Task Processing Method, Device, and Ground State Energy Level Determination Method Based on Quantum Computing

Abstract

This application relates to the field of quantum computing, and discloses a task processing method, device, and ground state energy level determination method based on quantum computing, including: mapping the Yang-Baxter equation into a basic quantum circuit with symmetry; determining the target number of required basic quantum circuits according to the number of qubits involved in the target task to be solved by the target substance and the number of qubits of the basic quantum circuit; the molecule of the target substance has a symmetric structure; combining the target number of basic quantum circuits to obtain a parameterized quantum circuit with symmetry; processing the target task to be solved based on the parameterized quantum circuit. Since the Yang-Baxter equation has symmetry, the parameterized quantum circuit obtained based on the Yang-Baxter equation can maintain the symmetric characteristics of chemical molecules during quantum state evolution. When solving tasks related to substances with symmetric molecular structures, unnecessary search paths can be reduced, the complexity of task solving can be reduced, and the solving efficiency can be improved.

Description

Technical Field

[0001] The present application relates to the field of quantum computing, and in particular, to a task processing method based on quantum computing, a device, a computing device, a computer-readable storage medium, and a method for determining the ground state energy level of a substance with a symmetric molecular structure. Background Art

[0002] Quantum computing refers to the process of initializing multiple qubits, then performing a series of unitary operations (corresponding to pulse operations of an actual system), and then performing measurement and analysis. Due to the existence of quantum superposition and quantum entanglement, quantum computing has the advantage of parallelism. Utilizing the quantum advantage for quantum algorithm design can accelerate the solution of some classical problems.

[0003] The variational quantum algorithm based on a parameterized quantum circuit is an important class of quantum algorithms, which are widely applied to problems such as molecular simulation and combinatorial optimization. This type of algorithm adopts a classical-quantum hybrid architecture. A parameterized quantum circuit is used to find the quantum state corresponding to the problem to be solved, the value of the loss function is solved through this quantum state, the parameters are updated by a classical optimizer, and finally converge to the extreme value of the loss function. Among them, the design of the parameterized quantum circuit is the key to solving the problem. Currently, when designing a parameterized quantum circuit, it is usually a simple combination of basic quantum gates (such as single-qubit rotation gates and two-qubit gates). For substances with symmetric molecular structures (such as water and hydrogen), the current parameterized quantum circuits cannot fully utilize the inherent characteristics of these substances when solving the problems to be solved, which will increase the computational complexity and thus lead to low efficiency in solving problems.

[0004] Therefore, how to solve the above technical problems should be the focus of attention of those skilled in the art. Summary of the Invention

[0005] The purpose of the present application is to provide a task processing method based on quantum computing, a device, a computing device, a computer-readable storage medium, and a method for determining the ground state energy level of a substance with a symmetric molecular structure, so as to reduce the complexity of task solving and improve the solving efficiency when solving tasks related to substances with symmetric molecular structures.

[0006] To solve the above technical problems, the present application provides a task processing method based on quantum computing, including:

[0007] Mapping the Yang-Baxter equation into a basic quantum circuit with symmetry;

[0008] Determining the target number of the basic quantum circuits required according to the number of qubits involved in the target task to be solved of the target substance and the number of qubits of the basic quantum circuit; the target substance has a symmetric molecular structure;

[0009] Combine the basic quantum circuits of the target quantity to obtain a parameterized quantum circuit with symmetry;

[0010] Process the target task to be solved based on the parameterized quantum circuit.

[0011] Optionally, it further includes:

[0012] Evolve the parameterized quantum circuit from the initial quantum state to the final quantum state;

[0013] Determine the expectation value of the Hamiltonian in the final quantum state to obtain the function value of the loss function for the target task to be solved;

[0014] Use the parameter gradient of the expectation value to iteratively optimize the parameters in the loss function until the function value is less than a preset threshold, and use the corresponding parameters as the final parameters in the parameterized quantum circuit.

[0015] Optionally, before evolving the parameterized quantum circuit from the initial quantum state to the final quantum state, it further includes:

[0016] Map the original data corresponding to the target task to be solved into a vector;

[0017] Perform normalization processing on the vector to determine the initial quantum state.

[0018] Optionally, before using the parameter gradient of the expectation value to iteratively optimize the parameters in the loss function, it further includes:

[0019] Determine the parameter gradient of the expectation value.

[0020] This application also provides a task processing device based on quantum computing, including:

[0021] A first mapping module, configured to map the Yang-Baxter equation into a basic quantum circuit with symmetry;

[0022] A first determination module, configured to determine the target quantity of the basic quantum circuits required according to the number of bits involved in the target task to be solved of the target substance and the number of bits of the basic quantum circuit; the target substance has a symmetric molecular structure;

[0023] A combination module, configured to combine the basic quantum circuits of the target quantity to obtain a parameterized quantum circuit with symmetry;

[0024] A processing module, configured to process the target task to be solved based on the parameterized quantum circuit.

[0025] Optionally, it further includes:

[0026] An evolution module for evolving the parameterized quantum circuit from the initial quantum state to the final quantum state;

[0027] A second determination module for determining the expected value of the Hamiltonian in the final quantum state to obtain the function value of the loss function for the target task to be solved;

[0028] An iteration module for iteratively optimizing the parameters in the loss function using the parameter gradient of the expected value until the function value is less than a preset threshold, and taking the corresponding parameters as the final parameters in the parameterized quantum circuit.

[0029] Optionally, it further includes:

[0030] A second mapping module for mapping the original data corresponding to the target task to be solved into a vector;

[0031] A normalization module for normalizing the vector to determine the initial quantum state.

[0032] This application also provides a computing device, including:

[0033] A memory for storing computer programs;

[0034] A processor for implementing the steps of any one of the above-mentioned quantum computing-based task processing methods when executing the computer program.

[0035] This application also provides a computer-readable storage medium, on which a computer program is stored, and the computer program, when executed by a processor, implements the steps of any one of the above-mentioned quantum computing-based task processing methods.

[0036] This application also provides a method for determining the ground state energy level of a substance with a symmetric molecular structure, and the method for determining the ground state energy level is implemented based on any one of the above-mentioned methods, where the target task to be solved includes determining the ground state energy level of the substance.

[0037] A quantum computing-based task processing method provided by this application includes: mapping the Yang-Baxter equation into a basic quantum circuit with symmetry; determining the target number of the basic quantum circuits required according to the number of bits involved in the target task to be solved of the target substance and the number of bits of the basic quantum circuit; the target substance has a symmetric molecular structure; combining the target number of the basic quantum circuits to obtain a parameterized quantum circuit with symmetry; processing the target task to be solved based on the parameterized quantum circuit.

[0038] It can be seen that when solving the task regarding substances with symmetric structures in this application, the Yang-Baxter equation is mapped into a basic quantum circuit, and then a parameterized quantum circuit with symmetry is constructed based on the basic quantum circuit, and then the parameterized quantum circuit is used to solve the target task. The Yang-Baxter equation has symmetry, so the parameterized quantum circuit obtained based on the Yang-Baxter equation can maintain the symmetric characteristics of chemical molecules in the quantum state evolution. When solving the task regarding substances with symmetric molecular structures, unnecessary search paths can be reduced, the complexity of task solving can be lowered, and the solving efficiency can be improved.

[0039] In addition, this application also provides a device, a computing device, and a computer-readable storage medium having the above advantages. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] In order to more clearly illustrate the technical solutions of the embodiments of this application or the prior art, the following will briefly introduce the drawings required to be used in the description of the embodiments or the prior art. Obviously, the following-described drawings are only some embodiments of this application. For those of ordinary skill in the art, other drawings can also be obtained based on these drawings without creative efforts.

[0041] Figure 1 It is a flowchart of a task processing method based on quantum computing provided by an embodiment of this application;

[0042] Figure 2 It is a flowchart of a method for determining parameters in a parameterized quantum circuit provided by an embodiment of this application;

[0043] Figure 3 It is a framework diagram of a task processing method based on quantum computing provided by an embodiment of this application;

[0044] Figure 4 It is an optimization result diagram of a parameterized quantum circuit constructed by this application;

[0045] Figure 5 It is an optimization result diagram of a traditional parameterized quantum circuit;

[0046] Figure 6 It is a structural block diagram of a task processing device based on quantum computing provided by an embodiment of this application;

[0047] Figure 7 It is a structural block diagram of a computing device provided by an embodiment of this application. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0048] To enable those skilled in the art to better understand the solution of this application, the following further detailed description of this application will be given in conjunction with the accompanying drawings and specific embodiments. Obviously, the described embodiments are only a part of the embodiments of this application, rather than all the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments in this application without creative efforts shall fall within the scope of protection of this application.

[0049] As described in the background art section, currently when designing parameterized quantum circuits, it is usually a simple combination of basic quantum gates (such as single-qubit rotation gates and two-qubit gates). For substances with symmetric molecular structures, the current parameterized quantum circuits cannot make full use of the intrinsic characteristics of these substances when solving problems that need to be solved, which will increase the computational complexity and thus lead to relatively low efficiency in solving problems.

[0050] In view of this, this application provides a task processing method based on quantum computing. Please refer to Figure 1 , including:

[0051] Step S101: Map the Yang-Baxter equation into a basic quantum circuit with symmetry.

[0052] The Yang-Baxter equation (Yang-Baxter, YBE), also known as the Yang-Baxter equation, the braiding operator in the Yang-Baxter equation is a universal quantum gate and has a close relationship with quantum entanglement. The Yang-Baxter equation can be applied to quantum correlation and topological quantum computing.

[0053] The Yang-Baxter equation can be described as:

[0054] R 12 (u)R 23 (w)R 12 (v) = R 23 (v)R 12 (w)R 23 (u) (1)

[0055] where u and v are spectral parameters.

[0056] The Lorentz-like transformation relationship of spectral parameters is:

[0057] w = (u + v) / ((1 - uv / c 2 )) (2)

[0058] where u and v are spectral parameters and c is the speed of light.

[0059] where is the Yang-Baxter matrix acting on the first particle and the second particle, is the Yang-Baxter matrix acting on the second particle and the third particle.

[0060] Replace \(u\), \(w\), \(v\) with \(\theta_1\), \(\theta_2\), \(\theta_3\), and the matrix \(R(\theta\) i ) is represented in the following form:

[0061]

[0062] Then there is \(R\) 12 (\(\theta_1\)) \(R\) 23 (\(\theta_2\)) \(R\) 12 (\(\theta_3\)) = \(R\) 23 (\(\theta_3\)) \(R\) 12 (\(\theta_2\)) \(R\) 23 (\(\theta_1\)) (4)

[0063] Among them, the Lorentz transformation conditions are satisfied:

[0064] \(R\) 12 (\(\theta_1\)) \(R\) 23 (\(\theta_2\)) \(R\) 12 (\(\theta_3\)) can be represented by the following quantum circuit:

[0065]

[0066] \(R(\theta)\) can be decomposed into quantum gates in the following form:

[0067]

[0068] Among them, the decomposed quantum gates are composed of single-qubit gates and CNOT gates. The single-qubit gate \(R\) x,y,z (\(\theta\)) represents a rotation of \(\theta\) angles around the \(x\)-axis, \(y\)-axis, and \(z\)-axis respectively.

[0069] According to the above content, combining two sets of Yang-Baxter equation type circuits together gives a basic quantum circuit with symmetry. The basic quantum circuit \(A\) is:

[0070]

[0071] Among them, the Lorentz transformation conditions are satisfied:

[0072]

[0073]

[0074]

[0075] The basic quantum circuit \(A\) is symmetric up and down, and the number of qubits is 4.

[0076] Step S102: Determine the target number of the basic quantum circuits required according to the number of bits involved in the target task to be solved for the target substance and the number of bits of the basic quantum circuit; the target substance has a symmetric molecular structure.

[0077] It should be noted that the target task to be solved in this application is not limited and depends on the situation. For example, the target task to be solved can be to solve the ground state energy level, etc.

[0078] The number of bits involved in the target task to be solved is a multiple of 4.

[0079] When the number of bits involved in the target task to be solved is 4, the target number of the basic quantum circuits required is 1; when the number of bits involved in the target task to be solved is 8, the target number of the basic quantum circuits required is 5; when the number of bits involved in the target task to be solved is 12, the target number of the basic quantum circuits required is 8; when the number of bits involved in the target task to be solved is 16, the target number of the basic quantum circuits required is 11; and so on. When the number of bits involved in the target task to be solved is greater than 8, for every 4 increase in the number of bits involved in the target task to be solved, the target number of the basic quantum circuits required increases by 3.

[0080] It should be noted that the target substance in this application is not limited. For example, it can be a substance with a symmetric structure such as a chemical molecule like water or hydrogen.

[0081] Step S103: Combine the target number of the basic quantum circuits to obtain a parameterized quantum circuit with symmetry.

[0082] For example, when the target number is 1, the parameterized quantum circuit is the basic quantum circuit.

[0083] When the target number is 5, the parameterized quantum circuit is as follows. The parameterized quantum circuit includes a total of 5 basic quantum circuits, namely A1, A2, A4, A6, and A7.

[0084]

[0085] When the target number is 8, the parameterized quantum circuit is as follows. The parameterized quantum circuit includes a total of 8 basic quantum circuits, namely A1, A2, A3, A4, A5, A6, A7, and A8.

[0086]

[0087] When the target number is more, the parameterized quantum circuit follows the same pattern.

[0088] Step S104: Process the target task to be solved based on the parameterized quantum circuit.

[0089] The process of handling the target task to be solved can refer to the related technology, which will not be elaborated in detail in this application.

[0090] Based on the basic quantum circuit corresponding to the Yang-Baxter equation to construct a parameterized quantum circuit can ensure the uniform distribution of entanglement in the subsystem of the parameterized quantum circuit, which is applicable to solving problems with symmetry and is more efficient than general parameterized quantum circuits.

[0091] In this embodiment, when solving the task regarding substances with a symmetric structure, the Yang-Baxter equation is mapped into a basic quantum circuit, and then a parameterized quantum circuit with symmetry is constructed based on the basic quantum circuit, and then the parameterized quantum circuit is used to solve the target task. Since the Yang-Baxter equation has symmetry, the parameterized quantum circuit obtained based on the Yang-Baxter equation can maintain the symmetric characteristics of chemical molecules in the quantum state evolution. When solving the task regarding substances with a symmetric molecular structure, unnecessary search paths can be reduced, the complexity of task solving can be lowered, and the solving efficiency can be improved.

[0092] Based on the above embodiment, in an embodiment of the present application, the task processing method based on quantum computing may further include the process of determining the parameters in the parameterized quantum circuit, and the method for determining the parameters in the parameterized quantum circuit is as Figure 2 shown, including:

[0093] Step S201: Evolve the parameterized quantum circuit from the initial quantum state to the final quantum state.

[0094] Optionally, in an embodiment of the present application, before evolving the parameterized quantum circuit from the initial quantum state to the final quantum state, it further includes:

[0095] Map the original data corresponding to the target task to be solved into a vector;

[0096] Perform normalization processing on the vector to determine the initial quantum state.

[0097] The original data depends on the specific target task to be solved, and this application does not make specific limitations. For example, when the target task to be solved is to solve the ground state energy level, the original data is ground state information data, including orbital information, orbital arrangement information, etc.

[0098] Step S202: Determine the expectation value of the Hamiltonian at the final quantum state to obtain the function value of the loss function regarding the target task to be solved.

[0099] The expected value of the Hamiltonian of the target substance in the final quantum state can be measured in a quantum computer. Compared with encoding data with 0 and 1 in a traditional computer, a quantum computer uses a quantum superposition state α|0> + β|1> for encoding, where both α and β are complex numbers, and |α| 2 +|β| 2 = 1, which is the quantum amplitude.

[0100] The expected value of the Hamiltonian in the final quantum state is the function value of the loss function.

[0101] The parameters in the loss function are the same as those in the parameterized quantum circuit.

[0102] Step S203: Use the parameter gradient of the expected value to iteratively optimize the parameters in the loss function until the function value is less than a preset threshold, and use the corresponding parameters as the final parameters in the parameterized quantum circuit.

[0103] It should be noted that in this application, the preset threshold is not limited and depends on the situation. The function value being less than the preset threshold means that the expected value is less than the preset threshold.

[0104] It should also be noted that in this application, the way of parameter optimization iteration is not limited and can be selected by oneself. For example, the gradient descent algorithm can be used.

[0105] Each set of parameters corresponds to a function value (i.e., the expected value). When the parameters in the loss function change gradually according to the parameter gradient, the corresponding function value also changes. The purpose of iteratively optimizing the parameters is to obtain the extreme value of the loss function.

[0106] When the function value is less than the preset threshold, the parameters corresponding to this function value are the parameters in the obtained parameterized quantum circuit.

[0107] It should be pointed out that steps S201 to S203 are also the process of determining the ground state energy level, and the function value less than the preset threshold is the ground state energy level.

[0108] The parameter gradient of the expected value used in this embodiment can be already determined and directly used in this step. However, this application does not limit this. In an embodiment of this application, before using the parameter gradient of the expected value to iteratively optimize the parameters in the loss function, it may further include:

[0109] Determine the parameter gradient of the expected value.

[0110] Next, in combination with Figure 3 the framework diagram of the task processing method based on quantum computing shown, the task processing method based on quantum computing in this application will be elaborated.

[0111] Step 1: Preprocess the original data information and obtain a vector containing the data information through mapping transformation;

[0112] Step 2: Normalize the mapped vector to prepare the initial state of the quantum state;

[0113] Step 3: Map the Yang - Baxter equation into a basic quantum circuit with symmetry;

[0114] Step 4: Combine a series of basic quantum circuits to obtain a parameterized quantum circuit with symmetry;

[0115] Step 5: Execute the quantum evolution process corresponding to the parameterized quantum circuit on a quantum computer, evolving from the initial quantum state to the final quantum state;

[0116] Step 6: Measure the expected value of the Hamiltonian in the final quantum state on a quantum computer to obtain the loss function;

[0117] Step 7: Solve the parameter gradient of the measured expected value through a classical optimizer and iteratively optimize the parameters in the parameterized quantum circuit (parameters in the loss function). When the expected value of the Hamiltonian reaches the minimum, the quantum state simultaneously evolves to the solution of the problem;

[0118] Step 8: Use the parameterized quantum circuit to perform information - processing tasks.

[0119] This application also provides a method for determining the ground - state energy level of a substance with a symmetric molecular structure. The method for determining the ground - state energy level is implemented based on the quantum - computing - based task - processing method described in any of the above embodiments. As an implementable manner, the method for determining the ground - state energy level includes:

[0120] Map the Yang - Baxter equation into a basic quantum circuit with symmetry;

[0121] According to the number of qubits involved in the ground - state energy level of the target substance and the number of qubits of the basic quantum circuit, obtain the target number of the basic quantum circuits required to determine the ground - state energy level of the target substance; the target substance has a symmetric molecular structure;

[0122] Combine the target number of the basic quantum circuits to obtain a parameterized quantum circuit with symmetry;

[0123] Determine the ground - state energy level of the target substance based on the parameterized quantum circuit.

[0124] Taking the solution of the ground state energy level of the hydrogen molecule as an example, the solution of the parameterized quantum circuit constructed according to the Yang-Baxter equation in this application and the traditional parameterized quantum circuit is simulated and compared. In the simulation comparison, except for the parameterized quantum circuit, the classical optimization algorithm is the same, and the initial parameters are all 4 random numbers from 0 to 1.

[0125] The Hamiltonian of the hydrogen molecule is:

[0126] -0.10828642633408778 -0.045413740730899495[X0 X1 Y2 Y3]+0.045413740730899495[X0 Y1 Y2 X3]+0.045413740730899495[Y0X1 X2 Y3]-0.045413740730899495[Y0 Y1 X2 X3]+0.17287043695155[Z0]+0.1685408730798563[Z0Z1]+0.12056020320710414[Z0 Z2]+0.16597394393800363[Z0 Z3]+0.1728704369515501[Z1]+0.16597394393800363[Z1 Z2]+0.12056020320710414[Z1Z3]-0.22066557903984965[Z2]+0.17467628158972687[Z2 Z3]-0.22066557903984968[Z3]

[0127] Where [] represents the direct product operation of the internal Pauli matrices, and the identity matrix is omitted. This Hamiltonian contains 4 qubits, so the parameterized quantum circuit constructed in this application is:

[0128]

[0129] The traditional parameterized quantum circuit is:

[0130]

[0131] The number of parameters required for the parameterized quantum circuit constructed in this application and the traditional parameterized quantum circuit is both 4.

[0132] Through analytical calculation, it can be known that the ground state energy level of this Hamiltonian is -2.29. The maximum number of optimization iterations is set to 400, and the cut-off condition is set to -2.25, that is, stop when the value of the loss function is less than -2.25. The optimization results of the parameterized quantum circuit constructed in this application and the traditional parameterized quantum circuit are respectively as Figure 4 and Figure 5As shown, where the abscissa is the number of iterations and the ordinate is the value of the loss function. From Figure 4 and Figure 5 it can be seen that for the Yang-Baxter type parameterized quantum circuit in this application, it takes about 40 times to optimize the value of the loss function below the preset threshold (-2.25). However, when the traditional parameterized quantum circuit reaches the maximum number of iterations, it still cannot optimize the value of the loss function below the preset threshold. This fully demonstrates the superiority of the Yang-Baxter type parameterized quantum circuit in this application when solving some problems with symmetric structures.

[0133] It should be noted that the ground state energy level determination method in this application can also be used to determine the ground state energy levels of other substances with symmetric molecular structures such as water molecules.

[0134] Next, the task processing device based on quantum computing provided in the embodiments of this application will be introduced. The task processing device based on quantum computing described below can be mutually corresponding and referenced with the quantum computing-based task processing method described above.

[0135] Figure 6 is the structural block diagram of the task processing device based on quantum computing provided in the embodiments of this application. Referring to Figure 6 The task processing device based on quantum computing may include:

[0136] A first mapping module 100, configured to map the Yang-Baxter equation into a basic quantum circuit with symmetry;

[0137] A first determination module 200, configured to determine the target number of the basic quantum circuits required according to the number of bits involved in the target task to be solved of the target substance and the number of bits of the basic quantum circuit; the target substance has a symmetric molecular structure;

[0138] A combination module 300, configured to combine the target number of the basic quantum circuits to obtain a parameterized quantum circuit with symmetry;

[0139] A processing module 400, configured to process the target task to be solved based on the parameterized quantum circuit.

[0140] The task processing device based on quantum computing in this embodiment is used to implement the aforementioned task processing method based on quantum computing. Therefore, the specific implementation manners in the task processing device based on quantum computing can be seen in the embodiment part of the task processing method based on quantum computing in the previous text. For example, the first mapping module 100, the first determination module 200, the combination module 300, and the processing module 400 are respectively used to implement steps S101, S102, S103, and S104 in the aforementioned task processing method based on quantum computing. Therefore, the specific implementation manners can be referred to the descriptions of the corresponding respective part embodiments and will not be elaborated herein.

[0141] Optionally, the task processing device based on quantum computing further includes:

[0142] An evolution module, configured to evolve the parameterized quantum circuit from the initial quantum state to the final quantum state;

[0143] A second determination module, configured to determine the expectation value of the Hamiltonian in the final quantum state to obtain the function value of the loss function for the target task to be solved;

[0144] An iteration module, configured to iteratively optimize the parameters in the loss function using the parameter gradient of the expectation value until the function value is less than a preset threshold, and use the corresponding parameters as the final parameters in the parameterized quantum circuit.

[0145] Optionally, the task processing device based on quantum computing further includes:

[0146] A second mapping module, configured to map the original data corresponding to the target task to be solved into a vector;

[0147] A normalization module, configured to perform normalization processing on the vector to determine the initial quantum state.

[0148] Optionally, the task processing device based on quantum computing further includes:

[0149] A third determination module, configured to determine the parameter gradient of the expectation value.

[0150] Next, the computing device provided in the embodiments of the present application will be introduced. The computing device described below can be correspondingly referred to the task processing method based on quantum computing described above.

[0151] As Figure 7 shown, the present application further provides a computing device, including:

[0152] A memory 11, configured to store a computer program;

[0153] A processor 12, which is configured to implement the steps of the quantum-computing-based task processing method according to any of the above embodiments when executing the computer program.

[0154] The following introduces the computer-readable storage medium provided by the embodiments of the present application. The computer-readable storage medium described below can be correspondingly referred to the quantum-computing-based task processing method described above.

[0155] A computer-readable storage medium, on which a computer program is stored, and the computer program, when executed by a processor, implements the steps of the quantum-computing-based task processing method according to any of the above embodiments.

[0156] The embodiments in this specification are described in a progressive manner. Each embodiment focuses on the differences from other embodiments. The same or similar parts among the embodiments can be referred to each other. For the devices disclosed in the embodiments, since they correspond to the methods disclosed in the embodiments, the description is relatively simple. For the relevant parts, refer to the description of the method part.

[0157] Those skilled in the art can further realize that the units and algorithm steps of each example described in combination with the embodiments disclosed in this article can be implemented by electronic hardware, computer software, or a combination of the two. To clearly illustrate the interchangeability of hardware and software, the components and steps of each example have been generally described according to functions in the above description. Whether these functions are executed in a hardware or software manner depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered to exceed the scope of this application.

[0158] The steps of the method or algorithm described in combination with the embodiments disclosed in this article can be directly implemented by hardware, a software module executed by a processor, or a combination of the two. The software module can be placed in a random access memory (RAM), internal memory, read-only memory (ROM), electrically programmable ROM, electrically erasable programmable ROM, registers, hard disk, removable disk, CD-ROM, or any other form of storage medium well-known in the technical field.

[0159] The above has introduced in detail the task processing method, device, computing device, computer-readable storage medium provided by the present application, and the method for determining the ground state energy level of a substance with a symmetric molecular structure. Specific examples are used in this article to elaborate on the principle and implementation manner of the present application. The description of the above embodiments is only used to help understand the method and its core idea of the present application. It should be noted that for those of ordinary skill in the art, without departing from the principle of the present application, several improvements and modifications can be made to the present application, and these improvements and modifications also fall within the protection scope of the claims of the present application.

Claims

1. A task processing method based on quantum computing, characterized in that, Including: Mapping the Yang-Baxter equation into a basic quantum circuit with symmetry; The basic quantum circuit is symmetric up and down. The basic quantum circuit includes R(θ1), R(θ3), R(θ4), R(θ6), R(θ YB ). R(θ1) and R(θ3) act on the first two qubits, R(θ4) and R(θ6) act on the last two qubits, and R(θ YB ) acts on the middle two qubits. Combining two sets of Yang-Baxter equation type circuits together gives the symmetric basic quantum circuit. The number of qubits of the basic quantum circuit is 4. The basic quantum circuit A is: ； Among them, the Yang-Baxter equation is: ; where u and v are spectral parameters; The Lorentz-like transformation relationship of spectral parameters is: ; where u and v are spectral parameters, and c is the speed of light; Among them, is the Yang-Baxter matrix acting on the first particle and the second particle, is the Yang-Baxter matrix acting on the second particle and the third particle; Replace \(u\), \(w\), \(v\) with \(\theta_1\), \(\theta_2\), \(\theta_3\), and the matrix \(R(\theta i )\) is represented in the following form: ； Satisfying the Lorentz transformation condition: ； ； ； According to the number of bits involved in the target task to be solved of the target substance and the number of bits of the basic quantum circuit, determining the target number of the required basic quantum circuits; the target substance has a symmetric molecular structure; Combining the target number of the basic quantum circuits to obtain a parameterized quantum circuit with symmetry; Processing the target task to be solved based on the parameterized quantum circuit.

2. The task processing method based on quantum computing according to claim 1, wherein Also including: Evolving the parameterized quantum circuit from the initial quantum state to the final quantum state; Determining the expectation value of the Hamiltonian at the final quantum state to obtain the function value of the loss function for the target task to be solved; Using the parameter gradient of the expectation value to iteratively optimize the parameters in the loss function until the function value is less than a preset threshold, and taking the corresponding parameters as the final parameters in the parameterized quantum circuit.

3. The task processing method based on quantum computing according to claim 2, wherein Before evolving the parameterized quantum circuit from the initial quantum state to the final quantum state, it also includes: Mapping the original data corresponding to the target task to be solved into a vector; Normalizing the vector to determine the initial quantum state.

4. The task processing method based on quantum computing according to claim 2, wherein, Before using the parameter gradient of the expectation value to iteratively optimize the parameters in the loss function, it also includes: Determining the parameter gradient of the expectation value.

5. A task processing device based on quantum computing, characterized in that, Including: A first mapping module for mapping the Yang-Baxter equation into a basic quantum circuit with symmetry; The basic quantum circuit is symmetric up and down. The basic quantum circuit includes R(θ1), R(θ3), R(θ4), R(θ6), R(θ YB ). R(θ1) and R(θ3) act on the first two qubits, R(θ4) and R(θ6) act on the last two qubits, and R(θ YB ) acts on the middle two qubits. Combining two sets of Yang-Baxter equation type circuits together gives the symmetric basic quantum circuit. The number of qubits of the basic quantum circuit is 4. The basic quantum circuit A is: ； Among them, the Yang-Baxter equation is: ; where u and v are spectral parameters; The Lorentz-like transformation relationship of spectral parameters is: ; where u and v are spectral parameters, and c is the speed of light; Among them, is the Yang-Baxter matrix acting on the first particle and the second particle, is the Yang-Baxter matrix acting on the second particle and the third particle; Replace \(u\), \(w\), \(v\) with \(\theta_1\), \(\theta_2\), \(\theta_3\), and the matrix \(R(\theta i )\) is represented in the following form: ； Satisfying the Lorentz transformation condition: ； ； ； A first determination module for determining the target number of the required basic quantum circuits according to the number of bits involved in the target task to be solved of the target substance and the number of bits of the basic quantum circuit; the target substance has a symmetric molecular structure; A combination module for combining the target number of the basic quantum circuits to obtain a parameterized quantum circuit with symmetry; A processing module for processing the target task to be solved based on the parameterized quantum circuit.

6. The task processing device based on quantum computing according to claim 5, characterized in that, Also including: An evolution module for evolving the parameterized quantum circuit from the initial quantum state to the final quantum state; A second determination module for determining the expectation value of the Hamiltonian at the final quantum state to obtain the function value of the loss function for the target task to be solved; An iteration module for using the parameter gradient of the expectation value to iteratively optimize the parameters in the loss function until the function value is less than a preset threshold, and taking the corresponding parameters as the final parameters in the parameterized quantum circuit.

7. The task processing device based on quantum computing according to claim 6, wherein Also including: A second mapping module for mapping the original data corresponding to the target task to be solved into a vector; A normalization module for normalizing the vector to determine the initial quantum state.

8. A computing device, characterized in that, Including: A memory for storing computer programs; A processor for implementing the steps of the task processing method based on quantum computing according to any one of claims 1 to 4 when executing the computer program.

9. A computer-readable storage medium, characterized in that, A computer program is stored on the computer-readable storage medium. When the computer program is executed by a processor, the steps of the task processing method based on quantum computing according to any one of claims 1 to 4 are implemented.

10. A method for determining the ground state energy level of a substance with a symmetric molecular structure, characterized in that, The ground state energy level determination method is implemented based on the method according to any one of claims 1 to 4, wherein the target task to be solved includes the determination of the ground state energy level of a substance.

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