A quantum communication optimization method and system based on AI

Abstract

The present invention relates to the field of artificial intelligence technology. The present invention discloses an AI-based quantum communication optimization method and system, comprising: a quantum communication hierarchical identification module, a communication data acquisition and transmission module, a quantum communication quality analysis module, a loss function hierarchical judgment module, and an intelligent terminal optimization and early warning module. The quantum communication network is hierarchically identified according to the linear topological structure of the quantum communication network and quantum information of each level of the quantum communication network is obtained. The communication quality of the quantum communication network is analyzed to obtain the quantum communication quality index of each level, and the quantum communication quality index of each level is substituted into a loss function model to calculate the loss difference index of each level to complete the risk judgment of each level of the quantum communication network. The risk gradient is divided according to the risk judgment result. The intelligent terminal completes the optimization and early warning instruction, responds to and handles the potential risk in time, and ensures the stable operation of the quantum communication network.

Description

Technical Field

[0001] The present invention relates to the field of artificial intelligence technology, and more specifically to an AI-based quantum communication optimization method and system. Background Art

[0002] In recent years, with the rapid development of artificial intelligence and quantum computing, the cross-integration between the two has become a new trend. AI technology, with its powerful data processing and pattern recognition capabilities, has shown great potential in optimizing complex systems, while quantum computing, with its unique parallelism and exponential computing capabilities, has significant advantages in processing large-scale data and solving complex problems.

[0003] Specifically, AI-based quantum communication optimization methods can discover new entanglement purification schemes and optimize quantum state transmission processes by simulating and training quantum communication protocols. For example, with the empowerment of quantum technology by deep learning, quantum teleportation protocols can be learned and the fidelity of transmission can be improved. In addition, AI technology can also be used to optimize parameter settings in quantum communication protocols, improve the robustness and adaptability of protocols, etc.

[0004] However, existing quantum communication optimization methods still have some challenges and limitations, such as the complexity and uncertainty of quantum communication networks, and noise and loss in the process of quantum state transmission. These problems may lead to a decline in the quality of quantum communication and affect the reliability and efficiency of quantum communication. At the same time, quantum communication networks contain multiple levels, and the above problems will lead to significant differences in the quality of quantum communication between different levels. Summary of the invention

[0005] In order to overcome the above-mentioned defects of the prior art, the present invention provides an AI-based quantum communication optimization system to solve the problems existing in the above-mentioned background technology.

[0006] The present invention provides the following technical solutions: an AI-based quantum communication optimization system, comprising: a quantum communication hierarchical identification module, a communication data acquisition and transmission module, a quantum communication quality analysis module, a loss function hierarchical judgment module, and an intelligent terminal optimization early warning module;

[0007] The quantum communication hierarchical identification module performs hierarchical identification on the quantum communication network according to the linear topological structure of the quantum communication network;

[0008] The communication data acquisition and transmission module acquires quantum information at each level of the quantum communication network through the quantum computing toolbox, and transmits the information to the quantum communication quality analysis module;

[0009] The quantum communication quality analysis module acquires quantum information of each level of the quantum communication network transmitted by the transmission module based on the communication data, and performs communication quality analysis on the quantum communication network to obtain quantum communication quality indexes of each level;

[0010] The loss function hierarchical judgment module substitutes the quantum communication quality index of each level into the loss function model to calculate the loss difference index of each level, and makes risk judgment on each level of the quantum communication network according to the loss difference index;

[0011] The intelligent terminal optimization and early warning module includes an intelligent optimization unit and an intelligent early warning unit. The risk gradient is divided based on the risk judgment results of each level of the quantum communication network, and the intelligent terminal completes the optimization and early warning instructions.

[0012] Preferably, in the quantum communication hierarchical identification module, the quantum communication network is hierarchically identified according to the linear topological structure of the quantum communication network, and the quantum communication network is divided into n layers, where i=1, 2, 3, ..., n, and i represents the serial number of the quantum communication network layer. In the linear topological structure, quantum nodes are arranged in a linear order, different quantum nodes are divided into different levels according to different heights, and adjacent nodes are connected through quantum channels.

[0013] Preferably, in the communication data acquisition and transmission module, quantum computing tools are used to acquire quantum information in real time during the communication process of each level of the quantum communication network to obtain the communication environment of quantum communication, and the quantum information specifically includes: quantum communication phase parameters and quantum communication amplitude parameters;

[0014] Use quantum interference equipment to obtain the phase characteristics of quantum states, measure quantum phases through interference phenomena, and obtain quantum communication phase parameters at all levels of the quantum communication network;

[0015] Quantum simulators are used to simulate quantum behavior, simulate quantum circuits and quantum states, and obtain quantum communication amplitude parameters at each level of the quantum communication network.

[0016] Preferably, in the quantum communication quality analysis module, the specific contents of the quantum communication quality indexes at each level obtained by performing communication quality analysis on the quantum communication network are as follows:

[0017] Step S1: Analyzing the phase attenuation in the quantum communication process based on the quantum communication phase parameters of each level of the quantum communication network to calculate the quantum phase attenuation coefficient of each level, and analyzing the amplitude attenuation in the quantum communication process based on the quantum communication amplitude parameters of each level of the quantum communication network to calculate the quantum amplitude attenuation coefficient of each level;

[0018] Step S2: Analyze the communication quality of each level through the quantum phase attenuation coefficient and quantum amplitude attenuation coefficient of each level of the quantum communication network, and obtain the quantum communication quality index of each level.

[0019] Preferably, the calculation contents of the quantum phase attenuation coefficients at each level are as follows:

[0020] Input a preset quantum phase into a quantum interference device, change the quantum phase through a phase modulator of the quantum interference device, generate interference phenomenon and measure the intensity distribution of interference fringes;

[0021] The quantum phase attenuation coefficient of each level is calculated based on the intensity distribution of the interference fringes. The calculation formula is: ,in represents the quantum phase attenuation coefficient at each level in the quantum communication process, It represents the maximum intensity of interference fringes generated at each level in the quantum communication process. It represents the minimum intensity of interference fringes generated at each level in the quantum communication process. Indicates the length of the interference fringes generated at each level during quantum communication, It represents the distance between the maximum and minimum intensity of the interference fringes generated at each level during quantum communication, and e represents a natural constant;

[0022] The calculation formula of the quantum amplitude attenuation coefficient of each level is: ,in represents the quantum amplitude attenuation coefficient of each level, represents the quantum decay rate of each level, Represents the amplitude value corresponding to the quantum input state at each level, Represents the amplitude value corresponding to the quantum output state of each level.

[0023] Preferably, the calculation formula of the quantum decay rate of each level is: ,in represents the quantum decay rate of each level, e represents the natural constant, It represents the time for each level of quantum to transform from input state to output state, Represents the decay time constant.

[0024] Preferably, the communication quality of each level is analyzed by the quantum phase attenuation coefficient and the quantum amplitude attenuation coefficient of each level of the quantum communication network, and the calculation formula of the quantum communication quality index of each level is obtained as follows: ,in represents the quantum communication quality index at each level, represents the quantum phase attenuation coefficient at each level in the quantum communication process, represents the quantum amplitude attenuation coefficient of each level, and e represents a natural constant.

[0025] Preferably, in the loss function hierarchical judgment module, the quantum communication quality index of each level is substituted into the loss function model to calculate the loss difference index of each level, and the specific content of risk judgment of each level of the quantum communication network based on the loss difference index is as follows:

[0026] Substitute the quantum communication quality index of each level into the loss function model to calculate the loss difference index of each level. The calculation formula of the loss difference index is: ,in Represents the loss difference index of each level in the quantum communication process, Represents the quantum communication quality index of each level in the quantum communication process, where i=2, 3, ..., n, i represents the sequence number of the quantum communication network layer;

[0027] The risk of each layer of the quantum communication network is judged according to the loss difference index of each layer during the communication process. When the loss difference index of each layer during the quantum communication process is greater than or equal to the preset risk threshold, the layer is judged to be risky; otherwise, the layer is judged to be risk-free.

[0028] Preferably, in the intelligent terminal optimization and early warning module, risk gradient division is performed based on the risk judgment results of each level of the quantum communication network: the risk judgment results of the loss function hierarchical judgment module are received, and the risk levels are divided into risk gradients: when the loss difference index of the risk level is greater than or equal to the preset early warning threshold, the intelligent early warning unit starts the early warning setting, locates the risk level of the warning and sends the early warning information to the intelligent terminal; when the loss difference index of the risk level is less than the preset early warning threshold, the intelligent optimization unit formulates an optimization strategy to optimize and adjust the quantum communication network.

[0029] An AI-based quantum communication optimization method comprises the following steps:

[0030] Step S01: hierarchically identifying the quantum communication network according to the linear topological structure of the quantum communication network;

[0031] Step S02: Obtaining quantum information at each level of the quantum communication network through the quantum computing toolbox;

[0032] Step S03: Analyze the communication quality of the quantum communication network to obtain the quantum communication quality index of each level;

[0033] Step S04: Substituting the quantum communication quality index of each level into the loss function model to calculate the loss difference index of each level, and making risk judgments on each level of the quantum communication network according to the loss difference index;

[0034] Step S05: Based on the risk assessment results of each level of the quantum communication network, the risk gradient is divided and the intelligent terminal completes the optimization warning instruction.

[0035] Technical effects and advantages of the present invention:

[0036] The present invention is provided with a quantum communication hierarchical identification module, a communication data acquisition and transmission module, a quantum communication quality analysis module, a loss function hierarchical judgment module, and an intelligent terminal optimization and early warning module. According to the linear topological structure of the quantum communication network, the quantum communication network is hierarchically identified and quantum information of each level of the quantum communication network is obtained. The communication quality of the quantum communication network is analyzed to obtain the quantum communication quality index of each level, thereby improving the reliability and efficiency of the quantum communication network. The phase attenuation and amplitude attenuation in the quantum communication process are accurately reflected by quantum analysis of different levels, thereby evaluating the stability and transmission efficiency of the quantum communication network to improve the communication quality.

[0037] The quantum communication quality index of each level is substituted into the loss function model to calculate the loss difference index of each level to complete the risk judgment of each level of the quantum communication network. The risk gradient is divided according to the risk judgment results. The intelligent terminal completes the optimization early warning instructions, responds to and handles potential risks in a timely manner, and ensures the stable operation of the quantum communication network. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] Figure 1 Schematic diagram of the structure of an AI-based quantum communication optimization system.

[0039] Figure 2 Schematic diagram of a flow chart of an AI-based quantum communication optimization method. DETAILED DESCRIPTION

[0040] The technical solutions in the present invention will be described clearly and completely below in conjunction with the accompanying drawings in the present invention. In addition, the forms of the various structures described in the following embodiments are merely illustrative. The AI-based quantum communication optimization method and system involved in the present invention are not limited to the various structures described in the following embodiments. All other implementations obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention.

[0041] like Figure 1 As shown, the present invention provides an AI-based quantum communication optimization system, including: a quantum communication hierarchical identification module, a communication data acquisition and transmission module, a quantum communication quality analysis module, a loss function hierarchical judgment module, and an intelligent terminal optimization early warning module;

[0042] The quantum communication hierarchical identification module performs hierarchical identification on the quantum communication network according to the linear topological structure of the quantum communication network;

[0043] The communication data acquisition and transmission module acquires quantum information at each level of the quantum communication network through the quantum computing toolbox, and transmits the information to the quantum communication quality analysis module;

[0044] The quantum communication quality analysis module acquires quantum information of each level of the quantum communication network transmitted by the transmission module based on the communication data, and performs communication quality analysis on the quantum communication network to obtain quantum communication quality indexes of each level;

[0045] The loss function hierarchical judgment module substitutes the quantum communication quality index of each level into the loss function model to calculate the loss difference index of each level, and makes risk judgment on each level of the quantum communication network according to the loss difference index;

[0046] The intelligent terminal optimization and early warning module includes an intelligent optimization unit and an intelligent early warning unit. The risk gradient is divided based on the risk judgment results of each level of the quantum communication network, and the intelligent terminal completes the optimization and early warning instructions.

[0047] In this embodiment, it should be specifically explained that in the quantum communication hierarchical identification module, the quantum communication network is hierarchically identified according to the linear topological structure of the quantum communication network, and the quantum communication network is divided into n layers, where i=1, 2, 3, ..., n, i represents the serial number of the quantum communication network layer. In the linear topological structure, quantum nodes are arranged in a linear order, different quantum nodes are divided into different levels according to different heights, and adjacent nodes are connected through quantum channels. The quantum nodes of each level have a unique identifier to facilitate hierarchical identification and acquisition of node information. Through hierarchical identification, the hierarchical structure of the quantum communication network and the connection relationship between nodes can be clearly understood, providing a basis for subsequent data acquisition and analysis.

[0048] In this embodiment, it should be specifically explained that in the communication data acquisition and transmission module, quantum information is acquired in real time during the communication process of each level of the quantum communication network using a quantum computing tool to obtain a communication environment for quantum communication, and the quantum information specifically includes: quantum communication phase parameters and quantum communication amplitude parameters;

[0049] Use quantum interference equipment to obtain the phase characteristics of quantum states, measure quantum phases through interference phenomena, and obtain quantum communication phase parameters at all levels of the quantum communication network. Quantum interference equipment uses components such as beam splitters, phase modulators, and beam combiners to measure phase information using the superposition and interference phenomena of quantum states. The phase characteristics of quantum states can be reflected by changes in interference fringes.

[0050] Use quantum simulators to simulate quantum behavior, simulate quantum circuits and quantum states, and obtain quantum communication amplitude parameters at all levels of the quantum communication network;

[0051] The quantum communication phase parameters are obtained by changing the quantum phase through the phase modulator of the quantum interference device to generate interference phenomenon, and the intensity distribution of the interference fringes is measured, specifically including: the maximum intensity of the interference fringes generated by each level in the quantum communication process, the minimum intensity of the interference fringes generated by each level in the quantum communication process, the fringe length of the interference fringes generated by each level in the quantum communication process, and the distance between the maximum intensity and the minimum intensity of the fringe when the interference fringes are generated by each level in the quantum communication process;

[0052] The quantum communication amplitude parameters specifically include: the amplitude value corresponding to the quantum input state of each level, the amplitude value corresponding to the quantum output state of each level, and the time for the quantum at each level to be converted from the input state to the output state.

[0053] In this embodiment, it should be specifically explained that in the quantum communication quality analysis module, the specific contents of the quantum communication quality indexes at each level obtained by performing communication quality analysis on the quantum communication network are as follows:

[0054] Step S1: Analyzing the phase attenuation in the quantum communication process based on the quantum communication phase parameters of each level of the quantum communication network to calculate the quantum phase attenuation coefficient of each level, and analyzing the amplitude attenuation in the quantum communication process based on the quantum communication amplitude parameters of each level of the quantum communication network to calculate the quantum amplitude attenuation coefficient of each level;

[0055] Step S2: Analyze the communication quality of each level through the quantum phase attenuation coefficient and quantum amplitude attenuation coefficient of each level of the quantum communication network, and obtain the quantum communication quality index of each level.

[0056] In this embodiment, it should be specifically explained that the calculation content of the quantum phase attenuation coefficient of each level is as follows:

[0057] Input the preset quantum phase into the quantum interference device, change the quantum phase through the phase modulator of the quantum interference device, generate interference phenomenon and measure the intensity distribution of interference fringes. The movement or change of interference fringes reflects the phase change of quantum state.

[0058] The quantum phase attenuation coefficient of each level is calculated based on the intensity distribution of the interference fringes. The calculation formula is: ,in represents the quantum phase attenuation coefficient at each level in the quantum communication process, It represents the maximum intensity of interference fringes generated at each level in the quantum communication process. It represents the minimum intensity of interference fringes generated at each level in the quantum communication process. Indicates the length of the interference fringes generated at each level during quantum communication, It represents the distance between the maximum and minimum intensity of the interference fringes generated at each level during quantum communication, and e represents a natural constant;

[0059] The calculation formula of the quantum amplitude attenuation coefficient of each level is: ,in represents the quantum amplitude attenuation coefficient of each level, represents the quantum decay rate of each level, Represents the amplitude value corresponding to the quantum input state at each level, Represents the amplitude value corresponding to the quantum output state of each level.

[0060] In this embodiment, it should be specifically explained that the calculation formula of the quantum decay rate of each level is: ,in represents the quantum decay rate of each level, e represents the natural constant, It represents the time for each level of quantum to transform from input state to output state, Represents the decay time constant.

[0061] In this embodiment, it should be specifically explained that the communication quality of each level is analyzed by the quantum phase attenuation coefficient and the quantum amplitude attenuation coefficient of each level of the quantum communication network, and the calculation formula of the quantum communication quality index of each level is obtained as follows: ,in represents the quantum communication quality index at each level, represents the quantum phase attenuation coefficient at each level in the quantum communication process, represents the quantum amplitude attenuation coefficient of each level, and e represents a natural constant.

[0062] In this embodiment, it should be specifically explained that in the loss function hierarchical judgment module, the quantum communication quality index of each level is substituted into the loss function model to calculate the loss difference index of each level, and the specific content of risk judgment of each level of the quantum communication network based on the loss difference index is as follows:

[0063] Substitute the quantum communication quality index of each level into the loss function model to calculate the loss difference index of each level. The calculation formula of the loss difference index is: ,in Represents the loss difference index of each level in the quantum communication process, Represents the quantum communication quality index of each level in the quantum communication process, where i=2, 3, ..., n, i represents the sequence number of the quantum communication network layer, when i=1, ;

[0064] The risk of each layer of the quantum communication network is judged according to the loss difference index of each layer during the communication process. When the loss difference index of each layer during the quantum communication process is greater than or equal to the preset risk threshold, the layer is judged to be risky. Conversely, when the loss difference index of each layer during the quantum communication process is less than the preset risk threshold, the layer is judged to be risk-free.

[0065] In this embodiment, it should be specifically explained that, in the intelligent terminal optimization warning module, risk gradient division is performed based on the risk judgment results of each level of the quantum communication network: the risk judgment result of the loss function hierarchical judgment module is received, and the risk level is divided into risk gradients: when the loss difference index of the risk level is greater than or equal to the preset warning threshold, the intelligent warning unit starts the warning setting, locates the risk level of the warning and sends the warning information to the intelligent terminal; when the loss difference index of the risk level is less than the preset warning threshold, the intelligent optimization unit formulates an optimization strategy to optimize and adjust the quantum communication network;

[0066] Optimization and adjustment include: Quantum node integration: Quantum nodes are an important part of the quantum communication network. The intelligent optimization unit will promote the integrated design of quantum nodes, improve the performance and reliability of nodes, and reduce the energy consumption and cost of nodes; Node synchronization and coordination: The synchronization and coordination between quantum nodes are crucial to the performance of the network. The intelligent optimization unit will adopt advanced synchronization algorithms and coordination mechanisms to ensure efficient and accurate information transmission between nodes.

[0067] like Figure 2 As shown, in this embodiment, it should be specifically stated that an AI-based quantum communication optimization method includes the following steps:

[0068] Step S01: hierarchically identifying the quantum communication network according to the linear topological structure of the quantum communication network;

[0069] Step S02: Obtaining quantum information at each level of the quantum communication network through the quantum computing toolbox;

[0070] Step S03: Analyze the communication quality of the quantum communication network to obtain the quantum communication quality index of each level;

[0071] Step S04: Substituting the quantum communication quality index of each level into the loss function model to calculate the loss difference index of each level, and making risk judgments on each level of the quantum communication network according to the loss difference index;

[0072] Step S05: Based on the risk assessment results of each level of the quantum communication network, the risk gradient is divided and the intelligent terminal completes the optimization warning instruction.

[0073] In this embodiment, it should be specifically explained that the difference between this embodiment and the prior art is mainly that this embodiment is provided with a quantum communication hierarchical identification module, a communication data acquisition and transmission module, a quantum communication quality analysis module, a loss function hierarchical judgment module, and an intelligent terminal optimization and early warning module. According to the linear topological structure of the quantum communication network, the quantum communication network is hierarchically identified and quantum information of each level of the quantum communication network is obtained. The communication quality of the quantum communication network is analyzed to obtain the quantum communication quality index of each level, thereby improving the reliability and efficiency of the quantum communication network. The phase attenuation and amplitude attenuation in the quantum communication process are accurately reflected through quantum analysis of different levels, thereby evaluating the stability and transmission efficiency of the quantum communication network to improve the communication quality.

[0074] The quantum communication quality index of each level is substituted into the loss function model to calculate the loss difference index of each level to complete the risk judgment of each level of the quantum communication network. The risk gradient is divided according to the risk judgment results. The intelligent terminal completes the optimization early warning instructions, responds to and handles potential risks in a timely manner, and ensures the stable operation of the quantum communication network.

[0075] Finally: The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

[0076] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art who is familiar with the present technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

Claims

1. An AI-based quantum communication optimization system, characterized by: include: Quantum communication hierarchical identification module, communication data acquisition and transmission module, quantum communication quality analysis module, loss function hierarchical judgment module, and intelligent terminal optimization and early warning module; The quantum communication hierarchical identification module performs hierarchical identification on the quantum communication network according to the linear topological structure of the quantum communication network; The communication data acquisition and transmission module acquires quantum information at each level of the quantum communication network through the quantum computing toolbox, and transmits the information to the quantum communication quality analysis module; The quantum communication quality analysis module acquires quantum information of each level of the quantum communication network transmitted by the transmission module based on the communication data, and performs communication quality analysis on the quantum communication network to obtain quantum communication quality indexes of each level; The loss function hierarchical judgment module substitutes the quantum communication quality index of each level into the loss function model to calculate the loss difference index of each level, and makes risk judgment on each level of the quantum communication network according to the loss difference index; The intelligent terminal optimization and early warning module includes an intelligent optimization unit and an intelligent early warning unit. The risk gradient is divided based on the risk judgment results of each level of the quantum communication network, and the intelligent terminal completes the optimization and early warning instructions.

2. The AI-based quantum communication optimization system according to claim 1, characterized in that: In the quantum communication hierarchical identification module, the quantum communication network is hierarchically identified according to the linear topological structure of the quantum communication network, and the quantum communication network is divided into n layers, where i=1, 2, 3, ..., n, and i represents the sequence number of the quantum communication network layer. In the linear topological structure, quantum nodes are arranged in a linear order, different quantum nodes are divided into different levels according to different heights, and adjacent nodes are connected through quantum channels.

3. The AI-based quantum communication optimization system according to claim 1, characterized in that: In the communication data acquisition and transmission module, quantum information is acquired in real time during the communication process of each level of the quantum communication network using quantum computing tools to obtain the communication environment of quantum communication, wherein the quantum information specifically includes: quantum communication phase parameters and quantum communication amplitude parameters; Use quantum interference equipment to obtain the phase characteristics of quantum states, measure quantum phases through interference phenomena, and obtain quantum communication phase parameters at all levels of the quantum communication network; Quantum simulators are used to simulate quantum behavior, simulate quantum circuits and quantum states, and obtain quantum communication amplitude parameters at each level of the quantum communication network.

4. The AI-based quantum communication optimization system according to claim 1, characterized in that: In the quantum communication quality analysis module, the communication quality analysis of the quantum communication network is performed to obtain the specific contents of the quantum communication quality indexes at each level as follows: Step S1: Analyzing the phase attenuation in the quantum communication process based on the quantum communication phase parameters of each level of the quantum communication network to calculate the quantum phase attenuation coefficient of each level, and analyzing the amplitude attenuation in the quantum communication process based on the quantum communication amplitude parameters of each level of the quantum communication network to calculate the quantum amplitude attenuation coefficient of each level; Step S2: Analyze the communication quality of each level through the quantum phase attenuation coefficient and quantum amplitude attenuation coefficient of each level of the quantum communication network, and obtain the quantum communication quality index of each level.

5. The AI-based quantum communication optimization system according to claim 4, characterized in that: The calculation contents of the quantum phase attenuation coefficients at each level are as follows: Input a preset quantum phase into a quantum interference device, change the quantum phase through a phase modulator of the quantum interference device, generate interference phenomenon and measure the intensity distribution of interference fringes; The quantum phase attenuation coefficient of each level is calculated based on the intensity distribution of the interference fringes. The calculation formula is: ,in represents the quantum phase attenuation coefficient at each level in the quantum communication process, It represents the maximum intensity of interference fringes generated at each level in the quantum communication process. It represents the minimum intensity of interference fringes generated at each level in the quantum communication process. Indicates the length of the interference fringes generated at each level during quantum communication, It represents the distance between the maximum and minimum intensity of the interference fringes generated at each level during quantum communication, and e represents a natural constant; The calculation formula of the quantum amplitude attenuation coefficient of each level is: ,in represents the quantum amplitude attenuation coefficient of each level, represents the quantum decay rate of each level, Represents the amplitude value corresponding to the quantum input state at each level, Represents the amplitude value corresponding to the quantum output state of each level.

6. The AI-based quantum communication optimization system according to claim 5, characterized in that: The calculation formula of the quantum decay rate of each level is: ,in represents the quantum decay rate of each level, e represents the natural constant, It represents the time for each level of quantum to transform from input state to output state, Represents the decay time constant.

7. The AI-based quantum communication optimization system according to claim 4, characterized in that: The communication quality of each level is analyzed by the quantum phase attenuation coefficient and quantum amplitude attenuation coefficient of each level of the quantum communication network, and the calculation formula of the quantum communication quality index of each level is obtained as follows: ,in represents the quantum communication quality index at each level, represents the quantum phase attenuation coefficient at each level in the quantum communication process, represents the quantum amplitude attenuation coefficient of each level, and e represents a natural constant.

8. The AI-based quantum communication optimization system according to claim 1, characterized in that: In the loss function hierarchical judgment module, the quantum communication quality index of each level is substituted into the loss function model to calculate the loss difference index of each level, and the specific content of risk judgment of each level of the quantum communication network based on the loss difference index is as follows: Substitute the quantum communication quality index of each level into the loss function model to calculate the loss difference index of each level. The calculation formula of the loss difference index is: ,in Represents the loss difference index of each level in the quantum communication process, Represents the quantum communication quality index of each level in the quantum communication process, where i=2, 3, ..., n, i represents the sequence number of the quantum communication network layer; The risk of each layer of the quantum communication network is judged according to the loss difference index of each layer during the communication process. When the loss difference index of each layer during the quantum communication process is greater than or equal to the preset risk threshold, the layer is judged to be risky; otherwise, the layer is judged to be risk-free.

9. The AI-based quantum communication optimization system according to claim 1, characterized in that: In the intelligent terminal optimization and early warning module, risk gradient division is performed based on the risk judgment results of each level of the quantum communication network: the risk judgment results of the loss function hierarchical judgment module are received, and the risk levels are divided into risk gradients: when the loss difference index of the risk level is greater than or equal to the preset early warning threshold, the intelligent early warning unit starts the early warning setting, locates the risk level of the warning and sends the early warning information to the intelligent terminal; when the loss difference index of the risk level is less than the preset early warning threshold, the intelligent optimization unit formulates an optimization strategy to optimize and adjust the quantum communication network.

10. An AI-based quantum communication optimization method, used to use an AI-based quantum communication optimization system according to any one of claims 1 to 9, characterized in that: The following steps are involved: Step S01: hierarchically identifying the quantum communication network according to the linear topological structure of the quantum communication network; Step S02: Obtaining quantum information at each level of the quantum communication network through the quantum computing toolbox; Step S03: Analyze the communication quality of the quantum communication network to obtain the quantum communication quality index of each level; Step S04: Substituting the quantum communication quality index of each level into the loss function model to calculate the loss difference index of each level, and making risk judgments on each level of the quantum communication network according to the loss difference index; Step S05: Based on the risk assessment results of each level of the quantum communication network, the risk gradient is divided and the intelligent terminal completes the optimization warning instruction.

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