A method and device for calculating protein molecular configuration
The quantum imaginary time evolution algorithm efficiently calculates protein molecular configurations using fewer resources and simplified quantum gates, addressing the computational challenges of classical computers by leveraging quantum computing.
Patent Information
- Application Number
- CN202211724298.1
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- Filing Date
- 2022-12-30
- Publication Date
- 2024-12-24
- Estimated Expiration
- 2042-12-30
Smart Images
Figure CN116189788B_ABST
Abstract
Description
Technical Field
[0001] The present invention relates to the field of quantum computing, and in particular to a method and device for computing protein molecular configuration. Background Art
[0002] Protein molecular configuration is an important research topic in biochemistry. In living organisms, proteins are the carriers and bearers of cell functions, responsible for performing most cell functions. The structure of protein is the three-dimensional arrangement of atoms in the amino acid chain molecule. The atoms in the molecule fold into a specific spatial configuration through hydrogen bonds, ionic interactions, van der Waals forces, hydrophobic interactions, etc. For most proteins, their three-dimensional structure determines their specific functions. In order to better study the important role of proteins in the process of life activities, we need to understand protein structure and study protein functions.
[0003] In today's era of rapid development of biotechnology, protein molecular configuration and its function have become important research topics in disciplines such as biochemistry, and its research results have also been widely used in disease treatment, drug target design, enzyme activity promotion and inhibition, protein engineering, etc. Many of these research results have made significant contributions to human understanding of the significance of protein in life activities and metabolism, and have been awarded the Nobel Prize. As people's research needs become more and more in-depth, we need to understand more and more complex protein molecular configurations, and even need to predict some protein molecular configurations. When the number of atoms in a protein molecule is large, the amount of calculation required is also increasing, and classical computers are increasingly unable to do this job. Quantum computers can greatly reduce the computational complexity of such problems, thus showing great advantages. Summary of the invention
[0004] The present application aims to provide a method and device for calculating the configuration of protein molecules, which can utilize fewer physical resources and be more efficient through quantum algorithms. The scheme is simple, and the selected parameter-containing quantum gates are also easy to implement on recent noisy medium-sized quantum computers.
[0005] According to one aspect of the present application, a method for calculating the molecular configuration of a protein is provided, comprising:
[0006] Given the Pauli operator form of the Hamiltonian of the protein molecular configuration, for each term in the Hamiltonian, a quantum circuit diagram is constructed using a quantum imaginary time evolution algorithm;
[0007] Executing the quantum circuit diagram so that the initial quantum state passes through the quantum circuit diagram to obtain a quantum final state;
[0008] Determining whether the quantum final state is the desired target state through the auxiliary bit measurement result, so as to obtain the ground state energy of the protein molecule;
[0009] Based on the ground state energy of the protein molecule, the configuration information of the protein molecule is obtained.
[0010] According to some embodiments, the method comprises:
[0011] The method of judging whether the quantum final state is the desired target state by the auxiliary bit measurement result to obtain the ground state energy of the protein molecule includes:
[0012] Repeatedly measure the energy average value of the quantum state under the Hamiltonian, and determine if the variation of the energy average value is less than a threshold value, then obtain the ground state energy of the protein molecule.
[0013] According to some embodiments, the method further comprises:
[0014] According to the Pauli operator form of the Hamiltonian of the protein molecular configuration, the Hartley Fock state of the protein molecular configuration is calculated using a classical algorithm, and the Hartley Fock state is used as the initial quantum state.
[0015] According to some embodiments, the method comprises:
[0016] The executing the quantum circuit diagram so that the initial quantum state obtains a quantum final state through the quantum circuit diagram includes:
[0017] For each item in the Hamiltonian, an auxiliary bit with an initial quantum state of |0> is introduced, and an executable quantum circuit diagram is generated according to the Pauli operator of the current item of the Hamiltonian.
[0018] According to some embodiments, the method comprises:
[0019] The generating an executable quantum circuit diagram according to the Pauli operator of the current term of the Hamiltonian further includes:
[0020] The quantum circuit diagram is represented as a series of basic quantum gate operations, and the quantum evolution process corresponding to the quantum circuit diagram is executed by a quantum computer to obtain a quantum final state.
[0021] According to some embodiments, the method comprises:
[0022] The method of judging whether the quantum final state is the desired target state by the auxiliary bit measurement result to obtain the ground state energy of the protein molecule also includes:
[0023] Measure the auxiliary bit. When the auxiliary bit is at |0>, calculate the quantum final state |ψ> of the current term of Hamiltonian after the imaginary time evolution with a step length of Δt, expressed as |ψ>=A*exp(-c k h kΔt)|ψ0>,
[0024] Among them, A is the normalization coefficient, c k is the coefficient of the kth term of the Hamiltonian, h k is the Pauli matrix of the kth term of the Hamiltonian, Δt is the step size of the imaginary time evolution, and ψ0 is the initial quantum state.
[0025] According to some embodiments, the method comprises:
[0026] The repeatedly measuring the energy average value of the quantum state under the Hamiltonian and determining if the variation of the energy average value is less than a threshold value, then obtaining the ground state energy of the protein molecule comprises:
[0027] When all terms in the Hamiltonian are calculated, the average energy of the quantum final state under the Hamiltonian is repeatedly measured.
[0028] According to some embodiments, the method comprises:
[0029] The method of repeatedly measuring the energy average value of the quantum state under the Hamiltonian and determining if the variation of the energy average value is less than a threshold value, then obtaining the ground state energy of the protein molecule, further includes:
[0030] The energy average value of the quantum state under the Hamiltonian is repeatedly measured until the difference between the energy average values measured twice in succession is less than a threshold value, and then the energy average value obtained by the last measurement is output.
[0031] According to another aspect of the present application, a device for calculating the folding configuration of a protein molecule is provided, comprising at least one quantum processor and at least one classical processor, a quantum register communicatively connected to the at least one quantum processor, and a memory and a classical register communicatively connected to the at least one quantum processor and the at least one classical processor; wherein the memory is used to store execution instructions, and the at least one quantum processor and the at least one classical processor are used to execute according to the execution instructions.
[0032] The quantum processor is configured as follows:
[0033] A Pauli operator form of a Hamiltonian of a given protein molecule configuration is used to construct a quantum circuit diagram for each item in the Hamiltonian using a quantum imaginary time evolution algorithm; the quantum circuit diagram is executed so that an initial quantum state passes through the quantum circuit diagram to obtain a quantum final state; whether the quantum final state is a desired target state is determined by an auxiliary bit measurement result to obtain the ground state energy of the protein molecule; and configuration information of the protein molecule is obtained based on the ground state energy of the protein molecule;
[0034] The classical register is configured to store measurement results and parameter data of the quantum register.
[0035] According to some embodiments, the quantum processor is further configured to:
[0036] Repeatedly measure the energy average value of the quantum state under the Hamiltonian, and determine if the variation of the energy average value is less than a threshold value, then obtain the ground state energy of the protein molecule.
[0037] According to the exemplary embodiments of the present application, by utilizing quantum algorithms, fewer physical resources can be utilized and the process can be more efficient. The scheme is simple, and the selected parameter-containing quantum gates are also easy to implement on recent noisy medium-sized quantum computers.
[0038] It should be understood that the foregoing general description and the following detailed description are exemplary only and are not restrictive of the present application. BRIEF DESCRIPTION OF THE DRAWINGS
[0039] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings required for describing the embodiments are briefly introduced below.
[0040] Figure 1 A flow chart of a method for calculating the configuration of a protein molecule according to an exemplary embodiment of the present application is shown.
[0041] Figure 2 A schematic diagram of a method for calculating the configuration of a protein molecule according to an exemplary embodiment of the present application is shown.
[0042] Figure 3 A schematic diagram of a quantum circuit for calculating the configuration of a protein molecule according to an exemplary embodiment of the present application is shown.
[0043] Figure 4 A block diagram showing an apparatus for calculating the configuration of a protein molecule according to an exemplary embodiment of the present application. DETAILED DESCRIPTION
[0044] Example embodiments will now be described more fully with reference to the accompanying drawings. However, example embodiments can be implemented in many forms and should not be construed as limited to the embodiments set forth herein; rather, these embodiments are provided so that this application will be comprehensive and complete and will fully convey the concepts of the example embodiments to those skilled in the art. The same reference numerals in the figures represent the same or similar parts, and thus their repeated description will be omitted.
[0045] In addition, described feature, structure or characteristic can be combined in one or more embodiments in any suitable manner. In the following description, many specific details are provided to provide a full understanding of the embodiments of the present application. However, those skilled in the art will appreciate that the technical scheme of the present application can be put into practice without one or more of the specific details, or other methods, components, devices, steps, etc. can be adopted. In other cases, known methods, devices, realizations or operations are not shown or described in detail to avoid blurring the various aspects of the application.
[0046] The block diagrams shown in the accompanying drawings are merely functional entities and do not necessarily correspond to physically independent entities. That is, these functional entities may be implemented in software form, or in one or more hardware modules or integrated circuits, or in different networks and / or processor devices and / or microcontroller devices.
[0047] The flowcharts shown in the accompanying drawings are only exemplary and do not necessarily include all the contents and operations / steps, nor must they be executed in the order described. For example, some operations / steps can be decomposed, and some operations / steps can be combined or partially combined, so the actual execution order may change according to actual conditions.
[0048] It should be understood that although the terms first, second, third, etc. may be used herein to describe various components, these components should not be limited by these terms. These terms are used to distinguish one component from another component. Therefore, the first component discussed below can be referred to as the second component without departing from the teachings of the concepts of the present application. As used herein, the term "and / or" includes any one of the associated listed items and all combinations of one or more.
[0049] Those skilled in the art will appreciate that the drawings are merely schematic diagrams of example embodiments, and the modules or processes in the drawings are not necessarily necessary for implementing the present application, and therefore cannot be used to limit the scope of protection of the present application.
[0050] The folding configuration problem of protein molecules is a complex multi-body problem. Protein molecules contain many atoms and have a complex structure. There are complex two-body, three-body and other multi-body interactions between atoms. Calculations usually require a huge amount of computing power, and using classical computers requires a lot of time and space costs.
[0051] The classical method for calculating the configuration of protein molecules requires solving the eigenvalues of the Hamiltonian matrix. The dimension of the matrix is exponentially related to the number of atoms in the molecule, and the amount of computation required to solve the eigenvalues of the matrix is polynomially related to the dimension of the matrix. Therefore, even simulating simple protein molecules requires huge computing resources, which brings great difficulties to classical calculations.
[0052] As the demand for research on protein molecular configurations becomes more and more in-depth, we need to understand more and more complex protein molecular configurations, and even need to predict some protein molecular configurations. When the number of atoms in a protein molecule is large, the amount of calculation required is also increasing, and classical computers are increasingly unable to handle this task. Quantum computers can greatly reduce the computational complexity of such problems, thus showing great advantages.
[0053] After quantum computers mature, this technology route can be applied to cutting-edge biotechnology fields to calculate and predict the configuration of complex protein molecules and their biological functions, greatly reducing the difficulty of calculations.
[0054] Currently, there are a variety of quantum imaginary-time evolution algorithms that can predict the molecular configuration of protein molecules, but they have disadvantages such as a large number of auxiliary bits, the need for more complex classical computing assistance, and large calculation errors.
[0055] The present invention provides a method for calculating the configuration of protein molecules based on a quantum imaginary time evolution algorithm. Compared with classical calculation methods and other existing similar quantum algorithms, this technical route requires significantly reduced computational complexity, omits classical processing and classical optimization parts, improves accuracy, and reduces the need for auxiliary bits.
[0056] The exemplary embodiments of the present application are described below with reference to the accompanying drawings.
[0057] Figure 1 A flow chart of a method for calculating the configuration of a protein molecule according to an exemplary embodiment of the present application is shown.
[0058] See also Figure 1 In S101, the Pauli operator form of the Hamiltonian of the protein molecular configuration is given, and for each item in the Hamiltonian, a quantum circuit diagram is constructed using a quantum imaginary time evolution algorithm.
[0059] According to some embodiments, given the Pauli operator form of the Hamiltonian describing the protein molecular configuration, the Hartree-Fock state (HF state) of the protein molecular configuration is obtained using a classical algorithm, and the HF state is used as the initial quantum state of the algorithm.
[0060] For each item in the Hamiltonian, an auxiliary bit with an initial quantum state of |0> is introduced, and an executable quantum circuit diagram is generated according to the Pauli operator of this item in the current Hamiltonian. The quantum circuit diagram is represented as a series of basic quantum gate operations, and the quantum evolution process corresponding to the quantum circuit diagram is executed on a quantum computer.
[0061] In S103, the quantum circuit diagram is executed so that the initial quantum state passes through the quantum circuit diagram to obtain a quantum final state.
[0062] According to some embodiments, a quantum state is subjected to a series of quantum gate operations on a quantum computer to obtain a quantum final state.
[0063] In S105, it is determined whether the quantum final state is the desired target state by using the auxiliary bit measurement result to obtain the ground state energy of the protein molecule.
[0064] In S107, the configuration information of the protein molecule is obtained based on the ground state energy of the protein molecule.
[0065] According to some embodiments, the auxiliary bit is measured, and when the auxiliary bit is at |0>, the quantum final state |ψ> after the current term of the Hamiltonian evolves in the imaginary time with a step size of Δt is calculated, which is expressed as |ψ>=A*exp(-c k h k Δt)ψ0>, where A is the normalization coefficient, c k is the coefficient of the kth term of the Hamiltonian, h k is the Pauli matrix of the kth term of the Hamiltonian, Δt is the step size of the imaginary time evolution, and ψ0 is the initial quantum state.
[0066] In the previous step, when all the terms in the Hamiltonian are completed, repeat and measure the average energy of the quantum final state under the Hamiltonian.
[0067] The above two steps are repeated continuously until the difference between the average energy values measured twice in a row is less than the threshold value. At this time, the average energy value measured for the last time is output to obtain the ground state energy of the protein molecule, thus completing the calculation of the protein molecular configuration.
[0068] The technical route of solving the Hamiltonian eigenvalues by using the imaginary-time evolution algorithm based on quantum computers can significantly reduce the computational complexity required by this technical route compared to the computing speed of classical computers. Compared with using other currently feasible quantum algorithms to calculate the Hamiltonian eigenvalues, this algorithm has higher accuracy and consumes less classical and quantum resources. The reason for this advantage is that the principle used by this algorithm is closest to the imaginary-time evolution equation, without making too many approximations, which greatly improves the accuracy; and this algorithm uses full quantum processing during the quantum computer operation stage, does not require classical parameter training, and each layer of the circuit only involves one item of the Hamiltonian, so only one auxiliary bit is required, which greatly saves computing resources.
[0069] Figure 2 A schematic diagram of a method for calculating the configuration of a protein molecule according to an exemplary embodiment of the present application is shown.
[0070] See also Figure 2The classical preprocessor generates and preprocesses the data, and then transmits it to the quantum computer as data input. The quantum computer processes the data through the quantum imaginary time evolution algorithm and then reads and outputs it. The output data is read into the classical computer, and after processing, the information of the folding configuration of the protein molecule can be obtained. The specific steps include the following:
[0071] Step 1: There is a Pauli operator form of the Hamiltonian that describes the protein molecular configuration. Use the classical algorithm to obtain the Hartree-Fock state (HF state) of the protein molecular configuration, and use the HF state as the initial quantum state of this algorithm.
[0072] Step 2: For each item in the Hamiltonian, introduce an auxiliary bit with an initial quantum state of |0>, generate an executable quantum circuit diagram based on the Pauli operator of this item in the current Hamiltonian, represent the quantum circuit diagram as a series of basic quantum gate operations, and execute the quantum evolution process corresponding to the quantum circuit diagram on the quantum computer. That is, the quantum state on the quantum computer undergoes a series of quantum gate operations to obtain the quantum final state.
[0073] Measure the auxiliary bit. When the auxiliary bit is at |0>, calculate the quantum final state |ψ> of the current term of Hamiltonian after the imaginary time evolution with a step length of Δt, expressed as |ψ>=A*exp(-c k h k Δt)|ψ0>, where A is the normalization coefficient, c k is the coefficient of the kth term of the Hamiltonian, h k is the Pauli matrix of the kth term of the Hamiltonian, Δt is the step size of the imaginary time evolution, and ψ0 is the initial quantum state.
[0074] Step 3: When all items in the Hamiltonian are completed in the previous step, repeat and measure the average energy of the quantum final state under the Hamiltonian.
[0075] Step 4: Repeat the above two steps until the difference between the average energy values measured twice in a row is less than the threshold. At this time, the average energy value measured for the last time is output to obtain the ground state energy of the protein molecule, thus completing the calculation of the protein molecular configuration.
[0076] Figure 3 A schematic diagram of a quantum circuit for calculating the configuration of a protein molecule according to an exemplary embodiment of the present application is shown.
[0077] According to some embodiments, using Figure 3 The specific method of calculating the protein molecular configuration through the quantum imaginary time evolution algorithm is as follows:
[0078] First, the Hamiltonian H consists of m Pauli direct product terms: where hk is the Pauli direct product term. The imaginary time evolution operator corresponding to this Hamiltonian is e -βH , using Trotter decomposition formula, it can be written as
[0079]
[0080] Ignoring the error term O9Δτ), we only need to apply the operator to the quantum state in sequence Virtual time evolution can be achieved.
[0081] Implementing Operators The method is mainly divided into the following five steps:
[0082] 1) Apply unitary transformation U to the working bit k , where U k satisfy is a function that only acts on the first k The Pauli matrix σ on bits z ; Mathematically it can be proved that there must be such a U k , in the quantum circuit, U k It can be constructed by Hadamard gates, S gates, and CNOT gates, and the number of gates required is proportional to the number of bits at most; here U k In this case, k can be any natural number from 1 to m, and Figure 3 Only two special cases, k = 1 and k = m, are shown in the figure, and the intermediate cases are omitted with ellipsis. HF represents the Hartley Fock state, which is the initial quantum state in the quantum computer; ψ f represents the final quantum state obtained after the quantum computer operation, which can be approximately considered as ψ f It is the ground state of the protein molecule.
[0083] 2) Introduce an auxiliary bit, initialized to |0>;
[0084] 3) For the first k bits and auxiliary bits act as controlled-Ry operations, where the lth bit k bits are control bits, and the auxiliary bits are target bits. The rotation angle is θ k =arccos[exp(-2|c k |Δτ)];
[0085] 4) Measure the auxiliary bit. If it is 0, continue the operation; if it is 1, start from the beginning;
[0086] 5) If the auxiliary bit is measured to obtain 0, then a unitary operation is performed on the quantum state
[0087] After the above five steps, the operator can be realized All By acting on the initial quantum state in a certain order, the imaginary time evolution operator can be realized.
[0088] Pauli direct product: a matrix obtained by directly producting several Pauli matrices and the identity matrix. There are three Pauli operators, namely The identity matrix is
[0089] Working bit: A quantum bit that carries information about the quantum system and directly participates in the operation. Auxiliary bit: A quantum bit that does not carry information about the quantum system and only plays an auxiliary role.
[0090] Hadamard gate, S gate and CNOT gate: Several quantum gates commonly used in quantum circuits. Hadamard gate and S gate are both single-bit gates, and the corresponding matrix forms are The CNOT gate is a two-bit gate. The two bits it contains are called the control bit and the target bit. The effect of the CNOT gate is: when the control bit is 0, the target bit remains unchanged, and when the control bit is 1, the target bit flips.
[0091] controlled-Ry: Similar to the CNOT gate, when the control bit is 0, the target bit remains unchanged. When the control bit is 1, the target bit is affected by an Ry gate.
[0092] The above technical solution for solving the Hamiltonian eigenvalues based on the imaginary time evolution algorithm of quantum computers can significantly reduce the computational complexity required by the technical solution compared to the computing speed of classical computers. Compared with using other currently feasible quantum algorithms to calculate the eigenvalues of the Hamiltonian, this algorithm has higher accuracy and consumes less classical and quantum resources. The reason for this advantage is that the principle used by this algorithm is closest to the imaginary time evolution equation, without making too many approximations, which greatly improves the accuracy; and this algorithm uses full quantum processing during the quantum computer operation stage, does not require classical parameter training, and each layer of the circuit only involves one item of the Hamiltonian, so only one auxiliary bit is required, which greatly saves computing resources.
[0093] Figure 4 A block diagram showing an apparatus for calculating the configuration of a protein molecule according to an exemplary embodiment of the present application.
[0094] A device for calculating the folding configuration of a protein molecule comprises at least one quantum processor and at least one classical processor, a quantum register communicatively connected to the at least one quantum processor, and a memory and a classical register communicatively connected to the at least one quantum processor and the at least one classical processor; wherein the memory is used to store execution instructions, the at least one quantum processor and the at least one classical processor are used to execute any of the aforementioned methods according to the execution instructions to obtain a result of calculating the folding configuration of a protein molecule, and the classical register is used to store the measurement results and parameter data of the quantum register.
[0095] According to some embodiments, a device for calculating protein molecular configuration using a quantum computer includes at least a memory for executing quantum circuit instructions and a quantum processor for executing quantum circuit programs.
[0096] By using a quantum computer to calculate the folding configuration of protein molecules, the Pauli operator form of the Hamiltonian that describes the configuration of protein molecules is given; for each item in the Hamiltonian, a quantum circuit is constructed using a quantum imaginary-time evolution algorithm, and the quantum circuit diagram is executed on a quantum computer. The initial quantum state will obtain a quantum final state after passing through the quantum circuit; by determining whether the quantum final state is the required target state through the measurement results of the auxiliary system, the average energy of the quantum state under the Hamiltonian is repeatedly measured until the change in the average value is less than a certain threshold, and the ground state energy of the protein molecule is obtained, thereby obtaining information about the configuration of the protein molecule.
[0097] The above technical solution for solving the Hamiltonian eigenvalues based on the imaginary time evolution algorithm of quantum computers can significantly reduce the computational complexity required by the technical solution compared to the computing speed of classical computers. Compared with using other currently feasible quantum algorithms to calculate the eigenvalues of the Hamiltonian, this algorithm has higher accuracy and consumes less classical and quantum resources. The reason for this advantage is that the principle used by this algorithm is closest to the imaginary time evolution equation, without making too many approximations, which greatly improves the accuracy; and this algorithm uses full quantum processing during the quantum computer operation stage, does not require classical parameter training, and each layer of the circuit only involves one item of the Hamiltonian, so only one auxiliary bit is required, which greatly saves computing resources.
[0098] It should be clearly understood that the present application describes how to form and use specific examples, but the present application is not limited to any details of these examples. On the contrary, based on the teaching of the content disclosed in the present application, these principles can be applied to many other embodiments.
[0099] Those skilled in the art will appreciate that all or part of the steps to implement the above embodiments are implemented as a computer program executed by a CPU. When the computer program is executed by the CPU, the program for executing the above functions defined by the above method provided in the present application may be stored in a computer-readable storage medium, which may be a read-only memory, a disk or an optical disk, etc.
[0100] In addition, it should be noted that the above figures are only schematic illustrations of the processes included in the method according to the exemplary embodiments of the present application, and are not intended to be limiting. It is easy to understand that the processes shown in the above figures do not indicate or limit the time sequence of these processes. In addition, it is also easy to understand that these processes can be performed synchronously or asynchronously, for example, in multiple modules.
[0101] Through the description of the example embodiments, it is easy for those skilled in the art to understand that the method for processing graph network data through a quantum node embedding algorithm according to an embodiment of the present application has at least one or more of the following advantages.
[0102] According to the exemplary embodiments, the use of quantum algorithms can utilize fewer physical resources and be more efficient, the scheme is simple, and the selected parameter-containing quantum gates are also easy to implement on recent noisy medium-sized quantum computers.
[0103] Those skilled in the art will appreciate that the above modules can be distributed in the device according to the description of the embodiment, or can be changed accordingly and only used in one or more devices different from the embodiment. The modules of the above embodiments can be combined into one module, or further divided into multiple sub-modules.
[0104] The exemplary embodiments of the present application are specifically shown and described above. It should be understood that the present application is not limited to the detailed structures, configurations or implementations described herein; on the contrary, the present application is intended to cover various modifications and equivalent configurations included in the spirit and scope of the appended claims.
Claims
1. A method for calculating the molecular configuration of a protein, characterized in that: include: Given the Pauli operator form of the Hamiltonian of the protein molecular configuration, for each item in the Hamiltonian, a quantum circuit diagram is constructed using a quantum imaginary time evolution algorithm; Executing the quantum circuit diagram so that the initial quantum state obtains the quantum final state through the quantum circuit diagram; Determining whether the quantum final state is the desired target state through the auxiliary bit measurement result, so as to obtain the ground state energy of the protein molecule; Based on the ground state energy of the protein molecule, obtaining configuration information of the protein molecule; The step of determining whether the quantum final state is the desired target state by using the auxiliary bit measurement result to obtain the ground state energy of the protein molecule includes: Repeatedly measuring the energy average of the quantum state under the Hamiltonian, and determining if the change amplitude of the energy average is less than a threshold, then obtaining the ground state energy of the protein molecule, including: When all items in the Hamiltonian are calculated, the energy average value of the quantum final state under the Hamiltonian is repeatedly measured until the difference between the energy average values measured twice in succession is less than a threshold value, and the energy average value obtained by the last measurement is output.
2. The method according to claim 1, characterized in that Also includes: According to the Pauli operator form of the Hamiltonian of the protein molecular configuration, the Hartley Fock state of the protein molecular configuration is calculated using a classical algorithm, and the Hartley Fock state is used as the initial quantum state.
3. The method according to claim 2, characterized in that The executing the quantum circuit diagram so that the initial quantum state obtains a quantum final state through the quantum circuit diagram includes: For each item in the Hamiltonian, an auxiliary bit with an initial quantum state of |0> is introduced, and an executable quantum circuit diagram is generated according to the Pauli operator of the current item in the Hamiltonian.
4. The method according to claim 3, characterized in that The generating an executable quantum circuit diagram according to the Pauli operator of the current term of the Hamiltonian also includes: The quantum circuit diagram is represented as a series of basic quantum gate operations, and the quantum evolution process corresponding to the quantum circuit diagram is executed by a quantum computer to obtain a quantum final state.
5. The method according to claim 4, characterized in that The method of judging whether the quantum final state is the desired target state by the auxiliary bit measurement result to obtain the ground state energy of the protein molecule also includes: Measure the auxiliary bit. When the auxiliary bit is at |0>, calculate the quantum final state |ψ> of the current term of Hamiltonian after the imaginary time evolution with a step length of Δt, expressed as |ψ>=A*exp(-c k h k Δt)|ψ0>, Among them, A is the normalization coefficient, c k is the coefficient of the kth term of the Hamiltonian, h k is the Pauli matrix of the kth term of the Hamiltonian, Δt is the step size of the imaginary time evolution, and ψ0 is the initial quantum state.
6. A device for calculating the folding configuration of protein molecules, characterized in that: The invention comprises at least one quantum processor and at least one classical processor, a quantum register communicatively connected to the at least one quantum processor, and a memory and a classical register communicatively connected to the at least one quantum processor and the at least one classical processor; wherein the memory is used to store execution instructions, and the at least one quantum processor and the at least one classical processor are used to execute according to the execution instructions. The quantum processor is configured as follows: A Pauli operator form of a Hamiltonian of a given protein molecule configuration is used, and for each item in the Hamiltonian, a quantum circuit diagram is constructed using a quantum imaginary time evolution algorithm; the quantum circuit diagram is executed so that an initial quantum state passes through the quantum circuit diagram to obtain a quantum final state; whether the quantum final state is a desired target state is determined by an auxiliary bit measurement result to obtain the ground state energy of the protein molecule; based on the ground state energy of the protein molecule, configuration information of the protein molecule is obtained; the energy average value of the quantum state under the Hamiltonian is repeatedly measured, and if the variation amplitude of the energy average value is less than a threshold value, the ground state energy of the protein molecule is obtained, including: after all items in the Hamiltonian are calculated, the energy average value of the quantum final state under the Hamiltonian is repeatedly measured until the difference between the energy average values measured twice in succession is less than a threshold value, and the energy average value obtained by the last measurement is output; The classical register is configured to store measurement results and parameter data of the quantum register.