Quantum simulation method and device

Abstract

This application discloses a quantum simulation method and apparatus, comprising: using first parameters and a pseudo-method to prepare a first quantum state corresponding to the evolution of a target time slice; within the target time slice, using a target Hamiltonian to perform an evolution operation on the first quantum state to generate a second quantum state; using second parameters and the pseudo-method to prepare a third quantum state; in response to the similarity between the second quantum state and the current third quantum state meeting a specified condition, using the current second parameter as the first parameter required for the simulation of the next target time slice, and returning to the step of preparing the first quantum state corresponding to the evolution of the target time slice using the first parameter and the pseudo-method, until all time slices are simulated. Using embodiments of this application, the fidelity of quantum simulation results is improved.

Description

Technical Field

[0001] The present application relates to the field of quantum computing technology, and in particular to a quantum simulation method and device. Background Art

[0002] Quantum simulation (also known as Hamiltonian simulation) is a problem in quantum information science. Specifically, it involves simulating the time evolution of a system's state given its Hamiltonian. Quantum simulation has a wide range of applications in quantum chemistry, biopharmaceuticals, and materials synthesis. It can also be used to design related quantum algorithms, such as the HHL algorithm, continuous-time quantum walk algorithm, and adiabatic quantum algorithm.

[0003] The current approach to quantum simulation involves decomposing the unitary matrix corresponding to the Hamiltonian into a series of unitary operations supported by quantum devices. This series of unitary operations is then constructed into a quantum circuit consisting of quantum logic gates for simulation. However, this simulation approach increases the depth of the quantum circuit as the number of qubits increases, making the simulation time-consuming and resulting in low fidelity of the quantum simulation results. Summary of the Invention

[0004] The purpose of this application is to provide a quantum simulation method and device, aiming to improve the fidelity of quantum simulation results.

[0005] An embodiment of the present application provides a quantum simulation method, the method comprising:

[0006] Using the first parameter and the hypothetical method, a first quantum state corresponding to the evolution of the target time slice is prepared;

[0007] performing an evolution operation on the first quantum state using a target Hamiltonian within the target time slice to generate a second quantum state;

[0008] Using the second parameter and the proposed method, a third quantum state is prepared;

[0009] In response to the similarity between the second quantum state and the current third quantum state meeting the specified conditions, the current second parameter is used as the first parameter required for the next target time slice simulation, and the step of preparing the first quantum state corresponding to the evolution of the target time slice using the first parameter and the assumed method is returned to be executed until all time slice simulations are completed.

[0010] Optionally, the target time slice is a current time slice to be evolved obtained by splitting a preset evolution time; and the target Hamiltonian is the Hamiltonian of a quantum system to be simulated.

[0011] Optionally, the length of each split time slice is no longer than the quantum bit coherence time of the target quantum computer.

[0012] Optionally, the method further includes:

[0013] In response to the similarity between the second quantum state and the current third quantum state not satisfying a specified condition, the second parameter is updated, and the step of preparing the third quantum state by using the second parameter and the hypothetical method is returned to.

[0014] Optionally, the second parameter is updated using a quantum gradient algorithm.

[0015] Optionally, the method further includes:

[0016] Obtaining a quantum circuit for measuring the similarity between the first quantum state and the current third quantum state;

[0017] The first quantum state and the current third quantum state are applied to the quantum circuit to obtain the similarity.

[0018] Another embodiment of the present application provides a quantum simulation device, comprising:

[0019] A first preparation module is used to prepare a first quantum state corresponding to the evolution of a target time slice using a first parameter and a simulated method;

[0020] a generation module, configured to perform an evolution operation on the first quantum state using a target Hamiltonian within the target time slice to generate a second quantum state;

[0021] A second preparation module is used to prepare a third quantum state using the second parameter and the simulated method;

[0022] An updating module is used to respond to the similarity between the second quantum state and the current third quantum state meeting a specified condition, use the current second parameter as the first parameter required for the next target time slice simulation, and return to execute the first preparation module until all time slice simulations are completed.

[0023] Another embodiment of the present application provides a quantum super-cooperative operating system, which implements quantum simulation according to any of the methods described above.

[0024] An embodiment of the present application provides a storage medium, wherein the storage medium stores a computer program, wherein the computer program is configured to implement any of the above methods when running.

[0025] An embodiment of the present application provides an electronic device, including a memory and a processor, wherein the memory stores a computer program, and the processor is configured to run the computer program to implement any of the above methods.

[0026] Compared with the prior art, the present application first uses a first parameter and a pseudo-method to prepare the first quantum state corresponding to the evolution of the target time slice; then, within the target time slice, the target Hamiltonian is used to perform an evolution operation on the first quantum state to generate a second quantum state; then, a second parameter and the pseudo-method are used to prepare a third quantum state; finally, in response to the similarity between the second quantum state and the current third quantum state meeting a specified condition, the current second parameter is used as the first parameter required for the simulation of the next target time slice, and the process returns to executing the step of preparing the first quantum state corresponding to the evolution of the target time slice using the first parameter and the pseudo-method until all time slice simulations are completed. The first parameter for preparing the first quantum state is determined by the similarity between the second quantum state and the third quantum state, ensuring the similarity between the first quantum state of the next target time slice and the second quantum state obtained in the current target time slice, which can greatly reduce the interference of noise and thus improve the fidelity of the quantum simulation results. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] Figure 1 This is a network block diagram of a quantum simulation system provided by an embodiment of the present application;

[0028] Figure 2 A schematic diagram of a quantum simulation method according to an embodiment of the present application;

[0029] Figure 3 A schematic diagram of the structure of a quantum simulation device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0030] The embodiments described below with reference to the accompanying drawings are exemplary and are only used to explain the present application, and should not be construed as limiting the present application.

[0031] Figure 1 This is a network block diagram of a quantum simulation system provided by an embodiment of the present application. The quantum simulation system may include a network 110, a server 120, a wireless device 130, a client 140, a storage unit 150, a classical processing system 160, a quantum processing system 170, and may also include additional memory, classical processors, quantum processors, and other devices (not shown).

[0032] The network 110 is a medium for providing communication links between various devices and computers connected together in the quantum simulation system, including but not limited to the Internet, corporate intranet, local area network, mobile communication network and their combinations. The connection method can be wired, wireless communication links or optical fiber cables.

[0033] Server 120 and client 140 are conventional data processing systems that may contain data and applications or software tools that perform conventional computing processes. Client 140 may be a personal computer or a network computer, so the data may also be provided by server 120. Wireless device 130 may be a smartphone, tablet, laptop, smart wearable device, etc. Storage unit 150 may include database 151, which may be configured to store data such as qubit parameters, quantum logic gate parameters, quantum circuits, and quantum programs.

[0034] The classical processing system 160 (quantum processing system 170) may include a classical processor 161 (quantum processor 171) for processing classical data (quantum data) and a memory 163 (memory 172) for storing classical data (quantum data). The classical data (quantum data) may be a boot file, an operating system image, and an application 162 (application 173). The application 162 (application 173) may be used to implement a quantum algorithm compiled according to the quantum simulation method provided in an embodiment of the present application.

[0035] Any data or information stored or generated in classical processing system 160 (quantum processing system 170) can also be configured to be stored or generated in another classical (quantum) processing system in a similar manner, and similarly, any application program executed therein can also be configured to be executed in another classical (quantum) processing system in a similar manner.

[0036] It should be noted that a true quantum computer is a hybrid structure, which includes at least Figure 1 The system consists of two parts: the classical processing system 160, which is responsible for performing classical calculations and control; and the quantum processing system 170, which is responsible for running quantum programs and thus realizing quantum computing.

[0037] The classical processing system 160 and quantum processing system 170 can be integrated into a single device or distributed across two different devices. For example, a first device including the classical processing system 160 runs a classical computer operating system, provides quantum application development tools and services, and also provides the storage and network services required by quantum applications. Users develop quantum applications using the quantum application development tools and services on the device, and send quantum programs to a second device including the quantum processing system 170 via the network services on the device. The second device runs a quantum computer operating system, which parses the code of the quantum program and compiles it into instructions that can be recognized and executed by the quantum computer measurement and control system. The quantum processor 170 then implements the quantum algorithm corresponding to the quantum program based on these instructions.

[0038] In a classic silicon chip-based processing system 160, the units of the classic processor 161 are CMOS transistors. These computing units are not constrained by time or coherence, meaning they are available at all times. Furthermore, the number of these computing units is plentiful within a silicon chip, with a typical classic processor currently containing tens of thousands of them. This abundance of computing units and the fixed selectable computational logic of CMOS transistors, such as AND logic, allow computational efficiency to be achieved through the combination of a large number of CMOS transistors with limited logical functions.

[0039] Unlike the logic unit in the classical processing system 160, the basic computing unit of the quantum processor 171 in the quantum processing system 170 is the qubit. The input of the qubit is limited by coherence and coherence time, that is, the qubit is limited by the length of use and is not available at any time. Making full use of the qubit within the available use time of the qubit is a key problem in quantum computing. In addition, the number of qubits in a quantum computer is one of the representative indicators of the performance of the quantum computer. Each qubit realizes the computing function through the logic function configured on demand. Given the limited number of qubits, the logical functions in the field of quantum computing are diverse, such as: Hadamard gate (H gate), Pauli-X gate (X gate), Pauli-Y gate (Y gate), Pauli-Z gate (Z gate), X gate, RY gate, RZ gate, CNOT gate, CR gate, iSWAP gate, Toffoli gate, etc. During quantum computing, it is necessary to use limited qubits in combination with a variety of logic functions to achieve the computing effect.

[0040] Based on these differences, the design of the logical functions acting on quantum bits (including the design of whether the quantum bits are used and the design of the efficiency of the use of each quantum bit) is the key to improving the computing performance of quantum computers and requires special design. However, the above-mentioned design for quantum bits is a technical issue that ordinary computing devices do not need to consider or face. Based on this, in order to improve the fidelity of simulation results in quantum computing, this application proposes a quantum simulation method and related devices to improve the fidelity of simulation results.

[0041] See also Figure 2 , Figure 2 A schematic flow chart of a quantum simulation method provided in an embodiment of the present application may include the following steps:

[0042] S201: Using the first parameter and the assumption method, prepare the first quantum state corresponding to the evolution of the target time slice.

[0043] The purpose of the simulation is to prepare the test state. The first quantum state is the test state. The simulation method can be UCC (Unitary Couple Cluster) simulation, HEA (Hardware Efficient Ansatz) or ADAPT (Adaptive Derivative-assembled Pseudo-Trotter) simulation. ADAPT simulation can be regarded as an improvement of UCC simulation. UCC simulation includes UCCS (Unitary Coupled Cluster of Single excitations) and UCCSD (Unitary Coupled Cluster of Single and Double excitations). Different simulation methods have different quantum circuits. The first parameter is the parameter required to prepare the test state by the simulation method. It can be the circuit parameter corresponding to the simulation method. Specifically, the rotation angle of the quantum rotary gate in the quantum circuit is determined by the first parameter. The rotation angle of the quantum rotary gate can be the first parameter or 2π*first parameter. For different first parameters, the first quantum states prepared using the same simulated method may be different. In this application, as long as the simulated method contains parameters and can prepare the experimental state, the specific simulated method is not limited here.

[0044] The target time slice is the current time slice to be evolved, obtained by splitting the preset evolution time. For example, if the evolution time is 10 seconds and the preset time interval is 1 second, the evolution time is split into time slices 1 through 10, each 1 second long. If time slices 1 through 6 have already been simulated, then time slice 7 is the target time slice. It should be noted that time slices can be split using the same or different time intervals.

[0045] In order to improve the fidelity of the simulation results of each time slice, the length of each split time slice is no longer than the coherence time of the qubit of the target quantum computer. This ensures that the simulation of the Hamiltonian is completed during quantum decoherence, making the simulation results closer to the actual results of running on the target quantum computer. When dividing the evolution time, it is necessary to set the time interval according to the coherence time of the qubit of the target quantum computer, and then obtain all the time slices. The target quantum computer is a real quantum computer, and the coherence time of the qubit is a performance parameter of the target quantum computer. Different target quantum computers may have different coherence times of qubits due to the different physical systems used in their construction (photons, superconductors, ion traps, etc.).

[0046] S202: Within the target time slice, using a target Hamiltonian, perform an evolution operation on the first quantum state to generate a second quantum state.

[0047] The target Hamiltonian is the Hamiltonian of the quantum system to be simulated. The quantum system can be a physical system or a chemical system. Quantum simulation can simulate the dynamic evolution of quantum systems such as chemical molecules in the microscopic world. It has important applications in quantum chemistry, materials science and other fields. Quantum simulation is also a key step in quantum principal component analysis and quantum linear system solving technology.

[0048] The evolution of the quantum system to be simulated over time is determined by the Hamiltonian of the quantum system. The evolution of the quantum state can be expressed as: |ψ(t)>=e -iHt |ψ(θ0)>, where |ψ(θ0)> is the first quantum state, |ψ(t)> is the second quantum state, i is an imaginary number, and U=e -iHt is a unitary matrix. Decomposing the unitary matrix yields a quantum circuit that simulates the evolution of the target Hamiltonian. Specifically, this can be done using Totter decomposition or LCU (Linear Combination of Unitaries). Based on the decomposition results, the quantum logic gates and the interactions between them and the qubits are determined, and quantum circuits are constructed based on this. Of course, other construction methods exist, which are not listed here. As long as they can simulate the evolution of the target Hamiltonian, they are sufficient.

[0049] Once the qubit is in the first quantum state, an excitation is applied to the qubit in the first quantum state. The duration of the excitation is the target time slice. The excitation is an evolution operation of the target Hamiltonian. That is, the target Hamiltonian is processed to determine how to apply the excitation so that the first quantum state evolves into the second quantum state. Specifically, the qubit in the first quantum state is evolved over time using a quantum circuit that simulates the evolution of the target Hamiltonian. When the time reaches the target time slice, the evolution stops, and the qubit is now in the second quantum state.

[0050] S203: Prepare a third quantum state using the second parameter and the simulated method.

[0051] The preparation of the third quantum state is the same as that of the first quantum state, except that the parameters used in the preparation are different. The first parameter and the second parameter can be selected within the same value range, which can be [0, 2π].

[0052] S204: In response to the similarity between the second quantum state and the current third quantum state meeting a specified condition, the current second parameter is used as the first parameter required for the next target time slice simulation, and the process returns to S201 until all time slice simulations are completed.

[0053] The specified condition is a measurement condition set for whether the similarity between the second quantum state and the current third quantum state meets the expectation. The specified condition can be that the similarity is within a preset range, or the loss function value calculated based on the similarity is within a specified range, or the difference between the current and previous loss functions is within a preset accuracy range, etc. The loss function can be expressed as (1-|<ψ(t+Δt)|ψ(θ n )>| 2 ) 2 , where |ψ(t+Δt)> is the second quantum state, |ψ(θ n )> is the current third quantum state, θ n is the second parameter, Δt is the length of the target time slice, and t is the sum of all previously simulated target time slices except the currently simulated target time slice. For example, if the currently simulated target time slice is time slice 3, then Δt is time slice 3, and t is the sum of time slices 1 and 2.

[0054] When the similarity meets the specified conditions, for the next target time slice, the fidelity between the first quantum state prepared using the current second parameter and the simulated method and the second quantum state generated in the previous target time slice can be optimized. The fidelity of the simulation results for each time slice is optimized so that the input quantum state (first quantum state) of each time slice can resist the interference of noise. This allows the state evolution of the quantum system to be simulated over a longer period of time, and the deviation between the simulation results and the actual results is controlled so that the simulation results can effectively reflect the actual results, thereby promoting technical research in related fields.

[0055] In this application, in order to obtain results with higher fidelity, the time is sliced and the simulation is completed within each time slice, minimizing the depth of the quantum circuit and thus achieving the fidelity requirement. At the same time, the same assumption is used to construct the input quantum state of the next time slice. This method of reconstructing the quantum state in each time slice has stronger noise resistance due to the use of the symmetry information of the Hamiltonian, further improving the fidelity of the simulation results.

[0056] In some possible implementations of the present application, the method may further include:

[0057] In response to the similarity between the second quantum state and the current third quantum state not satisfying a specified condition, the second parameter is updated, and the step of preparing the third quantum state by using the second parameter and the hypothetical method is returned to.

[0058] The second parameter can be updated by using a classical optimizer to obtain a gradient, calculating a new second parameter based on the gradient, and using the original second parameter as the new parameter. Alternatively, the second parameter can be updated using a quantum gradient algorithm, which may include a quantum gradient descent algorithm.

[0059] In some possible implementations of the present application, the method may further include:

[0060] Obtaining a quantum circuit for measuring the similarity between the first quantum state and the current third quantum state;

[0061] The first quantum state and the current third quantum state are applied to the quantum circuit to obtain the similarity.

[0062] The quantum circuit used to measure similarity, along with the number of qubits and the first and third quantum states, can be a quantum circuit with a SWAP-test function. This quantum circuit can include SWAP gates and H gates, and of course, other quantum logic gates. The first quantum state and the currently prepared third quantum state are applied to the quantum circuit. The first and third quantum states are altered by the quantum logic gates within the quantum circuit. The final state of the quantum circuit is measured, yielding a measurement result that reflects the similarity. For example, the probability corresponding to a specific eigenstate in the measurement result can be used as the similarity, or the probability corresponding to a specific eigenstate of a specific qubit can be measured. Similarly, multiple measurements can be performed, and the desired results obtained from these multiple measurements can be averaged or median-ed to obtain the similarity. Once the similarity is obtained, it can be determined whether it meets specified conditions.

[0063] It can be seen that the present application first uses the first parameter and the pseudo-method to prepare the first quantum state corresponding to the evolution of the target time slice; then, within the target time slice, the target Hamiltonian is used to perform an evolution operation on the first quantum state to generate a second quantum state; then, the second parameter and the pseudo-method are used to prepare the third quantum state; finally, in response to the similarity between the second quantum state and the current third quantum state meeting the specified conditions, the current second parameter is used as the first parameter required for the next target time slice simulation, and the step of using the first parameter and the pseudo-method to prepare the first quantum state corresponding to the evolution of the target time slice is returned to execute until all time slice simulations are completed. The first parameter for preparing the first quantum state is determined by the similarity between the second quantum state and the third quantum state, which ensures the similarity between the first quantum state of the next target time slice and the second quantum state obtained in the current target time slice, which can greatly reduce the interference of noise, thereby improving the fidelity of the quantum simulation results.

[0064] See also Figure 3 , Figure 3A schematic diagram of the structure of a quantum simulation device provided in an embodiment of the present application, Figure 2 Corresponding to the process shown, the device includes:

[0065] A first preparation module 301 is used to prepare a first quantum state corresponding to the evolution of a target time slice using a first parameter and a simulated method;

[0066] A generating module 302 is configured to perform an evolution operation on the first quantum state using a target Hamiltonian within the target time slice to generate a second quantum state;

[0067] A second preparation module 303 is used to prepare a third quantum state using the second parameter and the proposed method;

[0068] The updating module 304 is configured to, in response to the similarity between the second quantum state and the current third quantum state satisfying a specified condition, use the current second parameter as the first parameter required for simulating the next target time slice, and return to execute the first preparation module 301 .

[0069] In some possible implementations of the present application, the target time slice is the current time slice to be evolved obtained by splitting the preset evolution time; and the target Hamiltonian is the Hamiltonian of the quantum system to be simulated.

[0070] In some possible implementations of the present application, the length of each split time slice is no longer than the quantum bit coherence time of the target quantum computer.

[0071] In some possible implementations of the present application, the update module 304 may also be used to:

[0072] In response to the similarity between the second quantum state and the current third quantum state not satisfying a specified condition, the second parameter is updated, and the process returns to execute the second preparation module 303 .

[0073] In some possible implementations of the present application, the second parameter may be updated using a quantum gradient algorithm.

[0074] In some possible implementations of the present application, the device further includes:

[0075] A first obtaining module, configured to obtain a quantum circuit for measuring the similarity between the first quantum state and the current third quantum state;

[0076] The second obtaining module is configured to apply the first quantum state and the current third quantum state to the quantum circuit to obtain the similarity.

[0077] It can be seen that the present application first uses the first parameter and the pseudo-method to prepare the first quantum state corresponding to the evolution of the target time slice; then, within the target time slice, the target Hamiltonian is used to perform an evolution operation on the first quantum state to generate a second quantum state; then, the second parameter and the pseudo-method are used to prepare the third quantum state; finally, in response to the similarity between the second quantum state and the current third quantum state meeting the specified conditions, the current second parameter is used as the first parameter required for the next target time slice simulation, and the step of using the first parameter and the pseudo-method to prepare the first quantum state corresponding to the evolution of the target time slice is returned to execute until all time slice simulations are completed. The first parameter for preparing the first quantum state is determined by the similarity between the second quantum state and the third quantum state, which ensures the similarity between the first quantum state of the next target time slice and the second quantum state obtained in the current target time slice, which can greatly reduce the interference of noise, thereby improving the fidelity of the quantum simulation results.

[0078] An embodiment of the present application also provides a quantum super-cooperative operating system, which runs on a quantum computer including a quantum processor and / or a supercomputer including a classical processor, and is used to implement quantum simulation according to the method described in the embodiment of the method side of the present application.

[0079] An embodiment of the present application further provides a storage medium, wherein the storage medium stores a computer program, wherein the computer program is configured to implement the steps of any of the above method embodiments when run.

[0080] Specifically, in this embodiment, the above-mentioned storage medium may be configured to store a computer program for implementing the following steps:

[0081] S201: using the first parameter and the assumption method, preparing the first quantum state corresponding to the evolution of the target time slice;

[0082] S202: performing an evolution operation on the first quantum state using a target Hamiltonian within the target time slice to generate a second quantum state;

[0083] S203: preparing a third quantum state using the second parameter and the simulated method;

[0084] S204: In response to the similarity between the second quantum state and the current third quantum state meeting a specified condition, the current second parameter is used as the first parameter required for the next target time slice simulation, and the process returns to S201 until all time slice simulations are completed.

[0085] An embodiment of the present application further provides an electronic device, including a memory and a processor, wherein the memory stores a computer program, and the processor is configured to run the computer program to implement the steps in any of the above method embodiments.

[0086] Specifically, the electronic device may further include a transmission device and an input / output device, wherein the transmission device is connected to the processor, and the input / output device is connected to the processor.

[0087] Specifically, in this embodiment, the processor may be configured to implement the following steps through a computer program:

[0088] S201: using the first parameter and the assumption method, preparing the first quantum state corresponding to the evolution of the target time slice;

[0089] S202: performing an evolution operation on the first quantum state using a target Hamiltonian within the target time slice to generate a second quantum state;

[0090] S203: preparing a third quantum state using the second parameter and the simulated method;

[0091] S204: In response to the similarity between the second quantum state and the current third quantum state meeting a specified condition, the current second parameter is used as the first parameter required for the next target time slice simulation, and the process returns to S201 until all time slice simulations are completed.

[0092] The present application also provides a computer program product comprising instructions, which, when executed by a computer, enables the computer to perform the quantum simulation in any of the above embodiments.

[0093] It can be understood that in the various implementations of this specification, the size of the serial number of each process does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the implementation methods of this specification.

[0094] It can be understood that the various embodiments described in this specification can be implemented individually or in combination, and the embodiments in this specification are not limited to this.

[0095] Unless otherwise indicated, all technical and scientific terms used in the embodiments of this specification have the same meaning as those commonly understood by those skilled in the art in the technical field of this specification. The terms used in this specification are only for the purpose of describing specific embodiments and are not intended to limit the scope of this specification. The term "and / or" used in this specification includes any and all combinations of one or more related listed items. The singular forms "a", "above", and "the" used in the embodiments of this specification and the appended claims are also intended to include plural forms unless the context clearly indicates otherwise.

[0096] It is understood that the processor in the embodiments of this specification can be an integrated circuit chip with signal processing capabilities. During implementation, each step of the above method embodiment can be completed by hardware integrated logic circuits in the processor or software instructions. The above processor can be a general-purpose processor, a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field programmable gate array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components. The various methods, steps, and logic block diagrams disclosed in the embodiments of this specification can be implemented or executed. The general-purpose processor can be a microprocessor or any conventional processor. The steps of the method disclosed in the embodiments of this specification can be directly implemented as being executed by a hardware decoding processor, or by a combination of hardware and software modules in the decoding processor. The software module can be located in a storage medium mature in the art, such as random access memory, flash memory, read-only memory, programmable read-only memory, electrically erasable programmable memory, registers, etc. The storage medium is located in the memory, and the processor reads the information in the memory and completes the steps of the above method in combination with its hardware.

[0097] It will be understood that the memory in the embodiments of this specification may be a volatile memory or a non-volatile memory, or may include both volatile and non-volatile memories. Among them, the non-volatile memory may be a read-only memory (ROM), a programmable read-only memory (PROM), an erasable programmable read-only memory (EPROM), an electrically erasable programmable read-only memory (EEPROM), or a flash memory. The volatile memory may be a random access memory (RAM). It should be noted that the memory of the systems and methods described herein is intended to include, but is not limited to, these and any other suitable types of memory.

[0098] Those skilled in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professionals and technicians can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this specification.

[0099] Those skilled in the art will clearly understand that, for the convenience and brevity of description, the specific working processes of the above-described systems, devices and units can refer to the corresponding processes in the aforementioned method implementation methods and will not be repeated here.

[0100] In the several embodiments provided in this specification, it should be understood that the disclosed systems, devices, and methods can be implemented in other ways. For example, the device embodiments described above are merely illustrative. For example, the division of the units is merely a logical function division. In actual implementation, there may be other division methods, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0101] The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed across multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of this embodiment.

[0102] In addition, each functional unit in each embodiment of this specification may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.

[0103] If the functions are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this specification, or the part that contributes to the prior art, or the part of the technical solution can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes several instructions for enabling a computer device (which can be a personal computer, server, or network device, etc.) to execute all or part of the steps of the method described in each embodiment of this specification. The aforementioned storage medium includes various media that can store program codes, such as a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disk.

[0104] The above description is merely a specific embodiment of this specification, but the scope of protection of this application is not limited thereto. Any changes or substitutions that can be easily conceived by a person skilled in the art within the technical scope disclosed in this specification should be included within the scope of protection of this specification. Therefore, the scope of protection of this application should be based on the scope of protection of the claims.

Claims

1. A quantum simulation method, characterized in that: The method comprises: Using the first parameter and the hypothetical method, a first quantum state corresponding to the evolution of the target time slice is prepared; performing an evolution operation on the first quantum state using a target Hamiltonian within the target time slice to generate a second quantum state; Using the second parameter and the proposed method, a third quantum state is prepared; In response to the similarity between the second quantum state and the current third quantum state meeting the specified conditions, the current second parameter is used as the first parameter required for the next target time slice simulation, and the step of preparing the first quantum state corresponding to the evolution of the target time slice using the first parameter and the assumed method is returned to be executed until all time slice simulations are completed.

2. The method according to claim 1, characterized in that The target time slice is the current time slice to be evolved obtained by splitting the preset evolution time; the target Hamiltonian is the Hamiltonian of the quantum system to be simulated.

3. The method according to claim 2, characterized in that The length of each split time slice is no longer than the quantum bit coherence time of the target quantum computer.

4. The method according to any one of claims 1 to 3, characterized in that The method further comprises: In response to the similarity between the second quantum state and the current third quantum state not satisfying a specified condition, the second parameter is updated, and the step of preparing the third quantum state by using the second parameter and the hypothetical method is returned to.

5. The method according to claim 4, characterized in that The second parameter is updated using a quantum gradient algorithm.

6. The method according to claim 1, characterized in that The method further comprises: Obtaining a quantum circuit for measuring the similarity between the first quantum state and the current third quantum state; The first quantum state and the current third quantum state are applied to the quantum circuit to obtain the similarity.

7. A quantum simulation device, characterized in that The device comprises: A first preparation module is used to prepare a first quantum state corresponding to the evolution of a target time slice using a first parameter and a simulated method; a generation module, configured to perform an evolution operation on the first quantum state using a target Hamiltonian within the target time slice to generate a second quantum state; A second preparation module is used to prepare a third quantum state using the second parameter and the simulated method; An updating module is used to respond to the similarity between the second quantum state and the current third quantum state meeting a specified condition, use the current second parameter as the first parameter required for the next target time slice simulation, and return to execute the first preparation module until all time slice simulations are completed.

8. A quantitative super-cooperative operating system, characterized in that: The quantum super cooperative operating system implements quantum simulation according to the method described in any one of claims 1 to 6.

9. A storage medium, characterized in that: The storage medium stores a computer program, wherein the computer program is configured to implement the method according to any one of claims 1 to 6 when executed.

10. An electronic device comprising a memory and a processor, characterized in that: A computer program is stored in the memory, and the processor is configured to execute the computer program to implement the method according to any one of claims 1 to 6.

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