An entropy measurement method and intelligent decision-making system for the optimal number of quantum gate manipulation experiments

Abstract

The present invention discloses an entropy measurement method for the optimal strategy of a quantum gate manipulation experimental process and an intelligent decision-making system, which belong to the field of quantum computing and AI intelligent technology. In view of the problems in the prior art that the quantum gate manipulation experimental process lacks uncertainty analysis, the algorithm has a strong dependence on indicators and requires large-scale quantum gate verification, and the optimal number of quantum gate manipulation experiments cannot be predicted, the present invention provides an entropy measurement method for the optimal strategy of a quantum gate manipulation experimental process. According to the system manipulation experimental process, an active network topology structure corresponding to the process is constructed, and the topological structure time entropy, the maximum time algorithm and the optimal number of experiments entropy measurement method are given based on the hierarchical relationship and flow direction of the topological structure information flow. The present invention provides an intelligent decision-making system, which transforms a physical system into a quantum processor from the software perspective, realizes the strategy optimization of a class of quantum gate experimental processes under uncertain conditions and the prediction of the optimal number of experiments, reduces the risk of large-scale disordered experiments, and improves decision-making efficiency.

Description

Technical Field

[0001] The present invention relates to the fields of quantum computing, quantum information manipulation and AI intelligent technology, and more specifically, to a method for determining an optimal strategy for a quantum gate experimental process, optimizing a quantum circuit search scheme, determining an optimal number of experiments for quantum information storage and manipulation, and software development and application of an intelligent decision support system for a quantum information manipulation process. Background Art

[0002] In the process of quantum state manipulation of microwave photons to achieve quantum state transformation, the optimization of large-scale quantum information manipulation schemes is very important, as it can improve the efficiency of quantum computing fidelity estimates during the transmission, processing and detection of quantum information. There are three major challenges in the optimization of large-scale quantum information manipulation schemes, quantum information fidelity manipulation experiments and quantum computing: first, how to optimize the quantum gate experimental process and quantum circuit search scheme under uncertain conditions; second, how to give the corresponding optimal number of experiments around the quantum information manipulation experimental process under uncertain conditions; third, how to optimize the large-scale quantum information manipulation process from a software perspective, transform a physical system into a quantum processor through an intelligent decision-making system, and achieve the optimal quantum information manipulation process.

[0003] At present, in related research, some adopt the empirical approach of repeated practice, and there is a lack of analysis of uncertain factors in the process of systematic manipulation experiment, and it is difficult to make correct judgments on the advance prediction of the manipulation experiment. In order to prevent large-scale quantum gate testing, some adopt quantum circuit structure search algorithm. This algorithm depends on the structure and path of the tree-shaped super network space search space tree, depends on the weight values ​​in different path nodes, and it is more difficult to determine the weight value under uncertain conditions. Some use quantum random walk algorithm to optimize quantum circuits. In large-scale sampling, the quantum walk method is a random walk that represents the transfer probability with probability amplitude. The probability amplitude cannot fully reflect the uncertainty, and the strategy optimization still has uncertainty. Some use the optimal quantum information manipulation method based on local manipulation. This method is positively correlated with the precision of the multi-parameter experimental platform. The instability of the quantum state is still constrained by hardware, making it very difficult to manipulate. The quantum physical system manipulates the software system, and this method is also not feasible.

[0004] The optimal strategy decision for the quantum gate experimental process, the optimization of the quantum circuit search scheme, and the determination of the optimal number of experiments for quantum information storage and manipulation are directly related to the efficiency of quantum computing fidelity during quantum information acquisition, transmission, processing and detection. In order to avoid the blindness of large-scale quantum information manipulation and quantum circuit verification under uncertain conditions, corresponding algorithms must be given.

[0005] In order to correct errors through software, transform a physical system into a quantum processor, and make intelligent decisions such as optimal strategy decisions for a type of quantum gate experimental process under uncertain conditions, optimal quantum circuit search scheme optimization, and determination of the optimal number of experiments for quantum information storage and manipulation, it is necessary to build an intelligent decision-making system for quantum information manipulation. Summary of the invention

[0006] 1. Technical issues to be solved

[0007] In view of the uncertainty of the quantum information manipulation experimental process in the prior art, the optimal strategy decision directly affects the accuracy and timeliness of quantum computing; the probability determined by a certain input statistical analysis of multiple quantum bits is uncertain, and the existing quantum circuit strategy optimization method superimposes this uncertainty; in the large-scale gate manipulation experimental space, the quantum fidelity achievement effect is constrained by the hardware and is positively correlated with the precision of the platform, and it cannot well solve how to transform a physical system into a quantum processor. The present invention provides an entropy measurement method for the optimal number of quantum gate manipulation experiments and an intelligent decision-making system. The method is used to give algorithms such as the timeliness, time-effectiveness entropy, and total time-effectiveness entropy of the quantum information manipulation process under uncertain conditions, and the algorithm is used to give an entropy measurement method for the quantum information manipulation experimental process and a method for determining the optimal number of experiments for the quantum information manipulation process, and is applied to the development of an intelligent decision-making system for optimal strategy decision of a class of quantum gate experimental processes, optimal quantum circuit search scheme optimization, and optimal number of experiments for quantum information storage manipulation, and optimizes large-scale quantum gate inspections from the software perspective, transforms a physical system into a quantum processor, and realizes the optimal strategy of the experimental process and the optimal quantum circuit search scheme. The theory and method provided by this invention are of great significance for optimizing the experimental process of quantum information manipulation, predicting the optimal number of quantum information manipulation experiments in advance, and improving the efficiency of quantum information manipulation experiments.

[0008] 2. Technical solution

[0009] The purpose of the present invention is achieved by providing the following technical solutions.

[0010] The optimal number entropy measurement method for quantum gate manipulation experiments includes:

[0011] The constraints and general rules for optimizing the quantum information manipulation process are proposed. The main contents are summarized as follows: Constraints: The constraints determined by the quantum information manipulation experimental process (hereinafter referred to as the quantum information manipulation process) are the basic principles that must be followed in constructing the quantum information manipulation process, mainly including the logical structure, experimental manipulation process and experimental method of the quantum information manipulation process. The logical structure of the quantum information manipulation process is the logical process of the manipulation experiment to complete the fidelity of quantum information (such as the quantum chip parameter calibration logic process, the superconducting quantum chip real-time automatic calibration logic process, the quantum bit gate calibration logic process, etc.), that is, the experimenter designs the system to read the quantum information system to complete a task, and the order of the test experiments performed. The experimental manipulation process structurally specifies the basic direction of the quantum information flow and is the basis for the formation of the quantum information manipulation process. The experimental manipulation method is the basic way for the experimenter to complete the collaboration and conflict resolution process in the acquisition of the experimental manipulation process. Different experimental manipulation methods produce different collaboration processes. The constraints of the collaboration process and the collaboration relationship restrict the basic direction of the quantum information flow.

[0012] General rule: The quantum information manipulation process has a strong sequential nature. Generally speaking, the preceding work in the quantum information manipulation process is the basis for the subsequent work to begin. However, the preceding work often cannot meet the requirements of the subsequent work at once. Therefore, when the preceding work cannot meet the requirements of the subsequent work, such as when objective conditions such as time or other constraints allow, the preceding work will be revised (partially revised) in accordance with the requirements of the subsequent work. This phenomenon is called a "feedback" in the quantum information manipulation experiment, and the initial node at this time is called the feedback node. Obviously, there must be "feedback" in the quantum information manipulation experiment. This is based on the fact that the quantum information manipulation process has a strong sequential nature, such as the entanglement phenomenon between quantum bits. In atomic or photon state control activities, when the preceding work cannot meet the requirements of the subsequent work, the preceding work may be partially revised in accordance with the requirements of the subsequent work, that is, "feedback".

[0013] The activity network topology structure of the quantum information manipulation process is constructed, and the main contents are summarized as follows:

[0014] For any quantum information manipulation experiment, its physical meaning can be ignored, and the quantum information manipulation experiment process can be abstracted into the operation of the system quantum information flow, and its active network topology can be constructed based on the relationship between the task flows in the system quantum information manipulation experiment. When the quantum information flow passes through the node n times, the flow is n. In this way, based on the quantum information manipulation experiment process, only the connection relationship between the nodes of the information flow and the order between the hierarchical nodes are considered, and the active network topology of the quantum information manipulation experiment process is abstracted. The optimization problem of the quantum information manipulation experiment process is transformed into the problem of optimizing the information flow of the quantum information flow through the topological structure (as shown in the attached manual). Figure 2 ).

[0015] An algorithm for determining the time entropy of quantum information manipulation process under uncertain conditions is given. The main contents are summarized as follows:

[0016] Starting from the principle of quantum information entanglement, based on the movement path of atomic or photon states and the experimental process of quantum information manipulation, "entropy" is introduced as a powerful tool for describing uncertainty states into the timeliness measurement of the experimental process of quantum information manipulation, and the "time-dependent entropy" of the topological structure is used as a powerful tool for describing uncertainty states.

[0017] In the topological structure of the quantum information manipulation process, the total flow of arcs between the nodes of the cut is called the connection degree of the cut. For example, for the i-th subprocess, the connection degree of the j-th cut is denoted as l ij . ij The calculation is determined by the shortest path of the total flow of arcs between cut nodes. The length of the direct connection is 1, and the length increases by 1 each time it is transferred.

[0018] The span number k of nodes in the topological structure graph of the quantum information manipulation process is called the connection number, which corresponds to the set of natural numbers.

[0019] In the topological structure diagram of the quantum information manipulation process, when the number of connections is k, the corresponding connection degree of the cut is l ij ,say is a topological microstate, and

[0020] In the topological structure of quantum information manipulation process, if there are i sub-processes, each sub-process is divided into j cuts, and the microscopic state is L ij , called A t is the total connection degree of the process, and

[0021] In the topological structure of quantum information manipulation process, the measure of uncertainty in the timeliness of information flow is the timeliness entropy of quantum information manipulation process, denoted as and in, is the probability of achieving the connection between nodes when the number of connections is k, the i-th subprocess, and the j-th cut:

[0022] The steps for calculating the time entropy of the control process are as follows:

[0023] Step 1: Calculate the topological structure (or active network structure) corresponding to the quantum chip parameter calibration process, and the connection degree l ij ;

[0024] Step 2: Calculate the connection number k of the nodes in the cut;

[0025] Step 3: Calculate the microscopic state L ij ;

[0026] Step 4: Calculate the total connection degree A t ;

[0027] Step 5: Calculate the time-dependent entropy

[0028] The algorithm of time efficiency value of quantum information manipulation experimental process under uncertain conditions is given, and the main contents are summarized as follows:

[0029] In a certain quantum information manipulation process, the speed at which quantum information flows during quantum information transmission is measured is called the timeliness of the quantum information manipulation process.

[0030] In the topological structure of quantum information manipulation process, the total time entropy of the ith subprocess is called and Among them, n is the number of sub-processes contained in the process; m is the number of cuts in the topological structure of the quantum information manipulation process, and k is the number of connections.

[0031] If the microscopic state of n sub-processes in the topological structure of quantum information manipulation process is A max is the maximum connection degree, and

[0032] say The maximum time-effective entropy of the topological structure of the quantum information manipulation process, and in,

[0033] The time limit of the ith subprocess of the quantum information manipulation process is called R i ,and Among them, K i (x) is a function of the number of feedbacks x of the ith subprocess of the topological structure of the quantum information manipulation process, is the time-effectiveness entropy of the ith subprocess, is the maximum time-effective entropy of the ith subprocess.

[0034] The steps for calculating the timeliness of the control process are as follows:

[0035] Step 1: Calculate the total time-dependent entropy of the topological structure of the quantum information manipulation process

[0036] Step 2: Calculate the maximum connection degree A max ;

[0037] Step 3: Calculate the maximum time-dependent entropy

[0038] Step 4: Calculate the time R i ;

[0039] Step 5: Calculate the total time RT .

[0040] The relationship between the topological feedback function and the timeliness measure is summarized as follows:

[0041] Let's record the total duration of the quantum fidelity flow as R T , define the maximum time of quantum fidelity flow corresponding to the maximum cut U as R max , the maximum flow in the network W is determined by the flow of the cut. Obviously, W is also the maximum cut, so the maximum time effect should be the same as the total time effect, that is, R max =R T .

[0042] The relationship between the optimal number of experiments and the feedback function can be summarized as follows:

[0043] The optimal number of experiments in the quantum information manipulation process can be determined by the maximum number of feedbacks in the corresponding active network topology. Assume that the active network W corresponding to the quantum information manipulation process is W. By analyzing the relationship between the feedback function of the topology structure and the time efficiency measure, it can be obtained that the maximum flow in the network is determined by the flow of the cut, and obviously W is also the maximum cut.

[0044] A table showing the relationship between the optimal number of experiments and the time efficiency measure of the active network for the quantum information manipulation process with feedback is given (Table 1). The main contents are summarized as follows:

[0045] Table 1 List of the relationships between the optimal number of experiments and time effectiveness measures

[0046]

[0047] It can be seen from Table 1 that, in the absence of feedback, the greater the total time efficiency of the quantum chip parameter calibration system, the more stable the topological structure of the quantum chip parameter calibration flow, and the higher the efficiency of the quantum information manipulation experiment.

[0048] The entropy measurement method calculates the optimal number of experiments for the control process. The steps are as follows:

[0049] Step A: Calculate the time efficiency of the topological structure sub-process of the quantum information manipulation process:

[0050]

[0051] Step B: Give the relationship between system time efficiency and feedback function:

[0052]

[0053] Step C: Give the optimal number of quantum information manipulation processes to meet the following conditions:

[0054]

[0055] Step D: Determine the number of feedback nodes in the quantum information manipulation process:

[0056]

[0057] Given Q N The optimal number of experiments for quantum information manipulation process to achieve quantum information fidelity under uncertain conditions.

[0058] The main contents of the intelligent decision support system for quantum information manipulation process optimization and optimal number of experiments are summarized as follows:

[0059] Based on the entropy measurement method for the optimal number of quantum gate manipulation experiments, an intelligent decision-making system for the manipulation process is constructed. It is of great significance to improve the efficiency of quantum information manipulation experiments by optimizing the experimental process and determining the optimal number of experiments around the process.

[0060] The intelligent decision-making prototype system of the optimal number entropy measurement method for quantum gate manipulation experiments includes a manipulation experiment strategy library system, a quantum information database system, a manipulation experiment optimization management system, an information display monitoring system, etc.

[0061] Manipulation experiment strategy library system, including,

[0062] Recording module A: records the characteristic information and quantity of quantum information storage and manipulation schemes;

[0063] Processing module B: standardization of pre-assessment scheme information;

[0064] Calling module C: calling the optimization plan to be evaluated according to the authority;

[0065] Storage module D: stores historical quantum information storage manipulation plans and plans to be evaluated.

[0066] Policy information database system, including,

[0067] User layer: It can simultaneously meet the needs of users who need information storage, simulation data, test data, and optimization statistics for interaction. It is also the part of the control experiment strategy library that communicates with the database in each functional module.

[0068] Application server layer: The application server layer is the middle layer set up between the database and the user layer, which uniformly manages user access to the database and protects the security and work efficiency of the database. Database management includes user and authority management, and different users are assigned different authorities; knowledge base management is the management and maintenance of databases, information statistics databases, etc., including the addition, deletion, editing and query of information. The user interface is connected to the database through the middle layer.

[0069] Data layer: used to store a large amount of data related to the decision support system. The data layer mainly includes the experimental original database, analysis model database, and information classification database. That is, the part of the control experiment strategy library that communicates with the database in each functional module.

[0070] Manipulate the experiment optimization management system, including:

[0071] Recording module a: records the control process information and the corresponding topological structure nodes, levels, cuts, connections, micro-states and other quantitative information;

[0072] Analysis module b: Analyze and judge tasks, classify tasks into optimization of experimental strategy flow or determination of optimal number of experiments, and analyze and obtain the types and quantities of corresponding parameters;

[0073] Analytical module c: Analyze the relationship between the topological structure feedback function and the time measurement; Analyze the relationship between the optimal number of experiments and the feedback function;

[0074] Prediction module d: determine the type of manipulation experiment strategy process optimization or the optimal number of experiments;

[0075] Computation module e: Apply the entropy measurement method of the quantum information manipulation experimental process under uncertain conditions and enter the computation module e1 or computation module e2;

[0076] Calculation module e1: Apply the time entropy algorithm steps of the quantum information manipulation experimental process to calculate the process optimization time value;

[0077] Calculation module e2: Apply the algorithm steps of the optimal number of experiments in the quantum information manipulation experiment process to calculate the optimal number of experiments;

[0078] Statistical module f: time entropy of quantum information manipulation experimental process, optimal number of experiments of quantum information manipulation experimental process;

[0079] Storage module h: quantum information manipulation experimental process optimization time value or optimal number of experiments value;

[0080] Information display monitoring system, including,

[0081] State display module D: Displays the initial state of input data and the data of the intermediate operation process;

[0082] Monitoring and display module E: quantum information manipulation experiment process optimization calculation process display and quantum information manipulation experiment process optimization calculation process display;

[0083] Control display module F: quantum information manipulation experiment process optimization time value or display of the optimal number of experiments.

[0084] 3. Beneficial effects

[0085] Compared with the prior art, the advantages of the present invention are:

[0086] (1) The present invention provides an entropy-based measurement method for the optimal number of quantum gate manipulation experiments. "Entropy" is used as a powerful tool to describe the uncertainty state and is introduced into the timeliness measurement of the quantum information manipulation experimental process. An active network topology structure based on the quantum information manipulation experimental process is proposed, and the "timeliness entropy" of the topological structure is used as the uncertainty measurement of the quantum information manipulation experimental process, which improves the scientificity and credibility of the optimization of the quantum information manipulation experimental process.

[0087] (2) The present invention provides a method for determining the optimal number of experiments for optimizing the quantum information manipulation process, points out the relationship between the feedback function of the topological structure of the quantum information manipulation process and the time measurement, and the relationship between the optimal number of experiments and the feedback function, and provides an algorithm for the optimal number of experiments under uncertain conditions, thereby reducing the uncertainty of large-scale quantum gate manipulation and the complexity of large-scale sampling.

[0088] (3) The present invention provides an intelligent decision-making system for optimizing the quantum information manipulation process and determining the optimal number of experiments. Based on a new entropy-based measurement algorithm for the optimal number of quantum gate manipulation experiments, an intelligent decision-making prototype system is developed to reduce the previous infeasible method of improving processor hardware, which can only lead to errors, and improve the accuracy and computational efficiency of quantum information manipulation and intelligent decision support.

[0089] (4) The method and intelligent decision-making system of the present invention can also be applied to other control process manipulation experiments such as quantum information acquisition and quantum information storage, such as quantum chip structure scheme manipulation experiments and quantum bit gate calibration manipulation experiments, medium-scale superconducting manipulation experiments based on quantum networks, and other intelligent decision support systems for determining the optimal number of experiments, providing a theory, method and means for quantum information system strategy optimization under uncertain conditions. BRIEF DESCRIPTION OF THE DRAWINGS

[0090] Figure 1 A summary diagram of the optimal number entropy measurement method and intelligent decision-making system for quantum gate manipulation experiments provided by the present invention;

[0091] Figure 2 The network topology structure of the quantum information manipulation experimental process provided by the present invention;

[0092] Figure 3 A flow chart of the intelligent decision-making system for the optimal number of entropy measurement methods for quantum gate manipulation experiments provided by the present invention;

[0093] Figure 4 Example 1 provided for the invention - quantum chip parameter calibration flow chart;

[0094] Figure 5 The topological diagram of the process of quantum chip parameter calibration provided by the present invention is shown in Example 1.

[0095] Figure 6 The present invention provides Example 1 - the overall flow chart of the entropy measurement method control experiment optimization management decision system. DETAILED DESCRIPTION

[0096] In order to make the theoretical achievements, technical routes and innovations of the present invention more clear, the theoretical achievements and technical routes of the present invention will be clearly and completely described below in conjunction with the accompanying drawings of the present invention.

[0097] First, refer to the instruction manual Figure 1 , the present invention is described in detail.

[0098] See attached Figure 1 As shown, any quantum information manipulation experiment is a quantum physical system. The manipulation of the quantum physical system by the manipulation experiment process, the quantum control ability of the software, and the calculation accuracy directly determine whether the quantum gate can achieve the characteristic of quantum state fidelity. The present invention provides the optimal entropy measurement method for quantum gate manipulation experiments to achieve prior optimization analysis. Based on the quantum information manipulation experiment process, the uncertainty of the quantum information manipulation experiment process under the complex and changeable multi-physical field coupling is analyzed, and the constraints and general rules for the optimization of the quantum information manipulation process are proposed; ignoring its physical meaning, the quantum information manipulation experiment process is abstracted into the operation of information flow, and relying on the relationship between task flows in the system quantum information manipulation experiment, only the connection relationship between each node of the information flow and the order between hierarchical nodes are considered, and the active network topology of the quantum information manipulation experiment process is abstracted, and the optimization problem of the quantum information manipulation experiment process is transformed into the problem of optimizing the information flow of quantum information flow through the topological structure.

[0099] Classify intelligent decision-making tasks, optimize the experimental process or determine the optimal number of experiments.

[0100] Starting from the principle of quantum information entanglement, based on the movement path of atomic or photon states and the experimental process of quantum information manipulation, "entropy" is introduced as a powerful tool for describing uncertain states into the measurement of the timeliness of the experimental process of quantum information manipulation. The "time-effective entropy" of the topological structure is used as a powerful tool for describing uncertain states. The concepts of system traversal of microscopic states, degree of connection, and timeliness are proposed. The time-effective entropy of the topological structure, the maximum time-effective entropy, and the time-effective algorithm are given as an algorithm for determining the timeliness of the quantum information manipulation process under uncertain conditions.

[0101] Analyze the relationship between the feedback function of the topological structure of the control experiment process and the timeliness measurement, and give the timeliness R i And the experimental feedback function K i (x) satisfies the relation

[0102] When the quantum information manipulation process has "feedback" on the i-th sub-process and needs to repeat all the activities of this process, the time limit is recorded as Feedback function K i (x) The maximum number of feedbacks meets the following conditions: In particular, when discussing a quantum information manipulation process with only one sub-process, n=1; when the quantum information manipulation process is only regarded as a cut, m=1; when any node in the quantum information manipulation process does not have a path and the span is greater than 1, k=1.

[0103] Analyze the relationship between the optimal number of experiments and the feedback function, and give the optimal number of experiments Q for system control experiments N Entropy-based measurement algorithm.

[0104] If the feedback process is only completed in a part of an activity network, the part containing the feedback process is treated as a sub-process and the algorithm is the same. i (x) The maximum number of feedback times satisfies the following formula:

[0105]

[0106] Take the maximum value of both sides:

[0107] The optimal number of experiments for quantum information fidelity under uncertainty is Q w (that is, the number of feedbacks of the active network W), obviously, for any i,

[0108]

[0109]

[0110] Construct an intelligent decision-making prototype system based on the entropy measurement method for the optimal number of quantum gate manipulation experiments, which includes a quantum information manipulation experiment strategy library system, a quantum information database system, a manipulation experiment optimization management system, and an information display and monitoring system.

[0111] The paper also provides an empirical example 1: "Quantum chip parameter calibration flow chart" verification application. The entropy measurement method and intelligent decision-making system for the optimal number of quantum gate manipulation experiments are applied to transform the manipulation experiment optimization system into a quantum processor, thus solving the intelligent decision-making problem of quantum information manipulation experiments from the software perspective.

[0112] In conjunction with the instruction manual Figure 2 , the present invention is described in detail.

[0113] Figure 2 This is the network topology diagram of the quantum information manipulation experiment process, refer to Figure 2As shown, any quantum information manipulation experimental process can ignore its physical meaning and abstract the quantum information manipulation experimental process into a quantum information system flow activity network, and construct its activity network topology based on the relationship between task flows in the quantum information manipulation experiment. When the quantum information flow passes through the node n times, the flow is n. In this way, the quantum information manipulation experimental process is transformed into the problem of the information flow of quantum information flow through the topological structure.

[0114] In conjunction with the instruction manual Figure 3 , the present invention is described in detail.

[0115] Figure 3 The flow chart of the entropy measurement method intelligent decision-making system for the optimal number of quantum gate manipulation experiments is a process that describes the prototype system of the optimal strategy entropy measurement intelligent decision-making platform, which operates according to the relationship between the workflow and information flow. The optimal number of quantum gate manipulation experiment intelligent decision-making platform, quantum computing network server platform and display platform are controlled according to the flow direction of the information control flow; there is an interactive relationship between the strategy information database system and the manipulation experiment strategy library system, the manipulation experiment optimization management system and the information display monitoring system, and the quantum information display monitoring system relies on the relevant software support in the manipulation experiment optimization management system and has a dependent relationship; the internal work of each subsystem in the optimal strategy entropy measurement intelligent decision-making platform points to input and output according to the information operation flow.

[0116] Give the attached Figure 4 "Example 1 - Quantum chip parameter calibration flow chart", and attached Figure 5 "Example 1 - Quantum chip parameter calibration process topology diagram", given in the instruction manual Figure 6 Example 1 - Entropy measurement method is used to manipulate the overall flow chart of the experimental optimization management decision system. The application method of the algorithm of the present invention is described, and the calculation results are shown in Table 2.

[0117] According to the attached Figure 4 The quantum chip parameter calibration flow chart relies on the relationship between quantum information flow layers and builds an additional Figure 5 Topological diagram of quantum chip parameter calibration process.

[0118] Recording module a of the intelligent decision-making system through entropy measurement method: record the quantity information of the topological structure of the control process;

[0119] By analyzing module b: determining the types and quantities of topological structure parameters corresponding to the quantum chip parameter calibration process tasks;

[0120] Through the analysis module c: analyze the relationship between the topological structure feedback function and the time measurement, and the relationship between the optimal number of experiments and the feedback function;

[0121] Through the prediction module d: the instance prediction is divided into two operations: optimization of quantum chip parameter calibration process and determination of the optimal number of experiments;

[0122] Through the calculation module e1: the entropy measurement method for optimizing the control experiment process is applied to optimize the quantum chip parameter calibration process, and the process time entropy calculation algorithm is used. The steps are as follows:

[0123] Step 1: Calculate the topological structure (or active network structure) corresponding to the quantum information manipulation process, and the connection degree l ij ;

[0124] Step 2: Calculate the connection number k of the nodes in the cut;

[0125] Step 3: Calculate the microscopic state L ij ,

[0126] Step 4: Calculate the total connection degree A t ,

[0127] Step 5: Calculate the time-dependent entropy

[0128] Step 6: Calculate the total time R T , R max =R T .

[0129] Through the calculation module e2: the optimal number of manipulation experiments is determined by the entropy measurement method, and the optimal number of quantum chip parameter calibration process is solved. The time value of the quantum chip parameter calibration process of the storage module is called to calculate the time efficiency of the sub-process; according to the relationship between the topological structure feedback function and the time efficiency measurement, and the relationship between the optimal number of experiments and the feedback function, a method for determining the optimal number of computational manipulation experiments is given.

[0130] The calculation steps are as follows:

[0131] Step A: Calculate the time efficiency of the quantum chip parameter calibration sub-process:

[0132]

[0133] The time limit of the ith subprocess of the quantum chip parameter calibration process is denoted as R i , K i (x) is a function of the number of feedbacks x of the ith subprocess of the topological structure of the quantum information manipulation process, is the time-effectiveness entropy of the ith subprocess, is the maximum time-effective entropy of the ith subprocess.

[0134] Step B: Give the relationship between system time efficiency and feedback function:

[0135]

[0136] Step C: Give the optimal number of times to meet the conditions:

[0137]

[0138] Step D: Determine the number of feedback nodes in the quantum chip parameter calibration process:

[0139]

[0140] Q N This quantum chip parameter calibration process can achieve the optimal number of experiments for quantum information fidelity under uncertain conditions.

[0141] The above results are given in Table 2.

[0142] Table 2 List of optimal number of experiments for quantum information fidelity flow under uncertain conditions

[0143]

[0144] It can be obtained from Table 2 that the smaller the total time measurement value of the system, the more times the feedback is given, which indicates that the degree of order of the given "quantum chip parameter calibration process" is lower. Therefore, in the experiment of reading the quantum fidelity manipulation process, the quantum information storage error and quantum information calculation error should be minimized as much as possible, the feedback of the control process of obtaining the quantum fidelity manipulation process should be reduced, and the timeliness of the quantum chip parameter calibration system should be improved.

[0145] The invention and its implementation methods are described schematically above, and the description is not restrictive. Without departing from the spirit or basic features of the invention, the invention can be implemented in other forms. Obviously, the implementation verification example described is a part of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by researchers in this field without making creative work are within the scope of protection of the present invention.

Claims

1. An optimal entropy measurement method for quantum gate manipulation experiments, characterized in that: The steps are as follows, Step 1: Abstract the topological structure corresponding to the quantum information manipulation process and calculate the connection degree of the jth cut in the i-th sub-process, denoted as l ij , l ij The calculation of is determined by the shortest path of the total flow of arcs between cut nodes. The length of the direct connection is 1, and the length increases by 1 each time it is transferred. Step 2, calculating the connection number k of the nodes in the cut, where the connection number k is the number of spans of the nodes in the cut of the quantum information manipulation process topology structure diagram; Step 3: Calculate the microscopic state of the topological structure Step 4: Calculate the total connection degree A of the quantum information manipulation process t , Step 5: Calculate the time entropy of the quantum information manipulation process in, is the probability of achieving the connection between nodes of the jth cut in the i-th sub-process with the connection number k; Step 6: According to the time-dependent entropy in step 5 Calculating the total time-dependent entropy of the topological structure of the quantum information manipulation process Wherein, i = 1, 2, 3, 4, ..., n; n is the number of sub-processes in the process; m is the number of cuts in the topological structure of the quantum information manipulation process, and k is the number of connections; Step 7: According to the total connection degree A in step 4 t Calculate the maximum connection degree A max , Step 8: According to the maximum connection degree A in step 7 max , calculate the maximum time-effectiveness entropy of the i-th subprocess Step 9: Calculate the time efficiency R of the i-th sub-process i , Where i = 1, 2, 3, 4, ..., n; K i (x) is a function of the number of feedbacks x of the ith subprocess of the topological structure of the quantum information manipulation process; Step 10: Calculate the process optimization time value R T , R T =R max ; R max The maximum time efficiency of the quantum fidelity flow corresponding to the maximum cut; Step 11: Based on step 9, the relationship between system timeliness and feedback function is given. Step 12: According to step 9, the optimal number of feedback times of the topological structure corresponding to the quantum information manipulation process meets the conditions. Among them, Q w The number of feedback nodes of the topological structure of the quantum information manipulation process; Step 13: Determine the number of feedbacks for the quantum information manipulation process. Q N For Round up, Q N The optimal number of quantum gate manipulation experiments.

2. A prototype system of an intelligent decision-making platform for the optimal number of quantum gate manipulation experiments, characterized in that: The system architecture includes a strategy information database system, a manipulation experiment strategy library system, a manipulation experiment optimization management system based on the entropy measurement method for the optimal number of quantum gate manipulation experiments described in claim 1, and an information display monitoring system. Information is exchanged between the strategy information database system and the manipulation experiment strategy library system, and there is a dependency relationship between the manipulation experiment strategy library system and the manipulation experiment optimization management system; information is exchanged between the manipulation experiment optimization management system and the information display monitoring system.

3. According to claim 2, the prototype system of the intelligent decision-making platform for the optimal number of quantum gate manipulation experiments is characterized by: The manipulation experiment strategy library system includes: Recording module A: records the characteristic information and quantity of quantum gate manipulation experimental schemes; Processing module B: standardize the information of pre-evaluated quantum gate manipulation experimental schemes; Calling module C: calling the optimization plan to be evaluated according to the authority; Storage module D: stores historical quantum gate manipulation experimental plans and optimization plans to be evaluated.

4. According to claim 2, the prototype system of the intelligent decision-making platform for the optimal number of quantum gate manipulation experiments is characterized by: The manipulation experiment optimization management system includes: Recording module a: records the control process information and the quantum information control process topological structure nodes, levels, cuts, connection degrees, microscopic states and other quantitative information; Analysis module b: Analyze and judge tasks, classify tasks into optimization of experimental strategy flow or determination of optimal number of experiments, and analyze and obtain the types and quantities of corresponding parameters; Analysis module c: Analysis of the feedback function K of the topological structure of the quantum information manipulation process i (x) and time R i ; Analyze the optimal number of experiments and feedback function K i (x) the relationship between them; Prediction module d: determine the type of manipulation experiment strategy process optimization or the optimal number of experiments; Computation module e: applying the optimal number entropy measurement method step of the quantum gate manipulation experiment described in claim 1, and transferring to calculation module e1 or calculation module e2; Calculation module e1: applying the optimal number entropy measurement method step of the quantum gate manipulation experiment described in claim 1 to calculate the process optimization time value; Calculation module e2: applying the entropy measurement method step of the optimal number of quantum gate manipulation experiments described in claim 1 to calculate the optimal number of experiments; Statistics module f: Statistics of the time entropy of the quantum information manipulation experimental process and the optimal number of experiments in the quantum information manipulation experimental process; Storage module h: stores the optimization time value or the optimal number of experiments of the quantum information manipulation experiment process.

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