A fractal algorithm and verification device system for determining the cardinality of quantum gate test measurement

Abstract

The present invention discloses a fractal algorithm and verification device system for determining the cardinality of quantum gate inspection and measurement, which belong to the field of quantum computing and AI intelligent technology. In view of the problem in the prior art that large-scale quantum gate inspection is required for manipulating microwave photons to perform superposition and entangled state processes, the present invention provides a fractal algorithm and verification device system for determining the cardinality of quantum gate inspection and measurement. According to the established mathematical model of the fractal dimension of the experimental space as the estimated value of the number of quantum gate inspection and measurement bases, a fractal algorithm based on the self-similar structure of the experimental space and a fractal algorithm based on the sparse state of the experimental space are given. The verification device platform using the algorithm has a prototype system including a recording module, an analysis module, a parsing module, a prejudgment module, a calculation module and a display module. According to this verification device system, a verification and measurement system can be transformed into a quantum processor, and large-scale quantum gate inspections can be optimized from the software perspective to achieve the determination of the measurement cardinality of quantum gate inspections.

Description

Technical Field

[0001] The present invention relates to the field of quantum computing and AI intelligent technology, and more specifically, to a type of quantum gate inspection measurement cardinality determination, a quantum gate inspection measurement verification device, an AI intelligent decision-making system, and an application method. Background Art

[0002] In the process of quantum state manipulation of microwave photons to achieve quantum state transformation, it is very important to predict the number of quantum gate test measurement bases. It can reduce the number of times the unitary matrix is ​​decomposed into the second-order ground state matrix, control the number of experiments to complete the superposition state and entangled state of microwave photons, and improve the efficiency of quantum computing fidelity estimation. There are three major problems in the optimization of large-scale quantum gate test schemes: First, due to the uncertainty complex system of microwave photons in chaotic motion under superconducting conditions, large-scale quantum gate tests must make the quantum computing fidelity reach the preset value, characterize the number of quantum gate test measurement bases, and how to estimate it in advance? Second, how to use fewer quantum gates, while ensuring a certain number of quantum gate test measurement bases, meet the reality of the self-similar structure and sparse state of the experimental space, and provide a more scientific calculation method; third, how to optimize large-scale quantum gate tests from the software perspective, transform a physical system into a quantum processor through a verification device, and realize the determination of the quantum gate test measurement base.

[0003] At present, in related research, some use quantum tomography to conduct a large number of repeated experimental measurements and estimates, and measure the same Rabi curve (Rabi) frequency sequence hundreds or thousands of times, and make statistical judgments on the probability of the measurement results. However, when the number of quantum bits increases to a scale that is difficult to meet exponential growth, the number of quantum gate verification measurement experiments will also be exponential, which is difficult to achieve. In order to prevent large-scale quantum gate verification, some use the optimal quantum gate verification method based on local operations. This method is positively correlated with the precision of the multi-parameter quantum measurement platform. This method is still constrained by hardware. The quantum physical system controls the software system, so this method is also not feasible.

[0004] The number of measurement bases in the quantum gate verification process is directly related to large-scale quantum gate verification. In order to achieve advance prediction, the corresponding algorithm must be given to determine the number of measurement bases in the quantum gate verification process and abandon the blindness of large-scale quantum gate verification and quantum circuit verification.

[0005] In order to correct errors from the software and transform a physical system into a quantum processor, it is necessary to build a prototype system of quantum gate test measurement basis verification device starting from the experimental space. Based on this verification device system, large-scale quantum gate test is optimized from the software, a physical system is transformed into a quantum processor, and the determination of quantum gate test measurement basis is realized. Summary of the invention

[0006] 1. Technical issues to be solved

[0007] In view of the fact that the number of quantum gate test measurement experiments in the prior art is exponential, it is difficult to make statistical judgments on the probability of the same Rabi curve (Rabi) frequency measurement result; the probability determined by a plurality of quantum bits through a certain input statistical analysis has uncertainty, and the quantum bit representation cannot well reflect this uncertainty; the multi-parameter quantum measurement method is constrained by the hardware and is positively correlated with the precision of the platform, and cannot well solve how to transform a physical system into a quantum processor. The present invention provides a method for calculating the fractal dimension of the quantum gate test experiment space as an estimate of the number of quantum gate test measurement bases and a method for designing a prototype system of an experimental verification device. The method is used to provide a fractal algorithm based on the self-similar structure of the quantum gate test experiment space and a fractal algorithm based on the sparse state of the quantum gate test experiment space, and is applied in the development of a quantum gate test measurement base number intelligent decision support system, which optimizes large-scale quantum gate tests from the software perspective, transforms a physical system into a quantum processor, and realizes the determination of the estimated value of the quantum gate test measurement base. The theory and method provided by the invention improve the scientificity, credibility and operational efficiency of large-scale quantum gate test measurement intelligent decision-making.

[0008] 2. Technical solution

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

[0010] A fractal algorithm for determining the cardinality of quantum gate test measurements, including,

[0011] The main contents of the spatial analysis and topological structure of microwave photon controlled motion are summarized as follows:

[0012] Chaos is a fractal in time, and fractals are chaos in space; the world is nonlinear, and fractals are everywhere. Fractals are a mathematical construct, which means that the parts are similar to the whole in some way. Simply put, fractals are the study of infinitely complex structures with self-similarities. According to the self-similarity of fractal theory, this similarity can be completely the same in shape or similar in a statistical sense, but most fractals are statistically similar.

[0013] Microwave photons are indivisible units in the microscopic world. The manipulation of quantum bits is a process of quantum gate physics realization and a method of realizing quantum computing. According to the basic principles of quantum mechanics, all possible states of the measured system can be described by the Hilbert space of the complete complex inner product space. The inner product is a positive, conjugate symmetric, semi-conjugate linear and semi-linear binary function on the linear space. It brings orthogonality, length, and topology to the linear space. For infinite-dimensional space, topology determines the structure of space, and the structure also brings a mathematical structure-fractal. The generation of fractals in a mathematical sense is based on an iterative equation, that is, a recursive feedback system. The fractal dimension is the most basic quantity that quantitatively represents self-similar random shapes and phenomena. Fractals are the exploration of the inherent mathematical order under the complex surface of nature. Therefore, the quantum gate test space Θ fractal for superposition and entanglement states of microwave photons can be regarded as the exploration of the real mathematical structure of chaotic motion such as microwave photon transition, entanglement, and superposition in the quantum gate test space Θ.

[0014] The application value of quantum gate verification and measurement of the estimated number of ground states is summarized as follows:

[0015] Quantum states are generally non-classical superposition states, and the results of their measurements are random variables distributed according to the probability amplitude of each basis vector that constitutes them. Therefore, once the number of measurement bases in the quantum gate verification process is determined, the blindness of large-scale quantum gate verification and quantum circuit verification can be abandoned. Only a certain number of measurement bases need to be tested for quantum gates to achieve the expected fidelity requirements. In quantum computing that manipulates microwave photons, it is very important to estimate the number of measurement base states for quantum gate verification. With the estimated number of measurement base states, only a few unitary transformations are needed to represent any state in the Hilbert space as a superposition of base states, which greatly reduces the number of quantum gate verification and measurement experiments.

[0016] The fractal dimension of the quantum gate test experimental space Θ is used as the theoretical basis for estimating the number of measurement bases in the quantum gate test process. The main contents are summarized as follows:

[0017] The Bloch sphere is a geometric representation of the pure state space of a two-state system. The calculation of the quantum state vector is regarded as a second-order quantum system of quantum bits rotating around the Bloch sphere. This second-order quantum system describes the quantum state |qubit> by the following mathematical expression: That is, the quantum state |qubit> where the Bloch sphere is located is composed of the probabilities of the |0> state and the |1> state as the ground state coefficients. The usual method of probability calculation is to measure the same Rabi curve (Rabi) frequency time series hundreds or thousands of times, and then make a statistical judgment on the probability of the measurement results. Therefore, we cannot directly obtain the components of the final state vector, and can only estimate it through a large number of repeated experimental measurements through quantum tomography. However, when the number of quantum bits increases to a scale that is difficult to meet the exponential growth, the number of quantum gate test measurement experiments will also be exponential. According to the theory of quantum mechanics, the probabilities of the only two results of the quantum state |qubit>, the |0> state and the |1> state, obey the law of local conservation of probability. Quantum computing is a second-order quantum system that performs projected quantum measurements in the Hilbert space, that is, in the process of the quantum state |qubit> transformation, which belongs to the Hilbert space. Any vector in a separable Hilbert space is called a state vector. For any operation of the system, the state vector is described by the Schrödinger wave equation, which can be regarded as a unitary transformation of the state vector describing the system, that is, any state vector in the Hilbert space can be expressed as a superposition of some ground states. According to the divisibility and countability of the Hilbert space H, a one-to-one mapping can be established with natural numbers; and according to the fact that each pair of quantum ground states of microwave photons corresponds to a Bloch sphere, the number of Bloch spheres can be mapped one-to-one with natural numbers. The ground state vector of the Hilbert space H corresponds one-to-one to the quantum state |qubit> represented by the Bloch sphere set Q. Therefore, the quantum gate test experimental space Θ establishes a one-to-one correspondence with the Hilbert space H, thereby proving the one-to-one correspondence between the Hilbert space H, the Bloch sphere set Q, and the quantum gate test experimental space Θ. In other words, the fractal dimension that represents the manipulation of the quantum gate test experimental space Θ can be used as an estimate of the number of measurement bases in the quantum gate test process.

[0018] The experimental space Θ for manipulating quantum gates is the basis for classifying self-similar structures and sparse states. The main contents are summarized as follows:

[0019] According to the self-similarity of fractal theory, fractal is a mathematical construction, that is, the part is similar to the whole in some way; the fractal dimension is the most basic quantity that quantitatively represents self-similar random shapes and phenomena, and the Bloch sphere set Q in the quantum gate control test experimental space Θ has a self-similar structure. Therefore, the quantum gate control test experimental space Θ is a self-similar structure under chaotic motion, and the self-similar structure space capacity dimension D can be used as the fractal dimension.

[0020] Chaotic motion is a fractal phenomenon without characteristic scale. The fractal dimension is larger than the topological dimension but smaller than the dimension of the space occupied. Therefore, when n is very large, the distance between the first two bifurcation point parameters is the distance between the second two bifurcation point parameters. The resulting state is called a sparse state. To describe the sparse state in the quantum gate test experimental space Θ, a scalar index is given to it, denoted as α. max In order to ensure the rationality of the representation of sparse states in the quantum gate test experimental space Θ, the Feigenbaum constant δ is taken to represent the scalar index α of the sparse state in the quantum gate test experimental space Θ max , that is: α max =δ≈4.669.

[0021] Based on the fractal algorithm of the self-similar structure of the quantum gate test space Θ, the steps are as follows:

[0022] Step 1: Determine whether the experimental space Θ for manipulating quantum gates is a self-similar structure;

[0023] Step 2: Calculate the maximum value L of the side length of the quantum gate test experimental space Θ where the quantum gate test measurement basis vector is located;

[0024] Step 3: Set the radius value ρ of the Bloch sphere in the experimental space;

[0025] Step 4: Calculate the minimum number of Bloch spheres in the manipulation experiment space: minN(ρ);

[0026] Step 5: Calculate the fractal dimension D of the self-similar structure space:

[0027]

[0028] Step 6: Record the fractal dimension of the quantum gate test experimental space Θ, which is the number of quantum gate test measurement bases.

[0029] It can be seen from this that once the quantum gate test experimental space Θ is determined, L can also be determined, and the estimated value of the number of quantum gate test measurement bases can be determined.

[0030] Based on the fractal algorithm of the sparse state of the quantum gate test space Θ, the steps are as follows:

[0031] Step 1: Determine whether the manipulated experimental space Θ is a self-similar structure in a sparse state;

[0032] Step 2: Calculate the maximum value L of the side length of the quantum gate test experimental space Θ where the quantum gate test measurement basis vector is located;

[0033] Step 3: Calculate the radius ρ of the Bloch sphere in the quantum gate test experimental space;

[0034] Step 4: Calculate the minimum number of Bloch spheres minN(ρ) in the experimental space for manipulating quantum gates;

[0035] Step 5: Calculate the fractal dimension of the self-similar structure space of the sparse state

[0036] Step 6: Record the fractal dimension of the quantum gate test experimental space Θ of the sparse state, which is the number of quantum gate test measurement bases.

[0037] The main contents of the verification device system for determining the number of quantum gate test measurement bases are summarized as follows:

[0038] The verification device system for determining the number of quantum gate test measurement bases transforms a quantum gate test measurement system into a quantum processor, and realizes the determination of the estimated value of the number of quantum gate test measurement bases through the fractal dimension of the quantum gate test experimental space.

[0039] The verification device platform prototype system consists of:

[0040] Recording module a: records quantum state information of quantum gate test and type and quantity information of quantum gate test experimental space environment;

[0041] Analysis module b: Analyze and determine whether the quantum gate control test experimental space Θ is a self-similar structure or a sparse state structure, classify the structure, and analyze the types and quantities of experimental spaces that affect the quantum gate test task;

[0042] Analytical module d: Analyze the maximum side length L of the quantum gate test experimental space Θ; Analyze the minimum radius ρ of the Bloch sphere set Q;

[0043] Prediction module e: judge the type of self-similar structure or sparse state structure;

[0044] Calculation module f: applying the steps of the fractal algorithm based on the self-similar structure of the quantum gate test experimental space, or the steps of the fractal algorithm based on the sparse state of the quantum gate test experimental space, to calculate the fractal dimension of the quantum gate test experimental space Θ;

[0045] Display module g: displays the fractal dimension of the quantum gate test experimental space Θ and the number of quantum gate test measurement bases.

[0046] 3. Beneficial effects

[0047] Compared with the prior art, the advantages of the present invention are:

[0048] (1) The present invention provides a fractal algorithm for determining the measurement basis of quantum gate inspection, which is a new method for calculating the fractal dimension of the quantum gate inspection experimental space as an estimate of the number of quantum gate inspection measurement bases. According to this method, the number of quantum gate inspection measurement experiments is greatly reduced, and the scientific nature and inspection efficiency of quantum gate inspection are improved.

[0049] (2) The present invention provides a verification device system for determining the quantum gate test measurement cardinality. Based on a new algorithm for the fractal dimension of the quantum gate test experimental space, a quantum gate test software system is developed, which reduces the complexity of large-scale experiments on quantum states in the quantum gate test experimental space in the past, or the unfeasible method of improving the processor hardware when errors occur. This greatly reduces the number of quantum gate test measurement experiments and improves the application efficiency of intelligent decision support for the estimation of the quantum gate test measurement cardinality.

[0050] (3) The theory and method of the present invention can also be applied to a class of quantum gate inspection and measurement methods, quantum gate inspection and measurement metrology systems and Rabi curve intelligent decision support system software development, providing a theory, method and means for quantum gate inspection and measurement under uncertain conditions. BRIEF DESCRIPTION OF THE DRAWINGS

[0051] Figure 1 A system summary diagram of a fractal algorithm and verification device for determining the cardinality of a quantum gate test measurement provided by the present invention;

[0052] Figure 2 A one-to-one correspondence diagram of the verification space provided by the present invention;

[0053] Figure 3 This is an overall working flow chart of the system architecture of the quantum gate test experimental space verification device provided by the present invention. DETAILED DESCRIPTION

[0054] 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.

[0055] The present invention is described in detail with reference to the accompanying drawings and specific embodiments.

[0056] First refer to the attached Figure 1 As shown in the figure, starting from the problem of determining the measurement basis of quantum gate verification, a new method is proposed to use the fractal dimension of the quantum gate verification experimental space as an estimate of the number of quantum gate verification measurement bases. The purpose is to optimize large-scale quantum gate verification from the software perspective, transform a physical system into a quantum processor, and realize the determination of the number of quantum gate verification measurement bases. The topological structure of the controlled motion space of microwave photons is analyzed; the mathematical construction of the process of manipulating microwave photons to perform superposition and entanglement is proposed; the one-to-one correspondence between the Hilbert space H, the Bloch sphere set Q, and the quantum gate verification experimental space Θ is analyzed, and the relationship between the number of measurement bases of the quantum gate verification process and large-scale quantum gate verification is established, and the fractal dimension of the quantum gate verification experimental space is used as a mathematical model to estimate the number of quantum gate verification measurement bases.

[0057] The chaotic system that constitutes the circular mapping of the quantum gate test control system is X. The quantum state controls the microwave photons to realize the quantum state transformation. Let's remember that the quantum gate test experimental space is Θ, and the length, width and height of the space are x, y, and z respectively. Define max(x, y, z) = L. Construct the maximum experimental environment space volume V with L as the quantum gate test experimental space Θ, that is, V = [max(x, y, z)] 3 =L 3 , multifractalization of the quantum gate test manipulation circle mapping chaotic system.

[0058] When the fractal dimension of microwave photon-manipulated quantum gate test experimental space Θ corresponds one-to-one with the Bloch sphere set Q of self-similar structure, a classification study is conducted on the structure and state of the quantum gate test experimental space where the quantum gate test process is located.

[0059] When the quantum gate test experimental space is a self-similar structure, a fractal algorithm based on the self-similar structure of the quantum gate test experimental space is given, that is, the microwave photon manipulation quantum gate test experimental space Θ is regarded as a self-similar structure, and the calculation formula is substituted into it. Obtain the fractal dimension of the quantum gate test experimental space Θ.

[0060] When the quantum gate test experimental space is sparse, a fractal algorithm based on the sparse state of the quantum gate test experimental space is given, and the calculation formula is substituted into The fractal dimension of the quantum gate test experimental space Θ is obtained.

[0061] Taking n Qbits as an example, according to the fractal dimension of the quantum gate test experimental space, it can be used as a theoretical basis for estimating the measurement cardinality of quantum gate test, and D and D Θ That is, they are the fractal dimensions of the quantum gate test experimental space Θ based on the self-similar structure of the quantum gate test experimental space and the sparse state of the quantum gate test experimental space, which is also the estimated number of quantum gate test measurement bases.

[0062] In conjunction with the instruction manual Figure 2 , the present invention is described in detail.

[0063] See attached Figure 2As shown, in the experimental space Θ for controlling microwave photons to test superposition and entanglement quantum gates, the fractal dimension is D (i.e., the fractal dimension); the separable Hilbert space is H, and the Bloch sphere set is Q. The topological space corresponding to the Hilbert space H is countable, that is, a one-to-one mapping can be established with natural numbers; each pair of quantum ground states of microwave photons corresponds to a Bloch sphere, so the ground state vector of the Hilbert space H corresponds one-to-one to the quantum state |qubit> represented by the Bloch sphere set Q; the fractal dimension of the experimental space Θ for controlling microwave photons to test quantum gates corresponds one-to-one to the Bloch sphere set Q of self-similar structures, so the fractal dimension D of the experimental space Θ for controlling quantum gates is used as an estimate of the number of measurement bases in the quantum gate test process.

[0064] Example 1:

[0065] Taking n Qbits as an example, an application method of the quantum gate test measurement cardinality determination algorithm is given.

[0066] Instruction manual attached Figure 3 The overall working flow chart of the quantum gate test measurement cardinality verification device system is presented. The empirical example analysis and verification is performed. Under uncertain conditions, the fractal dimension D of the quantum gate test experimental space Θ is manipulated as the estimation algorithm of the measurement cardinality of the quantum gate test process.

[0067] The system recording module a of the measurement cardinality verification device is used to record the quantum gate test quantum state information and the quantum gate test experimental space environment type and quantity information; the quantum gate may be set to n bits. According to the theory of quantum mechanics, the quantum state in the Hilbert phase space is 2 n dimension; record that the length, width and height of the quantum gate test experimental space Θ are x, y and z respectively, and the maximum value of the quantum gate test experimental space Θ is V; record that the radius of the Bloch sphere in the quantum gate test experimental space is ρ, and the minimum number of the Bloch sphere set Q is N(δ).

[0068] By analyzing module b, the structure of the experimental space Θ for manipulating quantum gates is analyzed and judged, which can be divided into two categories: self-similar structure and sparse state structure.

[0069] Through the analytical module d, the length, width and height x, y, z values ​​of the experimental space Θ are checked by the quantum gate, and the maximum value V of the experimental space Θ is checked by the analytical quantum gate. 3 =L 3 ; With the radius of the Bloch sphere as ρ, the minimum number of Bloch spheres N(δ) in the experimental space for controlling quantum gates is calculated analytically, minN(ρ) = 2 n In fact, there must exist n in the Hilbert space H such that the dimension of the Hilbert space H is 2. n ; Based on the quantum gate n bits, the maximum value of the quantum gate test experimental space Θ is V = [max(x,y,z)] 3=L 3 , analytic Bloch sphere radius In fact, the quantum gate test and control system is a circularly mapped chaotic system. For the multifractal of the circularly mapped chaotic system, if the radius is multiplied by the parameter ρ each time After iterating n times,

[0070] The self-similar structure and sparse state structure types are determined by the prediction module e: when the fractal dimension of the microwave photon control quantum gate test experiment space Θ corresponds one-to-one to the Bloch sphere set Q of the self-similar structure, the microwave photon control quantum gate test experiment space Θ is regarded as a self-similar structure; when n is very large, the quantum gate test experiment space Θ exists in a sparse state, and at this time the quantum gate test experiment space Θ is a sparse state self-similar structure;

[0071] Through the calculation module f, the steps of the fractal algorithm based on the self-similar structure of the quantum gate test experimental space or the steps of the fractal algorithm based on the sparse state of the quantum gate test experimental space are applied, and the calculation is divided into two cases:

[0072] Case 1: When the quantum gate test experimental space Θ is a self-similar structure, follow the steps below:

[0073] Step 1: Determine whether the experimental space Θ for manipulating quantum gates is a self-similar structure;

[0074] Step 2: Based on the maximum value L of the side length of the quantum gate test experimental space Θ obtained analytically, calculate the maximum value V = [max(c,y,z)] of the quantum gate test experimental space Θ where the quantum gate test measurement basis vector is located. 3 =L 3 ;

[0075] Step 3: Calculate the minimum radius of the Bloch sphere set Q in the quantum gate test experimental space Θ

[0076] Step 4: Calculate the minimum number of Θ Bloch balls Q in the quantum gate control test experimental space minN(ρ)=2 n ;

[0077] Step 5: Calculate the fractal dimension D of the self-similar structure manipulation quantum gate test experimental space Θ and substitute it into the formula:

[0078]

[0079] Case 2: When the quantum gate test experimental space Θ exists in a sparse state, follow the previous steps 1 to 5, and then go to the following step:

[0080] Step 6: Calculate the fractal dimension of the self-similar structure space of the sparse state

[0081] Take α max =δ≈4.669, that is:

[0082]

[0083] D.D Θ That is, the fractal dimension of the quantum gate test experimental space Θ based on the self-similar structure of the quantum gate test experimental space and the sparse state of the quantum gate test experimental space, that is, the number of quantum gate test measurement bases.

[0084] Display module g: Display of the fractal dimension of the quantum gate test experimental space and the number of quantum gate test measurement bases. End. The application of the estimated value of the number of n-bit quantum gate test measurement bases is verified through empirical analysis, and the feasibility and scientificity of the new method of using the fractal dimension of the quantum gate test experimental space Θ as the estimated value of the number of measurement bases in the quantum gate test process is given.

[0085] The above empirical example analysis describes the invention and its implementation method. 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 implementation examples. Based on the implementation examples in the present invention, all other implementation examples obtained by researchers in this field without making creative work are within the scope of protection of the present invention.

Claims

1. A fractal algorithm for determining the basis of quantum gate test measurements, characterized in that: The specific steps are as follows: Step 1: construct a quantum gate test experimental space Θ, and establish a corresponding relationship between the fractal dimension of the quantum gate test experimental space Θ and the estimated value of the quantum gate detection cardinality according to the one-to-one correspondence between the Hilbert space and the space where the Bloch sphere is located; Step 2: Analyze the maximum value L of the side length of the quantum gate test experimental space Θ where the quantum gate test measurement basis vector is located, and calculate the maximum value of the experimental space Θ where the quantum gate test measurement basis vector is located ; The length of the quantum gate test experimental space Θ is x, the width is y, and the height is z. The maximum length of its side is ; Step 3: Calculate the radius of the Bloch sphere in the quantum gate test experimental space Θ according to the maximum value V of the quantum gate test space Θ ; Step 4: Calculate the quantum gate test experimental space Θ The minimum number of Bloch balls in the experiment ,in, Indicates The radius of the Bloch sphere in the experiment ; Step 5, determining the type of the quantum gate test experimental space Θ, wherein the type includes a self-similar structure and a sparse state; Step 6: When the type is a self-similar structure, the fractal dimension D is calculated by the following formula: ; When the type is sparse, the fractal dimension It is calculated by the following formula: ,in, The Feigenbaum constant δ is taken to represent the scalar index of the sparse state of the quantum gate test experimental space Θ; Step 7, record and display the fractal dimension of the quantum gate test measurement experimental space Θ, which is the quantum gate test measurement cardinality.

2. The fractal algorithm for determining the quantum gate test measurement cardinality according to claim 1, characterized in that: Said =δ≈4.

669.

3. A verification device system based on the fractal algorithm according to any one of claims 1 or 2, characterized in that: include, Recording module a: records quantum state information of quantum gate test, type and quantity information of quantum gate test experimental space Θ; Analysis module b: analyzing the parameters of the quantum gate test experimental space Θ, which is a self-similar structure or a sparse state structure, classifying the parameters, and analyzing the types and quantities of the parameters that affect the quantum gate test experimental space Θ; Analytical module d: Analyze the maximum side length L of the quantum gate test experimental space Θ; Analyze the minimum radius of the Bloch sphere set Q ; Pre-judgment module e: determines whether the quantum gate test experimental space Θ belongs to a self-similar structure or a sparse state structure type; Calculation module f: applying the steps of the fractal algorithm based on the self-similar structure of the quantum gate test experimental space Θ, or the steps of the fractal algorithm based on the sparse state of the quantum gate test experimental space Θ, to calculate the fractal dimension of the quantum gate test experimental space Θ; Display module g: displays the fractal dimension of the quantum gate test experimental space Θ.

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