among them, A i_1This represents the data sent from the Si_1 packet, i.e. A′ i_1 This represents the new data obtained by transforming the data in Si_1 at the transmitting end, i.e. B i_1 This represents the received data in the Si_1 packet, i.e. B′ i_1 This represents the new data obtained by the receiver transforming the data in Si_1, i.e.

[0292] The sender and receiver can discard the new data obtained by transforming the data for Si_1.

[0293] After performing the aforementioned transformation parameters, data transformation, and discard operations on all 2m data groups, the remaining m data groups will proceed to the next processing step.

[0294] Figure 9 Method 500 in (b) introduces another possible implementation. Method 500 includes:

[0295] S501, the transmitting end sends 2m×N coherent states {|α} to the receiving end. A >}.

[0296] S502, the receiver acquires the quantum measurement results.

[0297] It should be understood that S501 to S502 are similar to S401 to S402 in method 400, and therefore will not be described again.

[0298] Furthermore, the transmitting end and the receiving end obtain their respective transformation parameters η1 and η2.

[0299] One possible solution (denoted as Solution 4):

[0300] S503, the transmitting end obtains the channel transmittance Ti of 2m arrays.

[0301] S504, the transmitter determines the equivalent transmittance Teff.

[0302] S505, the transmitting end divides every two arrays into a group and calculates the transformation parameters η1 and η2 for each group.

[0303] It should be understood that S503 to S505 are similar to S403 to S405 in method 400, the difference being that the execution subject of S403 to S405 in method 400 is the receiving end, while the execution subject of S503 to S505 is the sending end.

[0304] In S506, the receiver divides every two arrays into a group.

[0305] It should be understood that the receiving end should use the same method of packet generation as the sending end.

[0306] S507, the transmitting end sends the receiver's transformation parameter η2 to the receiving end.

[0307] Another possible solution (denoted as Solution 5):

[0308] S508, the receiver acquires Ti from 2m packets.

[0309] It should be understood that S508 is similar to S403 in method 400, and for the sake of brevity, it will not be explained again.

[0310] S509, the receiving end sends Ti of the 2m packets to the sending end.

[0311] S510, the sending end determines Teff.

[0312] S511, the receiver determines Teff.

[0313] S512, the transmitter divides every two arrays into a group and calculates the transmitter transformation parameter η1 for each group.

[0314] S5 1 3, the receiver divides every two arrays into a group and calculates the receiver transformation parameter η2 for each group.

[0315] It should be understood that S510 to S513 are similar to S410 to S413 in method 400, and will not be described again.

[0316] S514, the transmitting end transforms the transmitting end data according to η1.

[0317] S5 1 5, the receiving end transforms the receiving end data according to η2.

[0318] It should be understood that S515 to S515 are similar to S419 to S420 of method 400, and will not be described again.

[0319] Therefore, the quantum key distribution method provided in this application can avoid the impact of channel transmittance variations on the security code rate while wasting relatively little data. Simultaneously, it reduces the number of data packets, lowers the requirements for system storage capacity and parallel processing capabilities, and reduces the uncertainty caused by channel attenuation variations.

[0320] The quantum key distribution method provided in this application has been described in detail above. The quantum key distribution apparatus provided in this application is described below.

[0321] Figure 10This is a schematic structural block diagram of a quantum key distribution device 600 provided according to an embodiment of this application. Figure 10 The device 600 shown includes a transceiver module 601 and a processing module 602.

[0322] The device 600 can be used to perform the actions performed by the first device (or transmitter) in the above method embodiment. In this case, the device 600 can be the first device (or transmitter) or a component configured on the first device (or transmitter). The transceiver module 610 is used to perform the transceiver-related operations of the first device (or transmitter) in the above method embodiment, and the processing module 620 is used to perform operations of the first device (or transmitter) in the above method embodiment other than transceiver.

[0323] One possible implementation includes a transceiver module 610, which transmits k sets of quantum states to a second device via a quantum channel. These k sets of quantum states are associated with k arrays. A processing module 620 divides these k arrays into m groups, each of which includes at least two arrays, where m is an integer greater than 1 and k is greater than or equal to 2m. The processing module 620 also acquires m first transformation parameters, each corresponding to one of the m groups. Furthermore, the processing module 620 transforms the first data of the first array in the i-th group and the second data of the second array in the i-th group according to the i-th first transformation parameter from the m first transformation parameters to obtain third data. The i-th first transformation parameter is determined based on a first transmittance and the transmittance of the first and second arrays, and corresponds to the i-th group, where i ∈ [1, m]. The processing module 620 further determines a security key based on the third data.

[0324] Optionally, in some embodiments, the transceiver module 610 is specifically configured to: receive the m first transformation parameters from the second device; or, the processing module 620 is specifically configured to: determine the m first transformation parameters based on the first transmittance and the transmittance of at least two arrays of each of the m groups.

[0325] Optionally, in some embodiments, the processing module 620 is specifically used to: obtain k transmittances of the k arrays; divide the k arrays into m groups according to the k transmittances of the k arrays, wherein in at least two arrays in each of the m groups, the transmittance of one array is greater than or equal to the first transmittance, and the transmittance of the other array is less than or equal to the first transmittance.

[0326] Optionally, in some embodiments, the method further includes: determining the first transmittance based on the k transmittances of the k arrays, wherein the absolute value of the difference between the number of transmittances greater than the first transmittance and the number of transmittances less than the first transmittance is less than or equal to a first threshold.

[0327] Optionally, in some embodiments, the first transmittance is greater than or equal to the transmittance of one of the at least two arrays in the i-th group, and less than or equal to the transmittance of the other array in the at least two arrays. The i-th first transformation parameter, the first transmittance, the transmittance of the first array, and the transmittance of the second array satisfy any of the following relationships: Wherein, η1 represents the i-th first transformation parameter, Teff represents the first transmittance, T1 represents the transmittance of the first array, and T2 represents the transmittance of the second array.

[0328] Optionally, in some embodiments, the first data, the second data, the third data, and the i-th first transformation parameter satisfy the following relationship: Wherein, A1 represents the first data, A2 represents the second data, A′1 represents the third data, and η1 represents the i-th first transformation parameter.

[0329] The device 600 can also be used to perform the actions performed by the second device (or receiver) in the above method embodiment. In this case, the device 600 can be the second device (or receiver) or a component configured on the second device (or receiver). The transceiver module 610 is used to perform the transceiver-related operations of the second device (or receiver) in the above method embodiment, and the processing module 620 is used to perform operations of the second device (or receiver) in the above method embodiment other than transceiver.

[0330] One possible implementation includes a transceiver module 610, which receives k sets of quantum states from a first device via a quantum channel, the k sets of quantum states being associated with k arrays; a processing module 620, which divides the k arrays into m groups, each of the m groups including at least two arrays, where m is an integer greater than 1 and k is greater than or equal to 2m; the processing module 620 is further configured to obtain m second transformation parameters, each of the m second transformation parameters corresponding to one of the m groups; the processing module 620 is further configured to transform the fourth data of the third array in the i-th group of the m groups and the fifth data of the fourth array in the i-th group according to the i-th second transformation parameter, the i-th second transformation parameter being determined based on a first transmittance and the transmittance of the third and fourth arrays, the i-th first transformation parameter corresponding to the i-th group, where i ∈ [1, m]; and the processing module 620 is further configured to determine a security key based on the sixth data.

[0331] Optionally, in some embodiments, the transceiver module 610 is specifically configured to: the second device receive the m second transformation parameters from the first device; or, the processing module 620 is specifically configured to: determine the m second transformation parameters based on the first transmittance and the transmittance of at least two arrays of each of the m groups.

[0332] Optionally, in some embodiments, the processing module 620 is specifically used to: obtain the k transmittances of the k arrays; divide the k arrays into m groups according to the k transmittances of the k arrays, wherein in each of the m groups, at least two arrays have a transmittance of one array greater than or equal to the first transmittance and a transmittance of the other array less than or equal to the first transmittance.

[0333] Optionally, in some embodiments, the processing module 620 is further configured to: the second device determine the first transmittance based on the k transmittances of the k arrays, wherein the absolute value of the difference between the number of transmittances greater than the first transmittance and the number of transmittances less than the first transmittance is less than a first threshold.

[0334] Optionally, in some embodiments, the first transmittance is greater than or equal to the transmittance of one of the at least two arrays in the i-th group, and less than or equal to the transmittance of the other array in the at least two arrays. The i-th first transformation parameter, the first transmittance, the transmittance of the first array, and the transmittance of the second array satisfy any of the following relationships: Wherein, η2 represents the i-th second transformation parameter, Teff represents the first transmittance, T1 represents the transmittance of the first array, and T2 represents the transmittance of the second array.

[0335] Optionally, in some embodiments, the first data, the second data, the third data, and the i-th first transformation parameter satisfy the following relationship: Wherein, B1 represents the fourth data, B2 represents the fifth data, B′1 represents the sixth data, and η2 represents the i-th second transformation parameter.

[0336] For details on the specific functions and beneficial effects of the transceiver module 610 and the processing module 620, please refer to [link / reference]. Figures 4-9 The embodiments shown are not described in detail here for the sake of simplicity.

[0337] Figure 11 This is a schematic structural block diagram of a quantum key distribution device 700 according to an embodiment of this application. The device 700 includes a bus 701, a processor 702, a communication interface 703, and a memory 704. The processor 702, memory 704, and communication interface 703 communicate via the bus 701. The processor 702 can be a field-programmable gate array (FPGA), an application-specific integrated circuit (ASIC), a system-on-a-chip (SoC), a central processing unit (CPU), a network processor (NP), a digital signal processor (DSP), a microcontroller unit (MCU), a programmable logic device (PLD), other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, or other integrated chips. The memory 704 stores executable code included in the pathological image processing system, and the processor 702 reads the executable code from the memory 704 to execute it as follows: Figure 3 The method is shown. The memory 704 may also include other software modules required for running processes, such as an operating system. The operating system can be LINUX. TM UNIX TM WINDOWS TN wait.

[0338] This application also provides a chip system, including: a logic circuit, the logic circuit being coupled to an input / output interface, through which data is transmitted to perform actions such as... Figure 3 The method described.

[0339] In implementation, each step of the above method can be completed by integrated logic circuits in the processor's hardware or by instructions in software. The steps of the method disclosed in the embodiments of this application can be directly implemented by a hardware processor, or by a combination of hardware and software modules in the processor. The software modules can reside in random access memory, flash memory, read-only memory, programmable read-only memory, electrically erasable programmable memory, registers, or other mature storage media in the art. This storage medium is located in memory, and the processor reads information from the memory and, in conjunction with its hardware, completes the steps of the above method. To avoid repetition, detailed descriptions are omitted here.

[0340] It should be noted that the processor in the embodiments of this application can be an integrated circuit chip with signal processing capabilities. In implementation, each step of the above method embodiments can be completed by the integrated logic circuitry in the processor's hardware or by instructions in software form. The general-purpose processor can be a microprocessor or any conventional processor. The steps of the method disclosed in the embodiments of this application can be directly implemented by a hardware decoding processor, or by a combination of hardware and software modules in the decoding processor. The software modules can reside in random access memory, flash memory, read-only memory, programmable read-only memory, electrically erasable programmable memory, registers, or other mature storage media in the art. This storage medium is located in memory; the processor reads information from the memory and, in conjunction with its hardware, completes the steps of the above method.

[0341] It is understood that the memory in the embodiments of this application can be volatile memory or non-volatile memory, or may include both volatile and non-volatile memory. The non-volatile memory can be read-only memory (ROM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), or flash memory. The volatile memory can be random access memory (RAM), which is used as an external cache. By way of example, but not limitation, many forms of RAM are available, such as static random access memory (SRAM), dynamic random access memory (DRAM), synchronous dynamic random access memory (SDRAM), double data rate synchronous dynamic random access memory (DDR SDRAM), enhanced synchronous dynamic random access memory (ESDRAM), synchronous linked dynamic random access memory (SLDRAM), and direct rambus RAM (DR RAM). It should be noted that the memory used in the systems and methods described herein is intended to include, but is not limited to, these and any other suitable types of memory.

[0342] According to the method provided in the embodiments of this application, this application also provides a computer program product, which includes: computer program code, which, when run on a computer, causes the computer to execute... Figure 3 The method of the illustrated embodiment.

[0343] According to the method provided in the embodiments of this application, this application also provides a computer-readable medium storing program code, which, when run on a computer, causes the computer to perform... Figure 3 The method of the illustrated embodiment.

[0344] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0345] Those skilled in the art will understand that, for the sake of convenience and brevity, the specific working processes of the systems, devices, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0346] In the several embodiments provided in this application, it should be understood that the disclosed systems, apparatuses, and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between apparatuses or units may be electrical, mechanical, or other forms.

[0347] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0348] In addition, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit.

[0349] If the aforementioned functions are implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or a portion of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0350] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. A method for quantum key distribution, characterized in that, include: The first device sends k sets of quantum states to the second device via a quantum channel, wherein the k sets of quantum states are associated with k arrays. The first device divides p arrays out of the k arrays into m groups, each of the m groups including at least two arrays, where m is an integer greater than 1, p is less than or equal to k, and p is greater than or equal to 2m; The first device acquires m first transformation parameters, and the m first transformation parameters correspond one-to-one with the m groups; The first device transforms the first data of the first array in the first group and the second data of the second array in the first group in the m groups according to the i-th first transformation parameter among the m first transformation parameters to obtain the third data. The i-th first transformation parameter is determined according to the first transmittance and the transmittance of the first array and the second array. The i-th first transformation parameter corresponds to the i-th group, where i∈[1,m]. The first device determines the security key based on the third data.

2. The method according to claim 1, characterized in that, The first device acquires m first transformation parameters, including: The first device receives the m first transformation parameters from the second device; or, The first device determines the m first transformation parameters based on the first transmittance and the transmittance of at least two arrays of each of the m groups.

3. The method according to claim 1 or 2, characterized in that, The first device divides p arrays out of the k arrays into m groups, including: The first device acquires k transmittance values ​​from the k arrays; The first device divides p arrays in the k arrays into m groups based on the k transmittances of the k arrays. In each of the m groups, at least two arrays in one array have a transmittance greater than or equal to the first transmittance, and the transmittance of the other array is less than or equal to the first transmittance.

4. The method according to claim 3, characterized in that, The method further includes: The first device determines the first transmittance based on the k transmittances of the k arrays, wherein the absolute value of the difference between the number of transmittances greater than the first transmittance and the number of transmittances less than the first transmittance is less than or equal to a first threshold.

5. The method according to claim 1, 2 or 4, characterized in that, The first transmittance is greater than or equal to the transmittance of one of the at least two arrays in the i-th group, and less than or equal to the transmittance of the other array. The i-th first transformation parameter, the first transmittance, the transmittance of the first array, and the transmittance of the second array satisfy the following relationship: Wherein, η1 represents the i-th first transformation parameter, Teff represents the first transmittance, T1 represents the transmittance of the first array, and T2 represents the transmittance of the second array.

6. The method according to claim 5, characterized in that, The first data, the second data, the third data, and the i-th first transformation parameter satisfy the following relationship: Wherein, A1 represents the first data, A2 represents the second data, and A′1 represents the third data.

7. The method according to claim 1, 2 or 4, characterized in that, The first transmittance is greater than or equal to the transmittance of one of the at least two arrays in the i-th group, and less than or equal to the transmittance of the other array. The i-th first transformation parameter, the first transmittance, the transmittance of the first array, and the transmittance of the second array satisfy the following relationship: Wherein, η1 represents the i-th first transformation parameter, Teff represents the first transmittance, T1 represents the transmittance of the first array, and T2 represents the transmittance of the second array.

8. The method according to claim 7, characterized in that, The first data, the second data, the third data, and the i-th first transformation parameter satisfy the following relationship: Wherein, A1 represents the first data, A2 represents the second data, A′2 represents the third data, and η1 represents the i-th first transformation parameter.

9. A method for quantum key distribution, characterized in that, include: The second device receives k sets of quantum states from the first device via a quantum channel, the k sets of quantum states being associated with k arrays; The second device divides p arrays out of the k arrays into m groups, each of the m groups including at least two arrays, where m is an integer greater than 1, p is less than or equal to k, and k is greater than or equal to 2m; The second device acquires m second transformation parameters, and the m second transformation parameters correspond one-to-one with the m groups; The second device transforms the fourth data of the third array and the fifth data of the fourth array in the i-th group of the m groups according to the i-th second transformation parameter among the m second transformation parameters to obtain the sixth data. The i-th second transformation parameter is determined according to the first transmittance and the transmittance of the third array and the fourth array. The i-th second transformation parameter corresponds to the i-th group, where i∈[1,m]. The second device determines the security key based on the sixth data.

10. The method according to claim 9, characterized in that, The second device acquires m second transformation parameters, including: The second device receives the m second transformation parameters from the first device; or, The second device determines the m second transformation parameters based on the first transmittance and the transmittance of at least two arrays of each of the m groups.

11. The method according to claim 9 or 10, characterized in that, The second device divides multiple arrays from the k arrays into m groups, including: The second device acquires the k transmittance values ​​of the k arrays; The second device divides p arrays in the k arrays into m groups based on the k transmittances of the k arrays. In each of the m groups, at least two arrays have a transmittance greater than or equal to the first transmittance and a transmittance less than or equal to the first transmittance.

12. The method according to claim 9, characterized in that, The method further includes: The second device determines the first transmittance based on the k transmittances of the k arrays, wherein the absolute value of the difference between the number of transmittances greater than the first transmittance and the number of transmittances less than the first transmittance is less than or equal to a first threshold.

13. The method according to claim 9, 10, or 12, characterized in that, The first transmittance is greater than or equal to the transmittance of one of the at least two arrays in the i-th group, and less than or equal to the transmittance of the other array. The i-th second transformation parameter, the first transmittance, the transmittance of the first array, and the transmittance of the second array satisfy the following relationship: Wherein, η2 represents the i-th second transformation parameter, Teff represents the first transmittance, T1 represents the transmittance of the first array, T2 represents the transmittance of the second array, and the first array and the second array are two arrays in the i-th group on the first device side.

14. The method according to claim 13, characterized in that, The fourth data, the fifth data, the sixth data, and the i-th second transformation parameter satisfy the following relationship: Wherein, B1 represents the fourth data, B2 represents the fifth data, and B′1 represents the sixth data.

15. The method according to claim 9, 10, or 12, characterized in that, The first transmittance is greater than or equal to the transmittance of one of the at least two arrays in the i-th group, and less than or equal to the transmittance of the other array. The i-th second transformation parameter, the first transmittance, the transmittance of the first array, and the transmittance of the second array satisfy the following relationship: Wherein, η2 represents the i-th second transformation parameter, Teff represents the first transmittance, T1 represents the transmittance of the first array, T2 represents the transmittance of the second array, and the first array and the second array are two arrays in the i-th group on the first device side.

16. The method according to claim 15, characterized in that, The fourth data, the fifth data, the sixth data, and the i-th second transformation parameter satisfy the following relationship: Wherein, B1 represents the fourth data, B2 represents the fifth data, and B′2 represents the sixth data.

17. A quantum key distribution device, characterized in that, include: A transceiver module is used to send k sets of quantum states to a second device via a quantum channel, wherein the k sets of quantum states are associated with k arrays. The processing module is used to divide p arrays out of the k arrays into m groups, each of the m groups including at least two arrays, where m is an integer greater than 1 and k is greater than or equal to 2m; The processing module is further configured to obtain m first transformation parameters, wherein the m first transformation parameters correspond one-to-one with the m groups; The processing module is further configured to transform the first data of the first array in the first group and the second data of the second array in the first group in the m groups according to the i-th first transformation parameter among the m first transformation parameters to obtain the third data. The i-th first transformation parameter is determined according to the first transmittance and the transmittance of the first array and the second array. The i-th first transformation parameter corresponds to the i-th group, where i∈[1,m]. The processing module is also used to determine a security key based on the third data.

18. The apparatus according to claim 17, characterized in that, The transceiver module is specifically used for: Receive the m first transformation parameters from the second device; or... The processing module is specifically used for: The m first transformation parameters are determined based on the first transmittance and the transmittance of at least two arrays of each of the m groups.

19. The apparatus according to claim 17 or 18, characterized in that, The processing module is specifically used for: Obtain the k transmittance values ​​from the k arrays; Based on the k transmittances of the k arrays, p arrays in the k arrays are divided into m groups. In each of the m groups, at least two arrays in one array have a transmittance greater than or equal to the first transmittance, and the transmittance of the other array is less than or equal to the first transmittance.

20. The apparatus according to claim 19, characterized in that, The processing module is also used for: The first transmittance is determined based on the k transmittance values ​​of the k arrays, wherein the absolute value of the difference between the number of transmittance values ​​greater than the first transmittance value and the number of transmittance values ​​less than the first transmittance value is less than a first threshold.

21. The apparatus according to claim 17, 18 or 20, characterized in that, The first transmittance is greater than or equal to the transmittance of one of the at least two arrays in the i-th group, and less than or equal to the transmittance of the other array. The i-th first transformation parameter, the first transmittance, the transmittance of the first array, and the transmittance of the second array satisfy the following relationship: Wherein, η1 represents the i-th first transformation parameter, Teff represents the first transmittance, T1 represents the transmittance of the first array, and T2 represents the transmittance of the second array.

22. The apparatus according to claim 21, characterized in that, The first data, the second data, the third data, and the i-th first transformation parameter satisfy the following relationship: Wherein, A1 represents the first data, A2 represents the second data, A′1 represents the third data, and η1 represents the i-th first transformation parameter.

23. The apparatus according to claim 17, 18 or 20, characterized in that, The first transmittance is greater than or equal to the transmittance of one of the at least two arrays in the i-th group, and less than or equal to the transmittance of the other array. The i-th first transformation parameter, the first transmittance, the transmittance of the first array, and the transmittance of the second array satisfy the following relationship: Wherein, η1 represents the i-th first transformation parameter, Teff represents the first transmittance, T1 represents the transmittance of the first array, and T2 represents the transmittance of the second array.

24. The apparatus according to claim 23, characterized in that, The first data, the second data, the third data, and the i-th first transformation parameter satisfy the following relationship: Wherein, A1 represents the first data, A2 represents the second data, and A′2 represents the third data.

25. A quantum key distribution device, characterized in that, include: A transceiver module is configured to receive k sets of quantum states from a first device via a quantum channel, wherein the k sets of quantum states are associated with k arrays. The processing module is used to divide p arrays out of the k arrays into m groups, each of the m groups including at least two arrays, where m is an integer greater than 1 and k is greater than or equal to 2m; The processing module is further configured to obtain m second transformation parameters, wherein the m second transformation parameters correspond one-to-one with the m groups; The processing module is further configured to transform the fourth data of the third array in the i-th group of the m groups and the fifth data of the fourth array in the i-th group to obtain the sixth data according to the i-th second transformation parameter among the m second transformation parameters. The i-th second transformation parameter is determined according to the first transmittance and the transmittance of the third array and the fourth array. The i-th second transformation parameter corresponds to the i-th group, where i∈[1,m]. The processing module is also used to determine a security key based on the sixth data.

26. The apparatus according to claim 25, characterized in that, The transceiver module is specifically used for: Receive the m second transformation parameters from the first device; or... The processing module is specifically used for: The m second transformation parameters are determined based on the first transmittance and the transmittance of at least two arrays of each of the m groups.

27. The apparatus according to claim 25 or 26, characterized in that, The processing module is specifically used for: Obtain the k transmittance values ​​from the k arrays; Based on the k transmittances of the k arrays, p arrays in the k arrays are divided into m groups, and in each of the m groups, at least two arrays have a transmittance of one array greater than or equal to the first transmittance and a transmittance of the other array less than or equal to the first transmittance.

28. The apparatus according to claim 27, characterized in that, The processing module is also used for: The first transmittance is determined based on the k transmittance values ​​of the k arrays, wherein the absolute value of the difference between the number of transmittance values ​​greater than the first transmittance value and the number of transmittance values ​​less than the first transmittance value is less than a first threshold.

29. The apparatus according to claim 25, 26 or 28, characterized in that, The first transmittance is greater than or equal to the transmittance of one of the at least two arrays in the i-th group, and less than or equal to the transmittance of the other array. The i-th second transformation parameter, the first transmittance, the transmittance of the first array, and the transmittance of the second array satisfy the following relationship: Wherein, η2 represents the i-th second transformation parameter, Teff represents the first transmittance, T1 represents the transmittance of the first array, T2 represents the transmittance of the second array, and the first array and the second array are two arrays in the i-th group on the first device side.

30. The apparatus according to claim 29, characterized in that, The fourth data, the fifth data, the sixth data, and the i-th second transformation parameter satisfy the following relationship: Wherein, B1 represents the fourth data, B2 represents the fifth data, B′1 represents the sixth data, and η2 represents the i-th second transformation parameter.

31. The apparatus according to claim 25, 26 or 28, characterized in that, The first transmittance is greater than or equal to the transmittance of one of the at least two arrays in the i-th group, and less than or equal to the transmittance of the other array. The i-th second transformation parameter, the first transmittance, the transmittance of the first array, and the transmittance of the second array satisfy the following relationship: Wherein, η2 represents the i-th second transformation parameter, Teff represents the first transmittance, T1 represents the transmittance of the first array, T2 represents the transmittance of the second array, and the first array and the second array are two arrays in the i-th group on the first device side.

32. The apparatus according to claim 31, characterized in that, The fourth data, the fifth data, the sixth data, and the i-th first transformation parameter satisfy the following relationship: Wherein, B1 represents the fourth data, B2 represents the fifth data, and B′1 represents the sixth data.

33. A quantum key distribution device, characterized in that, The device includes at least one processor coupled to at least one memory, the at least one processor being configured to execute a computer program or instructions stored in the at least one memory to cause the device to perform the method as claimed in any one of claims 1 to 8 or any one of claims 9 to 16.

34. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program that, when run on a computer, causes the computer to perform the method as claimed in any one of claims 1 to 8 or any one of claims 9 to 16.

35. A computer program product, characterized in that, The computer program product includes computer program code that, when run on a computer, causes the method of any one of claims 1 to 8 or any one of claims 9 to 16 to be performed.

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