Quantum Computing Method, Apparatus, Device, and Medium for Simon's Problem

Abstract

The present invention relates to a quantum computing method, apparatus, device, and medium for the Simon problem. The method includes: obtaining the number of original domain bits and the number of original range bits of the Simon problem function to be solved; constructing the same number of sub-Simon problem functions based on the original domain bits and the number of the Simon problem function to be solved, wherein the domain bits of each sub-Simon problem function are one bit in the original domain; mapping the range of each sub-Simon problem function to a range with one bit to obtain a corresponding Deutsch problem function; constructing a problem-solving quantum circuit; respectively running the problem-solving quantum circuits corresponding to each sub-Simon problem function to obtain the corresponding sub-characters to be obtained; and sequentially combining the corresponding sub-characters to obtain the string to be obtained of the Simon problem function to be solved. The present invention reduces the requirement for the number of qubits and improves the solving accuracy and efficiency.

Description

Technical Field

[0001] The present invention relates to the field of quantum computing technology, and in particular to a quantum computing method, device, equipment and medium for Simon problem. Background Art

[0002] Quantum algorithms are algorithms that run on quantum computers and represent a cutting-edge computing technology. They use properties such as quantum superposition and quantum entanglement in quantum mechanics to solve problems that are difficult to solve with traditional algorithms. Compared with classical algorithms, quantum algorithms use quantum bits (Qubit) as the basic carrier of information and can explore multiple possible solutions at the same time, thereby achieving significant superiority over classical computing on specific problems.

[0003] So far, researchers have developed a series of quantum algorithms and achieved remarkable results in many fields. Among them, the Simon algorithm not only promoted the development of Fourier transform algorithms based on quantum computing, but also laid the foundation for the famous Shor algorithm. With the advantage of quantum parallelism, the Shor algorithm can theoretically efficiently decompose large integers in polynomial time, which has brought disruptive changes to the field of cryptography. The Simon algorithm also shows great potential in solving practical problems, especially in cryptography and coding. For example, the Simon algorithm can effectively crack encryption schemes based on Simon functions.

[0004] The Simon algorithm was proposed by Daniel Simon in 1994 to solve a specific problem, namely, to determine whether a black box function is a one-to-one function or a two-to-one function and find the corresponding binary string. Specifically, given a Boolean function ,in , is the range of values that the independent variable can take, called the domain. is the range of the dependent variable value, called the range. This function satisfies the following properties: there is an unknown string , so that for all values of the independent variable ,have , if and only if or ( represents modulo 2 addition, or XOR operation).

[0005] The goal of solving the Simon problem is to determine the string s based on the given domain and range. Currently, there are two main methods to solve the Simon problem: one is the classical algorithm, and the other is the Simon algorithm proposed by Daniel Simon based on quantum computing. The query complexity of using the classical algorithm to solve the Simon problem is O(2 n) For the Simon problem, the query complexity of the Simon algorithm is O(n). Compared with classical computing methods, the computing speed of the existing Simon algorithm is exponentially accelerated.

[0006] However, when the domain and range of the Simon problem are given, the number of qubits required to solve the Simon problem using the existing Simon algorithm is n + m. When n and m are large, the required number of qubits will increase significantly, which means that a large-scale universal quantum computer is needed to complete the calculation. For today's quantum technology, there are many problems in using a large-scale universal quantum computer to solve the Simon problem. First, building and running such a computer requires a large amount of financial support; second, the computing efficiency is low because the increase in the number of qubits will lead to a significant increase in the depth and complexity of the quantum circuit, thus slowing down the computing speed; in addition, the quantum fidelity will also be limited, and qubits are vulnerable to noise and errors during operation, which will have a greater negative impact on the accuracy of the calculation. Summary of the Invention

[0007] In view of the technical problems existing in the prior art, the present invention proposes a quantum computing method, system and medium for solving the Simon problem, so as to reduce the demand for the number of qubits and improve the solution accuracy and efficiency.

[0008] To solve the above technical problems, according to one aspect of the present invention, the present invention provides a quantum computing method for solving the Simon problem, and the method includes the following steps:

[0009] Obtain the number of original domain bits and the number of original range bits of the Simon problem function to be solved, where the original independent variable values in the original domain and the original dependent variable values in the original range are both binary numbers;

[0010] Based on the original domain bits and the number of original domain bits of the Simon problem function to be solved, construct the same number of sub-Simon problem functions, where the domain bit of each sub-Simon problem function is one bit in the original domain, the range of each sub-Simon problem function is a sub-range of the range of the Simon problem function to be solved, and each sub-Simon problem function includes the corresponding sub-character to be solved;

[0011] Map the range of each sub-Simon problem function to a range with the number of bits being 1 to obtain the corresponding Deutsch problem function;

[0012] Construct a problem-solving quantum circuit, where the problem-solving quantum circuit includes a Deutsch problem function solving unit and a Simon problem equation solving unit connected in sequence;

[0013] Run the problem-solving quantum circuits corresponding to each sub-Simon problem function respectively to obtain the corresponding sub-characters to be solved;

[0014] According to the positions of the domain bits of the sub-Simon problem function in the original domain of the Simon problem function to be solved, combine the corresponding sub-characters to be solved in sequence to obtain the string to be solved of the Simon problem function to be solved.

[0015] Optionally, the steps of constructing the same number of sub-Simon problem functions include:

[0016] Determine a first bit in the original domain bits of the Simon problem function to be solved as the domain bit of the sub-Simon problem function, and the remaining bits as the second bits of the second domain;

[0017] Extract the first bit value from the original argument values of the original domain of the Simon problem function to be solved to form the sub-argument value of the sub-Simon problem function;

[0018] Sequentially extract the second bit values from each original argument value of the original domain of the Simon problem function to be solved to form the corresponding second argument values;

[0019] Combine each sub-argument value of the sub-Simon problem function with each second argument value respectively in the order of their positions in the original domain to form an original argument value in the original domain;

[0020] Obtain the original dependent variable value corresponding to the original argument value from the original range of the Simon problem function to be solved as the first original dependent variable value;

[0021] Determine one first original dependent variable value from the multiple first original dependent variable values corresponding to each sub-argument value as the sub-dependent variable value corresponding to the sub-argument value according to the same value-taking function, where the sub-dependent variable values corresponding to each sub-argument value constitute the range of the sub-Simon problem function.

[0022] Optionally, when constructing the same number of sub-Simon problem functions, take each first bit in the original domain of the Simon problem function to be solved as the domain bit of a sub-Simon problem function in the order from high to low or from low to high.

[0023] Optionally, the value-taking function is a maximum function or a minimum function. Correspondingly, the step of determining, according to the same value-taking function, a first original dependent variable value from multiple first original dependent variable values corresponding to each sub-independent variable value as the sub-dependent variable value corresponding to the sub-independent variable value includes: determining the first original dependent variable value with the largest or smallest numerical value from multiple first original dependent variable values corresponding to each sub-independent variable value as the sub-dependent variable value corresponding to the sub-independent variable value.

[0024] Optionally, when mapping the value range of a sub-Simon problem function to a value range with a bit number of 1, each sub-dependent variable value of the sub-Simon problem function is mapped to a binary numerical value with a bit number of 1, and when two sub-dependent variable values are the same, the mapped values corresponding to each sub-dependent variable value are the same, and are binary numerical values 0 or 1; when two sub-dependent variable values are different, the mapped values corresponding to each sub-dependent variable value are different, and are binary numerical values 0 and 1 respectively.

[0025] Optionally, the Simon problem equation-solving unit is a quantum gate or a combination of quantum gates that realizes flipping between the quantum 0 state and the quantum 1 state.

[0026] Optionally, when respectively running the problem function-solving quantum circuits corresponding to each sub-Simon problem function, the problem function-solving quantum circuits of the sub-Simon problem functions are run in a serial and / or parallel manner to obtain the corresponding sub-characters to be solved.

[0027] According to another aspect of the present invention, the present invention further provides a quantum computing device for Simon's problem. The device includes a parameter acquisition module, a sub-Simon problem function construction module, a mapping module, a quantum circuit construction module, an operation module, and a combination module. The parameter acquisition module is configured to acquire the number of original domain bits and the number of original range bits of the Simon's problem function to be solved, wherein the original independent variable values in the original domain and the original dependent variable values in the original range are binary numbers respectively; the sub-Simon problem function construction module is configured to construct the same number of sub-Simon problem functions based on the original domain bits and the number of original domain bits of the Simon's problem function to be solved. Among them, the domain bit of each sub-Simon problem function is a bit in the original domain, the range of each sub-Simon problem function is a sub-range of the range of the Simon's problem function to be solved, and each sub-Simon problem function has a sub-character to be solved; the mapping module is configured to map the range of each sub-Simon problem function to a range with the number of bits being 1 to obtain the corresponding Deutsch problem function; the quantum circuit construction module is configured to construct a problem-solving quantum circuit, wherein the problem-solving quantum circuit includes a Deutsch problem function solving unit and a Simon problem equation solving unit connected in sequence; the operation module is configured to respectively operate the problem-solving quantum circuits corresponding to each sub-Simon problem function to obtain the corresponding sub-characters to be solved; the combination module is configured to sequentially combine the corresponding sub-characters to be solved according to the positions of the domain bits of the sub-Simon problem functions in the original domain of the Simon's problem function to be solved to obtain the string to be solved of the Simon's problem function to be solved.

[0028] According to another aspect of the present invention, the present invention further provides an electronic device, including a processor and a memory. The memory stores computer instructions, and when the processor runs the computer instructions, it executes the aforementioned quantum computing method for Simon's problem.

[0029] According to another aspect of the present invention, the present invention further provides a computer-readable storage medium. The computer-readable storage medium stores computer instructions, and when the computer instructions are run by a processor, they execute the aforementioned quantum computing method for Simon's problem.

[0030] The present invention combines the concept of distributed computing with quantum algorithms, decomposes the solving task of the complex and resource-intensive Simon problem into a series of smaller and more manageable subtasks. Each subtask does not require ancillary qubits and only needs 1 qubit, significantly reducing the demand for quantum resources. Moreover, due to the small number of qubits applied, the influence of circuit noise on the quantum state is also significantly reduced, thus improving the quantum fidelity and further enhancing the computational accuracy of the solution. Since each subtask only needs 1 qubit, it is possible to flexibly set computing methods such as serial and parallel according to the existing computing resources, achieving an efficient solution to the Simon problem. Description of the Drawings

[0031] Next, the preferred embodiments of the present invention will be further described in detail with reference to the drawings, where:

[0032] Figure 1 is a flowchart of a quantum computing method for the Simon problem according to an embodiment of the present invention;

[0033] Figure 2 is a flowchart of a method for constructing a sub-Simon problem function according to an embodiment of the present invention;

[0034] Figure 3 is a schematic diagram of a quantum circuit of a Deutsch problem function according to an embodiment of the present invention;

[0035] Figure 4 is a schematic diagram of a problem-solving quantum circuit corresponding to a computing node according to an embodiment of the present invention;

[0036] Figure 5 is a flowchart of a method for solving the Simon problem based on multiple computing nodes and their quantum circuits according to an embodiment of the present invention;

[0037] Figure 6 is a schematic diagram of a quantum circuit used when solving the Simon problem using the prior art according to an embodiment of the present invention;

[0038] Figure 7 is a schematic block diagram of a quantum computing device for the Simon problem according to an embodiment of the present invention;

[0039] Figure 8 is a schematic block diagram of a quantum computing device for the Simon problem according to another embodiment of the present invention;

[0040] Figure 9 is a schematic block diagram of the structure of an electronic device according to an embodiment of the present invention. Detailed Embodiments

[0041] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are some, but not all, of the embodiments of the present invention. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0042] In the following detailed description, reference may be made to the accompanying drawings which form a part hereof, and in which are shown by way of illustration specific embodiments in which the application may be practiced. In the drawings, like reference numerals describe substantially similar components in different figures. The various specific embodiments of the present application have been described in sufficient detail below so that those of ordinary skill in the art with relevant knowledge and technology can implement the technical solutions of the present application. It should be understood that other embodiments may be utilized or structural, logical, or electrical changes may be made to the embodiments of the present application. Additionally, the "first", "second", etc. in the technical feature names of the present invention are not used to represent an order, but to distinguish different technical features with the same name.

[0043] In today's era of noisy intermediate-scale quantum (NISQ), compared to building a large-scale universal quantum computer, the technical path to realizing a small-scale quantum processor appears to be more practical and feasible. The concept of distributed quantum computing (DQC) is an innovative move that ingeniously combines the essence of distributed systems with quantum information processing technology. The implementation of this architecture relies on a carefully designed distributed quantum algorithm to ensure its effectiveness in practical applications.

[0044] See Figure 1 , Figure 1 is a flowchart of a quantum computing method for the Simon problem according to an embodiment of the present invention. In the present invention, the Boolean function in the Simon problem to be solved is: , where n is the number of binary bits of the original independent variable, simply referred to as the number of original domain bits, is called the original domain; m is the number of binary bits of the original dependent variable, simply referred to as the number of original range bits, , is called the original range; and it satisfies: for all values of the independent variable , there is , if and only if or , where s is the string to be found, . Hereinafter, the aforementioned Boolean function in the Simon problem to be solved will be simply referred to as the Simon problem function to be solved. The quantum computing method for the Simon problem in this embodiment includes the following steps:

[0045] Step S1, obtain the number of original domain bits and the number of original range bits of the Simon problem function to be solved, where the original independent variable values in the original domain and the original dependent variable values in the original range are binary numbers respectively.

[0046] Step S2, construct the same number of sub-Simon problem functions based on the original domain bits and their numbers of the Simon problem function to be solved. Among them, the domain bit of each sub-Simon problem function is one bit in the original domain, the range of each sub-Simon problem function is a sub-range of the range of the Simon problem function to be solved, and each sub-Simon problem function has a sub-character to be solved.

[0047] Step S3, map the range of each sub-Simon problem function to a range with 1 bit number to obtain the corresponding Deutsch problem function.

[0048] Step S4, construct a problem-solving quantum circuit, where the problem-solving quantum circuit includes a Deutsch problem function solving unit and a Simon problem equation solving unit connected in sequence.

[0049] Step S5, run the problem-solving quantum circuits corresponding to each sub-Simon problem function respectively to obtain the corresponding sub-characters to be solved.

[0050] Step S6, combine the corresponding sub-characters in sequence according to the positions of the domain bits of the sub-Simon problem functions in the original domain of the Simon problem function to be solved to obtain the string to be solved of the Simon problem function to be solved.

[0051] In the present invention, one calculation task of running the problem function solving quantum circuit corresponding to a sub-Simon problem function can be called a calculation node. The problem function solving quantum circuits corresponding to multiple sub-Simon problem functions in the present invention can be run serially by one quantum computing device or in parallel by multiple quantum computing devices. When the number of qubits supported by one quantum computing device is relatively large, multiple problem function solving quantum circuits can be run in parallel.

[0052] In step S1, obtain the number of original domain bits n and the number of original range bits m of the Simon problem function to be solved. In step S2, construct n sub-Simon problem functions. The domain bit of each sub-Simon problem function is one bit in the original domain. Refer to Figure 2 , Figure 2 is a method flowchart for constructing a sub-Simon problem function according to an embodiment of the present invention, which includes the following steps:

[0053] Step S21: Divide the original domain of the Simon problem function to be solved to obtain a composite domain. Specifically, determine a first bit in the bits of the original domain of the Simon problem function to be solved as the domain bit of the sub-Simon problem function, and the remaining bits as the second bits of the second domain; sequentially extract the first bit values 0 or 1 from each original independent variable value in the original domain to respectively form a sub-independent variable value of the sub-Simon problem function. Thus, the sub-independent variable value is 0 or 1, and the domain of the sub-Simon problem function can be expressed as {0, 1}; sequentially extract the second bit values corresponding to form a second independent variable value from each original independent variable value in the original domain, and all the second independent variable values constitute the second domain, which can be expressed as {0, 1} (n-1) . When determining the domain bit of the sub-Simon problem function from the bits of the original domain of the Simon problem function to be solved, the bit can be extracted from any position in the original domain of the Simon problem function to be solved as the domain bit of the sub-Simon problem function, and the domain bits of the sub-Simon problem functions corresponding to all computing nodes do not repeat. The domain of the sub-Simon problem function and the second domain constitute the composite domain.

[0054] Step S22: Based on the composite domain, obtain the corresponding original dependent variable value from the original range of the Simon problem function to be solved as the first original dependent variable value. Specifically, combine each sub-independent variable value in the domain of the sub-Simon problem function with each second independent variable value in the second domain in the order of their positions in the original domain to form an original independent variable value in the original domain, and obtain the corresponding original dependent variable value from the original range of the Simon problem function to be solved as the first original dependent variable value.

[0055] Step S23: Determine the range of the sub-Simon problem function. Specifically, determine one first original dependent variable value as the sub-dependent variable value corresponding to the sub-independent variable value from multiple first original dependent variable values corresponding to each sub-independent variable value according to the same value-taking function. Among them, the sub-dependent variable values corresponding to each sub-independent variable value constitute the range of the sub-Simon problem function of the target computing node, which can be expressed as {0, 1} m .

[0056] In step S22 of this embodiment, a composite domain is obtained by combining the domain of the sub-Simon problem function and the second domain. In one embodiment, the second domain serves as the first-layer domain, and the domain of the sub-Simon problem function is the second-layer domain. In the composite function corresponding to the composite domain, for each independent variable value based on the first-layer domain, the dependent variable value obtained is a sub-function based on the second-layer domain. The number of sub-functions is determined by the number of binary bits of the independent variable value (i.e., the second independent variable value) in the first-layer domain; with an independent variable value in the second-layer domain, that is, a sub-independent variable value in the domain of the sub-Simon problem function, through the said sub-function, a unique original dependent variable value can be determined from the original range, which is named the first original dependent variable value in the present invention.

[0057] In the present invention, the domain of the sub-Simon problem function is {0, 1}, the sub-independent variables are 0 and 1 respectively, that is, the number of bits is 1. Since the original independent variable bits of the Simon problem function to be solved have a total of n bits, the bits of the second independent variable in the second domain have a total of n - 1 bits. Therefore, the dependent variable value obtained based on each second independent variable value in the second domain is a sub-function, and the number of sub-functions is 2 (n-1) , and each sub-independent variable value of each sub-Simon problem function corresponds to 2 (n-1) first original dependent variable values.

[0058] In step S23, the value-taking function is the maximum function or the minimum function. Correspondingly, when constructing the range of the sub-Simon problem function, when determining one of the 2 (n-1) first original dependent variable values corresponding to a sub-independent variable value as the sub-dependent variable value of the sub-Simon problem function, the first original dependent variable value with the maximum or minimum dependent variable value is used as the sub-dependent variable value corresponding to the said sub-independent variable value.

[0059] When constructing n sub-Simon problem functions, in the order from high to low or from low to high, each first bit in the original domain of the Simon problem function to be solved is used as a domain bit of a sub-Simon problem function.

[0060] In the present invention, a Simon problem function is divided into n (the number of original domain bits) sub-Simon problem functions, and the sub-character to be solved for each sub-Simon problem function is one bit in the string to be solved of the Simon problem function to be solved. The present invention regards the calculation process of a sub-character to be solved as a calculation task, also called a calculation node. Corresponding to a physical quantum computing device, each calculation node corresponds to a qubit.

[0061] For example, the method of constructing the sub-Simon problem function in ascending order from the low bit to the high bit is described as follows:

[0062] (1) For the j-th sub-Simon problem function, when j = 0, select the left n - 1 bits to divide the Simon problem function to be solved, obtaining 2 (n-1) sub-functions. When j = 0, the general formula for function division is as shown in Expression 1-1 below. The j-th bit from the lowest is used as the domain bit of the 0-th sub-Simon problem function, and the high n - 1 bits are used as the second domain bit, thus obtaining the 0-th sub-Simon problem function, that is: .

[0063] 1-1

[0064] where k represents the sub-function serial number, , , and, m k is a 1-bit binary number, representing the independent variable of the k-th sub-function and also the binary value corresponding to the bit of the sub-independent variable of the 0-th sub-Simon problem function; , which are the remaining binary bits outside the domain bits of the 0-th sub-Simon problem function, constituting the second domain bit and also the binary representation of k.

[0065] As can be seen from the above expression, corresponding to the domain of the sub-Simon problem function, the same sub-independent variable value corresponds to 2 (n-1) sub-functions. Through a determined sub-independent variable value m k and a determined second independent variable value of a sub-function can jointly form an original independent variable value of the Simon problem function to be solved, and thus a specific dependent variable value can be determined from the original value range of the Simon problem function to be solved. Therefore, corresponding to a sub-independent variable value of the sub-Simon problem function, 2 (n-1) dependent variable values can be determined from the original value range of the Simon problem function to be solved. For the sake of distinction, these dependent variable values are called the first original dependent variable values.

[0066] Then, based on the maximum formula 1-2, the sub-Simon problem function of the j-th calculation node is obtained :

[0067] 1-2

[0068] where .

[0069] That is, for a specific independent variable value m of the j-th sub-Simon problem function j, starting from 2 (n-1) Take a maximum value from the 2 first original dependent variable values as the corresponding sub-dependent variable value, thus obtaining the j-th sub-Simon problem function .

[0070] (2) For the j-th node , select the j - 1 bits on the right and the n - j bits on the left to divide the Simon problem function to be solved, obtaining 2 (n-1) sub-functions. When j = 1, …, n - 2, the general formula for function division is as shown in the following expressions 1 - 3. The j-th bit starting from the low bit is used as the domain bit of the 0-th sub-Simon problem function, and the n - j bits higher than it and the j - 1 bits lower than it are used as the second domain bits, thus obtaining the j-th sub-Simon problem function, that is: .

[0071] 1 - 3

[0072] where k represents the sub-function number, , , and, m k is a 1-bit binary number, representing the independent variable of the k-th sub-function and also the binary value corresponding to the sub-independent variable of the j-th sub-Simon problem function; and is the remaining binary bits outside the domain bit of the j-th sub-Simon problem function, forming the second domain bits and also the binary representation of k.

[0073] As can be seen from the above expressions, corresponding to the domain of the sub-Simon problem function, the same sub-independent variable value corresponds to 2 (n-1) sub-functions. Through a determined sub-independent variable value m k and a determined second independent variable value of a sub-function can jointly form an original independent variable value of the Simon problem function to be solved, thus a specific dependent variable value can be determined from the original value range of the Simon problem function to be solved. Therefore, corresponding to a sub-independent variable value of the sub-Simon problem function, 2 (n-1) dependent variable values can be determined from the original value range of the Simon problem function to be solved. For the sake of distinction, these dependent variable values are called the first original dependent variable values.

[0074] Then, based on the maximum value formula 1 - 2, the sub-Simon problem function of the j-th calculation node is obtained .

[0075] (3) For the last sub-Simon problem function, j = n - 1, select the rightmost n - 1 bits to partition the Simon problem function to be solved, obtaining 2 (n-1) sub-functions. When j = n - 1, the general formula for function partitioning is as shown in the following Expressions 1 - 4. Take the j-th bit (the highest bit in this embodiment) starting from the lowest as the domain bit of the (n - 1)-th sub-Simon problem function, and the lower n - 1 bits as the second domain bit, thereby obtaining the (n - 1)-th sub-Simon problem function, that is: .

[0076] 1 - 4

[0077] where k represents the sub-function number, , , and, m k is a 1-bit binary number, representing the independent variable of the k-th sub-function and also the binary value corresponding to the bit of the sub-independent variable of the (n - 1)-th sub-Simon problem function; , are the remaining binary bits outside the domain bit of the (n - 1)-th sub-Simon problem function, forming the second domain bit and also the binary representation of k.

[0078] For a sub-independent variable value corresponding to the (n - 1)-th sub-Simon problem function, 2 (n-1) first original dependent variable values can be determined from the original range of the Simon problem function to be solved.

[0079] Then, based on the maximum value formula 1 - 2, the sub-Simon problem function of the j-th calculation node is obtained .

[0080] In step S3, when mapping the range of a sub-Simon problem function to a range with 1 bit, each sub-dependent variable value of the sub-Simon problem function is mapped to a binary value. When two sub-dependent variable values are the same, the mapped values corresponding to each sub-dependent variable value are the same, such as the binary values 0 or 1; when two sub-dependent variable values are different, the mapped values corresponding to each sub-dependent variable value are different, being the binary values 0 and 1 respectively.

[0081] For a Simon problem with the domain and range both being 1 bit, it is equivalent to judging the Boolean function h jThe problem of whether it is a balanced function or a constant function. The so-called balanced function means that for two input strings, the corresponding output strings are different, one is 0 and the other is 1. The so-called constant function means that for two input strings, the corresponding output strings are the same. Corresponding to the Simon problem where the domain and range are each 1 bit, for two independent variable values, if the dependent variable values are 0 and 1 respectively, that is, the two dependent variable values are different, then it is a balanced function. When the dependent variable values are the same, either 0 or 1, then it is a constant function. To implement the judgment of a Boolean function h j The function for solving the problem of whether it is a balanced function or a constant function is called the Deutsch problem function. See Figure 3 , Figure 3 which is a schematic diagram of the quantum circuit of the Deutsch problem function according to an embodiment of the present invention. The quantum circuit of the Deutsch problem function acts on a single qubit, and the module is an Oracle (black box function, or query function) quantum circuit unit, which can implement the calculation of the Deutsch problem function. The Oracle can perform the following operations .

[0082] Among them, the function h j (y) is encoded on the phase of the input qubit. Therefore, when h j (y) = 0, the phase of the input qubit remains unchanged. When h j (y) = 1, the phase of the input qubit flips.

[0083] In this quantum circuit, the input qubit is initialized to obtain the initial state which is:

[0084] .

[0085] The Hadamard gate is applied to generate the superposition state which is:

[0086] .

[0087] The quantum state after passing through the quantum circuit unit of the Oracle is:

[0088] .

[0089] If h j (y) = 0, the phase remains unchanged. If h j (y) = 1, the phase flips.

[0090] The Hadamard gate is applied to convert the phase information to the amplitude, and the obtained quantum state is:

[0091] 。

[0092] The calculation result is:

[0093] 。

[0094] At this time, measure the qubit. If the measurement result is , then it can be known that h j (y) is a constant function. If the measurement result is , then it can be known that h j (y) is a balanced function.

[0095] For the Simon problem function of the present invention, the measurement result satisfies the following relationship with the string s to be solved , and in the process of solving the equation, when there are two solutions of 0 and 1, the non-zero solution is the solution of the equation. Since the output quantum state of the quantum circuit of the Deutsch problem function is 0 or 1, therefore, after adding a quantum gate or a combination of quantum gates that realizes the flip between the quantum 0 state and the quantum 1 state after the quantum circuit for solving the Deutsch problem function shown in Figure 3 , the quantum state of the measurement result is the character to be solved, so there is no need to solve the equation anymore. Quantum gates that realize the flip between the quantum 0 state and the quantum 1 state are, for example, the X gate, the RX(pi) gate, the U3(pi,0,0), etc., and can also be a combination of quantum gates, such as HHX, HHHHX, etc.

[0096] Therefore, referring to Figure 4 , Figure 4 is a schematic diagram of the quantum circuit for problem solving corresponding to a computing node in an embodiment of the present invention, including a Deutsch problem function solving unit 80 and a Simon problem equation solving unit 81 connected in sequence. The Simon problem equation solving unit 81 in the present invention is an X gate. The structure of the Deutsch problem function solving unit 80 is as shown in Figure 3 , which will not be elaborated here.

[0097] In step S5, after running the quantum circuit for problem solving corresponding to each sub-Simon problem function, measure the quantum state, and the measured quantum state is the sub-character to be solved. For example, when the measured quantum state is , the corresponding sub-character to be solved is 0. When the measured quantum state is , the corresponding sub-character to be solved is 1.

[0098] Figure 5 is a flowchart of a method for solving the Simon problem based on multiple computing nodes and their quantum circuits according to an embodiment of the present invention. CombiningFigure 4 , the method includes the following steps:

[0099] Step S101, let j = 0.

[0100] Step S102, initialize the j-th qubit to the ground state. In one embodiment, the initialized ground state is state.

[0101] Step S103, generate the j-th sub-Simon problem function according to the method described above Figure 2 shown. .

[0102] Step S104, convert the j-th sub-Simon problem function into a Deutsch problem function h j :{0,1}→{0,1}.

[0103] Step S105, perform a Hadamard gate on the j-th qubit.

[0104] Step S106, perform on the j-th qubit, where .

[0105] Step S107, perform a Hadamard gate on the j-th qubit.

[0106] Step S108, perform an X gate on the j-th qubit.

[0107] Step S109, measure the qubit and use the measurement result as the sub-character S to be solved j . S j ∈{0,1}.

[0108] Step S110, determine whether j = n - 1 is satisfied. If it is satisfied, execute Step S111. If it is not satisfied, in Step S112, let j = j + 1 and return to Step S102.

[0109] Step S111, aggregate the n sub-strings S j to obtain the string s of the Simon problem to be solved. Among them, . s∈{0,1} n .

[0110] Among them, Steps S105 to S109 are an evolution and measurement process, and the measurement result is either the 0 state or the 1 state.

[0111] In Figure 5In the processing method shown, sub-characters corresponding to each sub-Simon problem function are obtained separately for each qubit in a serial manner. However, it can be known that sub-characters of multiple sub-Simon problem functions can also be obtained simultaneously in parallel by multiple qubits.

[0112] The technical solution of the present invention will be exemplarily described below through a specific embodiment.

[0113] In the Simon problem of this embodiment, n = 4 and m = 4. Assuming that the string to be solved is s = 1001, the truth table of the Boolean function f corresponding to the Simon problem in this embodiment is shown in Table 1 below.

[0114] Table 1: Truth table of the Simon problem function to be solved

[0115]

[0116] In Table 1, x is the original independent variable and f(x) is the original dependent variable. Among them, the number of binary bits in the original domain is 4, and the number of binary bits in the original range is 4. According to the method of constructing the sub-Simon problem function described above, the highest bit in the original domain is used as the domain of the 0th sub-Simon problem function, and the remaining 3 bits in the original domain are used as the second bit of the second domain, thus obtaining 2 3 = 8 sub-functions, which are respectively represented as f 0 000 、f 0 001 、f 0 010 、f 0 011 ,f 0 100 、f 0 101 、f 0 110 and f 0 111 ,where the superscript 0 represents the 0th sub-Simon problem function, and the subscripts 000 to 111 represent a specific second independent variable value in the second domain, which can also be considered as the binary representation of the sub-function number. Combining each sub-independent variable of the domain of the sub-Simon problem function and each second independent variable value together constitutes an original independent variable value in the original domain, and the corresponding first original dependent variable value is obtained from the original range. The truth values corresponding to the 8 sub-functions are shown below.

[0117] Table 2: Truth table of the 1st sub-function f 0 000

[0118]

[0119] Table 3: The second sub - function f 0 001 Truth table

[0120]

[0121] Table 4: The third sub - function f 0 010 Truth table

[0122]

[0123] Table 5: The fourth sub - function f 0 011 Truth table

[0124]

[0125] Table 6: The fifth sub - function f 0 100 Truth table

[0126]

[0127] Table 7: The sixth sub - function f 0 101 Truth table

[0128]

[0129] Table 8: The seventh sub - function f 0 110 Truth table

[0130]

[0131] Table 9: The eighth sub - function f 0 111 Truth table

[0132]

[0133] According to the above 8 sub - functions, corresponding to each independent variable value of 0 and 1, the maximum value is taken from the 8 first original dependent variable values as the sub - dependent variable value respectively, obtaining the 0th Simon problem function . Its truth table is shown in Table 10 below.

[0134] Table 10: The 0th Simon problem function Truth table

[0135]

[0136] Based on Table 10, map the range of the 0th sub-Simon problem function such that each sub-dependent variable value is mapped to a binary number. In this embodiment, the first sub-dependent variable value is mapped to the binary number 0. Then, compare whether the second sub-dependent variable value is the same as the first sub-dependent variable value. If they are different, map it to 1; if they are the same, map it to 0. In this embodiment, the first sub-dependent variable value 1110 and the second sub-dependent variable value 1110 are the same, so the second mapped value is also 0, thus obtaining a new function, namely the 0th Deutsch problem function , whose truth table is shown in Table 11 below.

[0137] Table 11: Truth table of the 0th Deutsch problem function Truth table of

[0138]

[0139] Based on the 0th Deutsch problem function , execute the Figure 4 quantum circuit of 1 qubit as shown. The measured quantum state is the 1 state, so the corresponding sub-character .

[0140] Similarly, for the Simon problem function to be solved in this embodiment, use the second bit from the left as the domain bit of the 1st sub-Simon problem function, and use the 1 bit on the left and the 2 bits on the right as the second bit of the second domain, thus obtaining 8 sub-functions: . Thus, the truth table of the 1st sub-Simon problem function is shown in Table 12 below.

[0141] Table 12: Truth table of the 1st sub-Simon problem function Truth table of

[0142]

[0143] Based on Table 12, map the range of the 1st sub-Simon problem function to obtain a new function, namely the 1st Deutsch problem function , whose truth table is shown in Table 13 below.

[0144] Table 13: Truth table of the 1st Deutsch problem function Truth table of

[0145]

[0146] Based on the 1st Deutsch problem function , execute Figure 4The quantum circuit of 1 qubit shown, the measured quantum state is the 0 state, so the corresponding sub-character .

[0147] Similarly, for the Simon problem function to be solved in this embodiment, the third bit from the left is used as the domain bit of the second sub-Simon problem function, and the two bits on the left and the one bit on the right are used as the second bit of the second domain, thus obtaining 8 sub-functions: . Thus, the second sub-Simon problem function has the truth table shown in Table 14 below.

[0148] Table 14: Truth table of the second sub-Simon problem function Truth table of

[0149]

[0150] Based on Table 14, the range of the second sub-Simon problem function is mapped to obtain a new function, that is, the second Deutsch problem function , and its truth table is shown in Table 15 below.

[0151] Table 15: Truth table of the second Deutsch problem function Truth table of

[0152]

[0153] Based on the second Deutsch problem function , execute the quantum circuit of 1 qubit shown in Figure 4 , the measured quantum state is the 0 state, so the corresponding sub-character .

[0154] Similarly, for the Simon problem function to be solved in this embodiment, the first bit from the right is used as the domain bit of the third sub-Simon problem function, and the three bits on the left are used as the second bit of the second domain, thus obtaining 8 sub-functions: . Thus, the third sub-Simon problem function has the truth table shown in Table 16 below.

[0155] Table 16: Truth table of the third sub-Simon problem function Truth table of

[0156]

[0157] Based on Table 16, the range of the third sub-Simon problem function is mapped to obtain a new function, that is, the third Deutsch problem function , and its truth table is shown in Table 17 below.

[0158] Table 17: The function of the 3rd Deutsch problem Truth table

[0159]

[0160] Based on the function of the 3rd Deutsch problem , perform Figure 4 the quantum circuit of 1 qubit shown, and the measured quantum state is the 1 state. Therefore, the corresponding sub-character .

[0161] Finally, combine the corresponding sub-characters to be solved in the order of the positions of the domain bits of each sub-Simon problem function in the original domain to obtain the string s to be solved of the Simon problem function in this embodiment, .

[0162] It can be seen from the above calculation process that for a Simon problem with 4 domain bits, since it is divided into 4 sub-problems, each sub-problem only needs to execute the quantum circuit of 1 qubit to obtain the sub-character. Therefore, when using the parallel method to execute the 1-qubit quantum circuits for 4 sub-problems simultaneously, only 4 qubits are needed. When using the serial method to sequentially execute the 1-qubit quantum circuits for 4 sub-problems, 1 qubit can complete the calculation task.

[0163] See Figure 6 , Figure 6 is a schematic diagram of the quantum circuit used to solve the Simon problem by applying the prior art according to an embodiment of the present invention. When using the prior art Simon problem quantum computing method to solve the foregoing Simon problem to be solved, the B in the quantum circuit f module is an Oracle (black box function, or called query function) quantum circuit unit that implements the Simon problem function. Oracle can implement . 4 qubits are required as computational qubits, and another 4 are used as auxiliary qubits, that is, 8 qubits are required to solve.

[0164] For a general quantum solution method of a Simon problem, it satisfies the orthogonality between the measurement result and the string s to be solved. Therefore, an equation is obtained according to each measurement result. To solve the string s in the Simon problem, at least n - 1 measurements need to be performed to obtain n - 1 different measurement results , and then a system of equations is obtained to solve the string s to be found. Corresponding to the above embodiment, it is necessary to execute 4 times Figure 6 The quantum circuit shown obtains a measurement result each time it is executed. An equation is constructed based on each measurement result, and then the system of equations consisting of four equations is solved to obtain the desired string s.

[0165] However, the method provided by the present invention obtains the sub-character after each execution of the quantum circuit, thereby eliminating the calculation process of solving the equation group and significantly improving the solution efficiency.

[0166] The present invention combines the concept of distributed computing with quantum algorithms, breaking down the complex and resource-intensive Simon problem into a series of small-scale, more manageable subtasks, each of which requires only one quantum bit, significantly reducing the demand for quantum resources and computing costs. In addition, since the number of quantum bits used is reduced, the impact of line noise on the quantum state is also significantly reduced, thereby improving quantum fidelity and, in turn, improving the computational accuracy of the solution. Since each subtask requires only one quantum bit, the efficient solution of the Simon problem can be achieved by flexibly setting serial, parallel, and other computing methods based on existing computing resources.

[0167] In another aspect, the invention provides a quantum computing device for the Simon problem, see Figure 7 , Figure 7 1 is a principle block diagram of a quantum computing device for Simon problem according to an embodiment of the present invention. In this embodiment, a quantum computing device for Simon problem (hereinafter referred to as computing device) 10 includes a parameter acquisition module 1, a sub-Simon problem function construction module 2, a mapping module 3, a quantum circuit construction module 4, an operation module 5 and a combination module 6, wherein the parameter acquisition module 1 is configured to obtain the original domain bit number and the original range bit number of the Simon problem function to be solved, wherein the Simon problem function to be solved is: , the original independent variable value in the original definition domain and the original dependent variable value in the original value range are binary numbers, n is the number of binary bits in the original definition domain, and m is the number of binary bits in the original value range. , and satisfies: for all independent variable values ,have , if and only if or , s is the string to be requested, The sub-Simon problem function construction module 2 is connected to the parameter acquisition module 1 and is configured to construct the same number of sub-Simon problem functions based on the original domain bits of the Simon problem function to be solved and their quantities. Among them, the domain bits of each sub-Simon problem function are one bit in the original domain, the range of each sub-Simon problem function is a sub-range of the range of the Simon problem function to be solved, and each sub-Simon problem function has a sub-character to be solved. The mapping module 3 is connected to the sub-Simon problem function construction module 2 and is configured to map the range of each sub-Simon problem function to a range with a bit number of 1 to obtain a corresponding Deutsch problem function. The quantum circuit construction module 4 is connected to the mapping module 3 and is configured to construct a problem-solving quantum circuit. The problem-solving quantum circuit includes a Deutsch problem function solving unit and a Simon problem equation solving unit connected in sequence. The operation module 5 is connected to the quantum circuit construction module 4 and is configured to respectively operate the problem function solving quantum circuits corresponding to each sub-Simon problem function to obtain the corresponding sub-characters to be solved. The combination module 6 is connected to the operation module 5 and is configured to sequentially combine the corresponding sub-strings to be solved according to the positions of the domain bits of the sub-Simon problem functions in the original domain of the Simon problem function to be solved to obtain the string to be solved of the Simon problem function to be solved.

[0168] In this embodiment, the operation module 5 is, for example, a quantum simulator implemented by a classical computing device or can also be a real quantum machine. When the operation module 5 supports one qubit, the operation module 5 sequentially operates the problem-solving quantum circuit and sends the measured results to the combination module 6. The combination module 6 takes each measured result (quantum 0 state or quantum 1 state) as the corresponding sub-character and combines the sub-strings of all sub-Simon problem functions to obtain the string of the Simon problem function to be solved. When the operation module 5 supports multiple qubits, the operation module 5 determines the calculation strategies of parallel operation and serial operation according to the number of qubits and the number of sub-Simon problem functions, and operates the problem-solving quantum circuits of the sub-Simon problem functions according to this calculation strategy.

[0169] See Figure 8 , Figure 8It is a schematic block diagram of a quantum computing device for Simon's problem according to another embodiment of the present invention. The operation module 5 in the computing device 10 in this embodiment includes a plurality of quantum computing units, and the quantum computing units are quantum simulators implemented by classical computing devices or can also be real quantum machines. Such as the first quantum computing unit 51, the second quantum computing unit 52, up to the t-th quantum computing unit 5t in the figure. The quantum circuit construction module 4 is respectively connected to each quantum computing unit. In one embodiment, the quantum circuit construction module 4 sends the problem-solving quantum circuits of the sub-Simon problem function to the corresponding quantum computing units respectively. Each quantum computing unit runs the problem-solving quantum circuit and sends the measurement result to the combination module 6. The combination module 6 takes each measurement result (quantum 0 state or quantum 1 state) as a corresponding sub-character, and then combines all the sub-characters to obtain the string of the Simon problem function to be solved.

[0170] On the other hand, the embodiment of the present invention also provides an electronic device. Refer to Figure 9 , Figure 9 It is a schematic block diagram of the structure of an electronic device according to an embodiment of the present invention. As Figure 9 shown, the electronic device includes a processor and a memory. Computer instructions are stored in the memory. When the processor runs the computer instructions, it executes the quantum computing method for Simon's problem provided by the present invention.

[0171] Specifically, the processor 601 may include a central processing unit (CPU) or a graphics processing unit (GPU), or an application specific integrated circuit (ASIC), or may be one or more integrated circuits configured to implement the embodiments of the present invention. The memory 602 may include a memory for data or instructions. For example, the memory 602 may be at least one of the following: a hard disk drive (HDD), a read-only memory (ROM), a random access memory (RAM), a floppy disk drive, a flash memory, an optical disc, a magneto-optical disc, a magnetic tape, a universal serial bus (USB) drive, or other physical / tangible memory storage devices. Also, the memory 602 includes a removable or non-removable (or fixed) medium. Again, the memory 602 may be inside or outside the integrated gateway disaster recovery device. The memory 602 may be a non-volatile solid state memory. In other words, generally the memory 602 includes a tangible (non-transitory) computer-readable storage medium (such as a memory device) encoded with executable instructions, and when the executable instructions stored therein are executed by the processor 601 (such as by one or more processors), the quantum computing method for Simon's problem in the embodiments of the present invention can be implemented.

[0172] In one example, Figure 9 The illustrated electronic device may further include a communication interface 603 and a bus 610. Among them, the processor 601, the memory 602, and the communication interface 603 are connected through the bus 610 to complete communication with each other. The communication interface 603 is mainly used to implement communication between various modules, devices, units, and / or devices in the electronic device.

[0173] The bus 610 includes hardware, software, or both, and can couple the components of the online data flow charging device to each other. For example, the bus may include at least one of the following: Accelerated Graphics Port (AGP) or other graphics buses, Extended Industry Standard Architecture (EISA) bus, Front Side Bus (FSB), HyperTransport (HT) interconnect, Industry Standard Architecture (ISA) bus, InfiniBand interconnect, Low Pin Count (LPC) bus, Memory bus, MicroChannel Architecture (MCA) bus, Peripheral Component Interconnect (PCI) bus, PCI-Express (PCI-X) bus, Serial Advanced Technology Attachment (SATA) bus, Video Electronics Standards Association Local (VLB) bus, or other suitable buses. The bus 610 may include one or more buses. Although the embodiments of the present invention describe or illustrate specific buses, the embodiments of the present invention may consider any suitable bus or interconnect method.

[0174] On the other hand, the embodiments of the present invention also provide a computer-readable storage medium, on which computer program instructions are stored. When the computer program instructions are executed by a processor, the foregoing quantum computing method for the Simon problem is implemented. The computer-readable storage medium is, for example, a classical computer-readable storage medium, such as a Read-Only Memory (ROM), a Random Access Memory (RAM), a disk storage medium device, an optical storage medium device, a flash memory device, an electrical, optical, or other physical / tangible memory storage device. It can also be a storage medium for storing quantum information and readable by a quantum computer, such as a Quantum Random Access Memory (QRAM). QRAM can be regarded as the quantum version of RAM in a classical computer. Through QRAM, a quantum superposition state of information can be created. Compared with RAM that needs to read one by one, data in superposition can be read at superposed addresses. QRAM can be implemented in physical ways such as optics, semiconductor quantum dots, superconducting circuits, and ion traps.

[0175] The flowcharts and / or block diagrams of the methods and systems of the embodiments of the present invention have been described above by way of example, and the relevant aspects have been described. It should be understood that each block in the flowchart and / or block diagram, or a combination thereof, can be implemented by computer program instructions, can also be implemented by dedicated hardware that performs the specified functions or actions, or can be implemented by a combination of dedicated hardware and computer instructions. When implemented in hardware, it can be, for example, an electronic circuit, an application specific integrated circuit (ASIC), appropriate firmware, a plug-in, a functional card, etc.; when implemented in software, it is a program or a code segment used to perform the required tasks. The program or code segment can be stored in a memory, or transmitted via a data signal carried in a carrier wave on a transmission medium or a communication link. The code segment can be downloaded via a computer network such as the Internet, an intranet, etc.

[0176] The above embodiments are only for illustrating the present invention, rather than limiting the present invention. Those of ordinary skill in the relevant technical field can make various changes and modifications without departing from the scope of the present invention. Therefore, all equivalent technical solutions should also fall within the scope of the disclosure of the present invention.

Claims

1. A quantum computing method for Simon's problem, characterized in that, The method includes: Obtaining the number of original domain bits and the number of original range bits of the Simon problem function to be solved, where the original independent variable values in the original domain and the original dependent variable values in the original range are both binary numbers; Constructing the same number of sub-Simon problem functions based on the original domain bits and the number of original domain bits of the Simon problem function to be solved. Among them, the domain bit of each sub-Simon problem function is a bit in the original domain, the range of each sub-Simon problem function is a sub-range of the range of the Simon problem function to be solved, and each sub-Simon problem function includes a corresponding sub-character to be solved. Among them, the calculation process of each sub-character to be solved is used as a calculation node and corresponds to a quantum bit; Mapping the range of each sub-Simon problem function to a range with 1 bit number to obtain the corresponding Deutsch problem function; Constructing a problem-solving quantum circuit, where the problem-solving quantum circuit includes a Deutsch problem function solving unit and a Simon problem equation solving unit connected in sequence; Respectively running the problem-solving quantum circuits corresponding to each sub-Simon problem function to obtain the corresponding sub-characters to be solved; Combining the corresponding sub-characters in sequence according to the positions of the domain bits of the sub-Simon problem functions in the original domain of the Simon problem function to be solved to obtain the string to be solved of the Simon problem function to be solved.

2. The quantum computing method for Simon's problem according to claim 1, wherein, The steps of constructing the same number of sub-Simon problem functions include: Determining a first bit in the original domain bits of the Simon problem function to be solved as the domain bit of the sub-Simon problem function, and the remaining bits as the second bits of the second domain; Extracting the first bit value from the original independent variable values in the original domain of the Simon problem function to be solved to form the sub-independent variable value of the sub-Simon problem function; Sequentially extracting the second bit values from each original independent variable value in the original domain of the Simon problem function to be solved to form the corresponding second independent variable values; Combining each sub-independent variable value of the sub-Simon problem function with each second independent variable value together in the order of their bits in the original domain to form an original independent variable value in the original domain; Obtaining the original dependent variable value corresponding to the original independent variable value from the original range of the Simon problem function to be solved as the first original dependent variable value; Determining one first original dependent variable value as the sub-dependent variable value corresponding to the sub-independent variable value according to the same value-taking function from the multiple first original dependent variable values corresponding to each sub-independent variable value, where the sub-dependent variable values corresponding to each sub-independent variable value form the range of the sub-Simon problem function.

3. The quantum computing method for Simon's problem according to claim 2, characterized in that, The steps of constructing the same number of sub-Simon problem functions include: taking each first bit in the original domain of the Simon problem function to be solved as the domain bit of a sub-Simon problem function in the order from high to low or from low to high.

4. The quantum computing method for Simon's problem according to claim 2 or 3, characterized in that, The value-taking function is a maximum function or a minimum function. Correspondingly, the step of determining a first original dependent variable value as the sub-dependent variable value corresponding to the sub-independent variable value from multiple first original dependent variable values corresponding to each sub-independent variable value according to the same value-taking function includes: determining the first original dependent variable value with the largest or smallest numerical value from multiple first original dependent variable values corresponding to each sub-independent variable value as the sub-dependent variable value corresponding to the sub-independent variable value.

5. The quantum computing method for Simon's problem according to claim 1, characterized in that, The step of mapping the value range of a sub-Simon problem function to a value range with a bit number of 1 includes: mapping each sub-dependent variable value of the sub-Simon problem function to a binary value with a bit number of 1, and when two sub-dependent variable values are the same, the mapping values corresponding to each sub-dependent variable value are the same, and are binary values 0 or 1; when two sub-dependent variable values are different, the mapping values corresponding to each sub-dependent variable value are different, and are binary values 0 and 1 respectively.

6. The quantum computing method for Simon's problem according to claim 1, wherein The Simon problem equation-solving unit is a quantum gate or a combination of quantum gates that realizes flipping between the quantum 0 state and the quantum 1 state.

7. The steps of separately running the problem function solving quantum circuit corresponding to each sub-Simon problem function in the quantum computing method for the Simon problem according to claim 1 include: Run the problem-solving quantum circuit of the sub-Simon problem function in a serial and / or parallel manner to obtain the corresponding sub-character to be solved.

8. A quantum computing device for Simon's problem, characterized in that, The device includes: A parameter acquisition module configured to acquire the number of bits of the original domain and the number of bits of the original range of the Simon problem function to be solved, wherein the original independent variable values in the original domain and the original dependent variable values in the original range are both binary numbers; A sub-Simon problem function construction module configured to construct the same number of sub-Simon problem functions based on the original domain bits and the number of original domain bits of the Simon problem function to be solved, wherein the domain bit of each sub-Simon problem function is a bit in the original domain, the value range of each sub-Simon problem function is a sub-range of the value range of the Simon problem function to be solved, and each sub-Simon problem function includes the corresponding sub-character to be solved, wherein the calculation process of each sub-character to be solved is used as a calculation node and corresponds to a quantum bit; A mapping module configured to map the value range of each sub-Simon problem function to a value range with a bit number of 1 to obtain the corresponding Deutsch problem function; A quantum circuit construction module configured to construct a problem-solving quantum circuit, wherein the problem-solving quantum circuit includes a Deutsch problem function solving unit and a Simon problem equation-solving unit connected in sequence; An operation module configured to respectively run the problem-solving quantum circuits corresponding to each sub-Simon problem function to obtain the corresponding sub-characters to be solved; A combination module configured to sequentially combine the corresponding sub-characters according to the positions of the domain bits of the sub-Simon problem functions in the original domain of the Simon problem function to be solved to obtain the string to be solved of the Simon problem function to be solved.

9. An electronic device, comprising a processor and a memory, characterized in that, The computer instructions are stored in the memory, and when the processor runs the computer instructions, it executes the quantum computing method for the Simon problem described in any one of claims 1-7.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer instructions, and when the computer instructions are run by the processor, it executes the quantum computing method for the Simon problem described in any one of claims 1-7.

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