Information processing program, information processing method, and information processing device

Abstract

To improve the accuracy of calculating molecular energy using molecular restructuring techniques. [Solution] For each fragment 111, the information processing device 100 acquires a plurality of candidate values ​​that can be solutions for each parameter 121 of the first variational quantum circuit 120. The plurality of candidate values ​​are calculated by VQE via a quantum computer. For each fragment 111, the information processing device 100 calculates the energy of the fragment 111 based on a noise-removed candidate value estimated based on the acquired plurality of candidate values ​​for each parameter 121. This allows the information processing device 100 to improve the accuracy of calculating the ground state energy of molecules, for example, in order to analyze the structure or properties of molecules that are candidates for drugs or materials.

Description

[Technical Field]

[0001] The present invention relates to an information processing program, an information processing method, and an information processing apparatus. [Background technology]

[0002] Traditionally, quantum chemical calculations have been used in fields such as drug discovery and materials development to analyze the structure or properties of molecules that are candidates for drugs or materials. Quantum chemical calculations, for example, calculate the energy of a molecule. This energy can be either ground energy or excitation energy. To reduce the processing load of quantum chemical calculations, there are molecular partitioning methods that divide the molecular structure into multiple fragments, calculate the energy of each fragment, and then integrate them to calculate the molecular energy. Examples of molecular partitioning methods include BE (Bootstrap Embedding) or DMET (Density Matrix Embedding Theory).

[0003] Prior art includes, for example, techniques for calculating molecular energy corresponding to interatomic distance. Other techniques include, for example, techniques for executing variational quantum amplitude estimation algorithms. Still other techniques include, for example, performing single-particle basis rotations on a qubit system encoding the state of a chemical system, measuring the Jordan-Wigner transform of the particle density operator, and determining the energy of the chemical system. Furthermore, for example, there are techniques for probabilistically canceling noise in measurement-based quantum devices. [Prior art documents] [Patent Documents]

[0004] [Patent Document 1] Japanese Patent Publication No. 2024-047969 [Patent Document 2] Japanese Patent Publication No. 2023-039444 [Patent Document 3] U.S. Patent Application Publication No. 2022 / 0254453 [Patent Document 4] U.S. Patent Application Publication No. 2023 / 0196172 [Overview of the project] [Problems that the invention aims to solve]

[0005] However, with conventional techniques, it is difficult to improve the accuracy of calculating molecular energy when using molecular partitioning methods. For example, when calculating the energy of a fragment using a variational quantum eigenvalue solver with a physical quantum computer, the accuracy of calculating the molecular energy can decrease due to the influence of noise.

[0006] In one aspect, the present invention aims to improve the accuracy of calculating molecular energy using molecular partitioning techniques. [Means for solving the problem]

[0007] According to one embodiment, when calculating the energy of a molecule based on the energy of each of several fragments obtained by dividing the molecular structure using a molecular partitioning method, an information processing program, information processing method, and information processing device are proposed. For each of the several parameters of a first variational quantum circuit that represents the Hamiltonian of the fragment, a noise-removed candidate value is estimated based on several candidate values ​​that can be solutions to the parameter, calculated by a variational quantum eigenvalue solver. For each of the several parameters of the fragment, the energy of the fragment is calculated based on the noise-removed candidate value estimated for each of the parameters. [Effects of the Invention]

[0008] According to one embodiment, it becomes possible to improve the accuracy of calculating molecular energy using molecular partitioning techniques. [Brief explanation of the drawing]

[0009] [Figure 1] FIG. 1 is an explanatory diagram showing one example of an information processing method according to an embodiment. [Figure 2] FIG. 2 is an explanatory diagram showing one example of an information processing system 200. [Figure 3] FIG. 3 is a block diagram showing a hardware configuration example of an information processing apparatus 100. [Figure 4] FIG. 4 is a block diagram showing a hardware configuration example of a chemical calculation apparatus 201. [Figure 5] FIG. 5 is a block diagram showing a functional configuration example of the information processing apparatus 100. [Figure 6] FIG. 6 is an explanatory diagram showing an operation policy. [Figure 7] FIG. 7 is an explanatory diagram (Part 1) showing an operation example of the information processing apparatus 100. [Figure 8] FIG. 8 is an explanatory diagram (Part 2) showing an operation example of the information processing apparatus 100. [Figure 9] FIG. 9 is an explanatory diagram showing one example of an effect. [Figure 10] FIG. 10 is a flowchart showing one example of an overall processing procedure. [Figure 11] FIG. 11 is a flowchart showing one example of a calculation processing procedure. MODE FOR CARRYING OUT THE INVENTION

[0010] Hereinafter, with reference to the drawings, embodiments of an information processing program, an information processing method, and an information processing apparatus according to the present invention will be described in detail.

[0011] (One Example of the Information Processing Method According to the Embodiment) FIG. 1 is an explanatory diagram showing one example of the information processing method according to the embodiment. The information processing apparatus 100 is a computer for calculating molecular energy using a molecular division technique. The information processing apparatus 100 is, for example, a server or a PC (Personal Computer).

[0012] Traditionally, quantum chemical calculations have been desirable in fields such as drug discovery and materials development. Quantum chemical calculations, for example, involve calculating the energy of molecules. This energy can be either ground energy or excitation energy.

[0013] Here, there is a method called a variational quantum eigensolver that calculates the energy of a molecule. In the following explanation, the variational quantum eigensolver may be referred to as "VQE (Variational Quantum Eigensolver)".

[0014] VQE is a variational algorithm. For example, VQE sets up a variational quantum circuit that represents the Hamiltonian of a molecule and updates the parameters of the set variational quantum circuit to minimize the expectation value of the Hamiltonian. The variational quantum circuit manipulates, for example, the quantum states that represent the molecular state.

[0015] VQE is performed using actual quantum computers of a scale known as NISQ (Noisy Intermediate-Scale Quantum Computer). In NISQ, errors can occur in the quantum state due to noise. Examples of noise include environmental noise, interference noise between qubits, and noise during qubit manipulation.

[0016] However, as the size of the molecule increases, the impact of noise in NISQ on the accuracy of calculating the molecular energy using VQE tends to become greater. Size refers to factors such as the number of atoms forming the molecule. Therefore, maintaining accuracy in calculating the molecular energy becomes difficult. Furthermore, increasing the size of the molecule can lead to increased processing time and processing load when calculating the molecular energy.

[0017] In contrast, to maintain the accuracy of calculating molecular energy while reducing the processing time and burden involved in calculating molecular energy, there are molecular fragmentation methods that divide the molecular structure into multiple fragments. In molecular fragmentation methods, the molecular energy is calculated by calculating the energy of each fragment and then integrating them.

[0018] In molecular partitioning methods, VQE (Variable Quantitative Equation) is sometimes used to calculate the energy of each fragment. Specifically, VQE can be used to calculate the fragment energy based on the results of an eigenvalue problem using the Hamiltonian. Examples of molecular partitioning methods include BE (Bootstrap Embedding) or DMET (Density Matrix Embedding Theory).

[0019] However, when using molecular partitioning techniques, it is difficult to improve the accuracy of calculating molecular energy. For example, one might consider using a physical quantum computer and utilizing VQE to calculate the energy of each fragment. In this case, the calculation of the energy of each fragment is affected by noise in the physical quantum computer, which can lead to a decrease in the accuracy of calculating the molecular energy.

[0020] Here, there is a technique called ZNE (Zero Noise Extrapolation) to suppress the effects of noise on actual quantum computers. ZNE is applied, for example, when calculating the energy of molecules using VQE. Specifically, ZNE uses VQE to calculate the energy of molecules affected by noise by utilizing each variational quantum circuit of multiple variational quantum circuits with different degrees of noise influence, and estimates the energy of molecules unaffected by noise.

[0021] Similarly, it is desirable to improve the accuracy of calculating molecular energy by applying ZNE to molecular decomposition methods. Conventionally, no method has been proposed for applying ZNE to molecular decomposition methods. For example, in molecular decomposition methods, the eigenvalue problem using the Hamiltonian is calculated using VQE without directly calculating the energy. Therefore, there is a problem in that ZNE cannot be simply applied to VQE in molecular decomposition methods. As a result, it is difficult to improve the accuracy of calculating molecular energy using molecular decomposition methods.

[0022] Therefore, in this embodiment, we will describe an information processing method that can improve the accuracy of calculating molecular energy using a molecular partitioning technique.

[0023] In Figure 1, the information processing device 100 identifies each of the multiple fragments 111 obtained by dividing the molecular structure 110. The information processing device 100 sets the Hamiltonian for each fragment 111. The information processing device 100 calculates the energy of the molecule by calculating and integrating the energy of each fragment 111 using a molecular decomposition method. Specifically, the information processing device 100 calculates the energy of each fragment 111 as shown in (1-1) and (1-2) below.

[0024] (1-1) For each fragment 111, the information processing device 100 obtains a plurality of candidate values ​​that can be solutions for each parameter 121 of the first variational quantum circuit 120. The first variational quantum circuit 120 represents the Hamiltonian of the fragment 111. The first variational quantum circuit 120 is, for example, the smallest scale variational quantum circuit that represents the Hamiltonian of the fragment 111. The first variational quantum circuit 120 may generate noise when executed on, for example, an actual quantum computer. The first variational quantum circuit 120 manipulates quantum states that represent molecular states.

[0025] Multiple candidate values ​​are calculated by VQE via a real quantum computer. Each of the multiple candidate values ​​is affected by noise in the real quantum computer when executing a specific variational quantum circuit. Specifically, each of the multiple candidate values ​​is affected by noise to a different degree. In the example in Figure 1, the multiple candidate values ​​are specifically candidate values ​​131 to 133.

[0026] Candidate value 131 is a candidate value that is treated as being affected by a reference noise originating from the first variational quantum circuit 120, calculated by VQE using the first variational quantum circuit 120. In other words, candidate value 131 is a candidate value that is treated as being affected by a reference noise of 1x originating from the first variational quantum circuit 120.

[0027] Candidate value 132 is a candidate value that is treated as being affected by three times the reference noise originating from the first variational quantum circuit 120, compared to candidate value 131, which is calculated by VQE using, for example, the superposition of the first variational quantum circuit 120. Here, superposition corresponds to sequentially connecting, for example, the first variational quantum circuit 120, the front-to-back inversion of the first variational quantum circuit 120, and the first variational quantum circuit 120.

[0028] Candidate value 133 is a candidate value that is treated as being affected by five times the reference noise originating from the first variational quantum circuit 120 compared to candidate value 131, which is calculated by VQE using, for example, the superposition of the first variational quantum circuit 120. Here, superposition corresponds to sequentially connecting, for example, the first variational quantum circuit 120, the front-to-back inversion of the first variational quantum circuit 120, the first variational quantum circuit 120, the front-to-back inversion of the first variational quantum circuit 120, and the first variational quantum circuit 120.

[0029] (1-2) For each fragment 111, the information processing device 100 estimates a noise-free candidate value for each parameter 121 of the first variational quantum circuit 120 based on a plurality of candidate values ​​obtained. In the example in Figure 1, the information processing device 100 specifically estimates a noise-free candidate value 140 based on three candidate values ​​131 to 133 that are treated as being affected by 1, 3, and 5 times the reference noise, respectively. In other words, candidate value 140 is a candidate value that is treated as being affected by, for example, 0 times the reference noise. In other words, candidate value 140 is a candidate value that is treated as not being affected by, for example, the reference noise.

[0030] As a result, the information processing device 100 can obtain, for each fragment 111, a solution for each parameter 121 of the first variational quantum circuit 120 that is unaffected by noise in the actual quantum computer.

[0031] (1-3) For each fragment 111, the information processing device 100 calculates the energy of the fragment 111 based on noise-free candidate values ​​estimated for each parameter 121 of the first variational quantum circuit 120.

[0032] The information processing device 100 calculates a reduced density matrix for each fragment 111, for example, based on noise-free candidate values ​​estimated for each parameter 121 of the first variational quantum circuit 120. The information processing device 100 calculates the energy of each fragment 111, for example, based on the calculated reduced density matrix. In the following description, the reduced density matrix may be referred to as "RDM (Reduced Density Matrix)".

[0033] This allows the information processing device 100 to improve the accuracy of calculating the energy of each fragment 111. The information processing device 100 can suppress the effects of noise in the actual quantum computer and improve the accuracy of calculating the energy of each fragment 111. As a result, the information processing device 100 can improve the accuracy of calculating the energy of the molecule based on the energy of each fragment 111. The information processing device 100 can reduce the processing time and processing load required to calculate the energy of the molecule while maintaining the accuracy of calculating the energy of the molecule using the molecular partitioning method.

[0034] Here, we have described the case where the functions of the information processing device 100 are realized by a single computer, but this is not the only case. For example, the functions of the information processing device 100 may be realized through the collaboration of multiple computers. For example, the functions of the information processing device 100 may be realized on the cloud.

[0035] (An example of information processing system 200) Next, using Figure 2, we will describe an example of an information processing system 200 to which the information processing device 100 shown in Figure 1 is applied.

[0036] Figure 2 is an explanatory diagram showing an example of an information processing system 200. In Figure 2, the information processing system 200 includes an information processing device 100, one or more chemical calculation devices 201, and one or more client devices 202.

[0037] In the information processing system 200, the information processing device 100 and the chemical calculation device 201 are connected via a wired or wireless network 210. The network 210 is, for example, a LAN (Local Area Network), a WAN (Wide Area Network), or the Internet. In the information processing system 200, the information processing device 100 and the client device 202 are connected via a wired or wireless network 210.

[0038] The information processing device 100 is a computer for controlling quantum chemical calculations. Quantum chemical calculations include, for example, calculating the energy of a target molecule. The energy is, for example, ground energy or excitation energy. The information processing device 100 receives a processing request that requests to perform quantum chemical calculations on a target molecule using a molecular resolution method. The molecular resolution method is, for example, BE or DMET.

[0039] A processing request may include, for example, structural information indicating the structure of the target molecule. This structural information may include, for example, the coordinates of each of the multiple atoms that make up the target molecule. The structural information may also include, for example, the types of each of the multiple atoms that make up the target molecule. A processing request may also include, for example, a number of divisions indicating how many fragments the structure of the target molecule should be divided into. The number of divisions may be, for example, pre-set by the user.

[0040] The information processing device 100 identifies the structure of the target molecule based on the structural information included in the processing request. The information processing device 100 divides the identified structure of the target molecule into multiple fragments equal to the number of divisions, thereby generating fragment information representing each fragment. Based on the fragment information, the information processing device 100 performs quantum chemical calculations to calculate the energy of the target molecule by extending DMET as shown below.

[0041] The information processing device 100, for example, in cooperation with the chemical calculation device 201, repeatedly performs a series of processes to calculate the energy of each fragment until a predetermined termination condition is met. The predetermined termination condition is, for example, that the sum of the number of atoms in each fragment matches the number of atoms in the molecule.

[0042] The series of processes includes, for example, a first process of calculating solutions for each parameter of the variational quantum circuit representing the Hamiltonian by using VQE to compute an eigenvalue problem using the Hamiltonian for each fragment. The series of processes includes, for example, a second process of calculating a quantum density matrix for each fragment based on the calculated solutions for each parameter, and calculating the energy of the fragment based on the calculated quantum density matrix. The series of processes includes, for example, a third process of updating the Hamiltonian of each fragment if a predetermined termination condition is not met when calculating the energy of each fragment.

[0043] Specifically, when the information processing device 100 performs the first processing, it prepares a plurality of variational quantum circuits with different degrees of noise influence for each fragment, based on a reference variational quantum circuit that represents the Hamiltonian of the fragment. The plurality of variational quantum circuits include, for example, a variational quantum circuit that is logically equivalent to the reference variational quantum circuit but is on a different scale. The plurality of variational quantum circuits may also include, for example, the reference variational quantum circuit.

[0044] Specifically, for each fragment, the information processing device 100 calculates multiple candidate values ​​that can be solutions for each parameter of the reference variational quantum circuit by having the chemical calculation device 201 execute each variational quantum circuit, using VQE. Each of the multiple candidate values ​​has a different degree of noise influence. Specifically, for each fragment, the information processing device 100 calculates a candidate value that is treated as unaffected by noise, which is a solution for each parameter of the reference variational quantum circuit, based on the multiple candidate values ​​calculated.

[0045] The information processing device 100 calculates the energy of the target molecule based on the last calculated energy of each fragment when predetermined termination conditions are met. The information processing device 100 outputs the calculated energy of the target molecule as a result of performing quantum chemical calculations on the target molecule. Output formats include, for example, display on a screen, print to a printer, transmit to another computer, or store in a memory area. The other computer is, for example, a client device 202.

[0046] The information processing device 100 transmits to the client device 202 the energy of the target molecule calculated as a result of performing quantum chemical calculations on the target molecule. The information processing device 100 may also output the energy of the target molecule calculated as a result of performing quantum chemical calculations on the target molecule so that the user can refer to it. The information processing device 100 is, for example, a server or a PC.

[0047] The chemical calculation device 201 is a computer that performs quantum chemical calculations on molecules. The chemical calculation device 201 executes variational quantum circuits according to the control of the information processing device 100. The chemical calculation device 201 returns the results of executing the variational quantum circuits to the information processing device 100. The chemical calculation device 201 is, for example, a physical quantum computer. The chemical calculation device 201 may also be, for example, a server or PC with a noisy quantum simulator.

[0048] The client device 202 is a computer used by a user who wishes to perform quantum chemical calculations on a target molecule. The user is, for example, a worker. In response to the user's input, the client device 202 generates a processing request that requests to perform quantum chemical calculations on the target molecule using a molecular partitioning method. In response to the user's input, the client device 202 obtains structural information indicating the structure of the target molecule. The client device 202 generates a processing request that includes structural information indicating the structure of the target molecule.

[0049] The client device 202 transmits the generated processing request to the information processing device 100. The client device 202 receives the results of the quantum chemical calculation performed on the target molecule from the information processing device 100. For example, the client device 202 receives the energy of the target molecule from the information processing device 100 as a result of the quantum chemical calculation performed on the target molecule. The client device 202 outputs the results of the quantum chemical calculation performed on the target molecule so that the user can refer to them. The client device 202 may be, for example, a PC, a tablet terminal, or a smartphone.

[0050] This explanation describes a case where the information processing device 100 is a different device from the chemical calculation device 201, but it is not limited to this case. For example, the information processing device 100 may have the functionality of a chemical calculation device 201 and may operate as a chemical calculation device 201. In this case, the information processing system 200 does not need to include a chemical calculation device 201.

[0051] This explanation describes a case where the information processing device 100 is a different device from the client device 202, but it is not limited to this case. For example, the information processing device 100 may have the functionality of a client device 202 and may operate as a client device 202. In this case, the information processing system 200 does not need to include a client device 202.

[0052] (Example of hardware configuration of information processing device 100) Next, an example of the hardware configuration of the information processing device 100 will be described using Figure 3.

[0053] Figure 3 is a block diagram showing an example of the hardware configuration of the information processing device 100. In Figure 3, the information processing device 100 includes a CPU (Central Processing Unit) 301, a memory 302, and a network interface 303. The information processing device 100 also includes a recording medium interface 304, a recording medium 305, a display 306, and an input device 307. Each component is connected by a bus 300.

[0054] Here, the CPU 301 is responsible for the overall control of the information processing device 100. The memory 302 includes, for example, ROM (Read Only Memory), RAM (Random Access Memory), and flash ROM. Specifically, for example, flash ROM and ROM store various programs, and RAM is used as the work area for the CPU 301. Programs stored in memory 302 are loaded into the CPU 301, causing the CPU 301 to execute the coded processes.

[0055] The network interface 303 is connected to network 210 via a communication line, and then connects to other computers via network 210. The network interface 303 manages the internal interface with network 210 and controls the input and output of data from other computers. The network interface 303 is, for example, a modem or a LAN adapter.

[0056] The recording medium interface (I / F) 304 controls the reading and writing of data to the recording medium 305 according to the control of the CPU 301. The recording medium interface (I / F) 304 is, for example, a disk drive, an SSD (Solid State Drive), or a USB (Universal Serial Bus) port. The recording medium 305 is a non-volatile memory that stores the data written under the control of the recording medium interface (I / F) 304. The recording medium 305 is, for example, a disk, semiconductor memory, or USB memory. The recording medium 305 may be detachable from the information processing device 100.

[0057] Display 306 displays data such as cursors, icons, toolboxes, documents, images, or functional information. Display 306 is, for example, a CRT (Cathode Ray Tube), a liquid crystal display, or an organic EL (Electroluminescence) display. Input device 307 has keys for inputting characters, numbers, or various instructions, and performs data input. Input device 307 is, for example, a keyboard or a mouse. Input device 307 may also be, for example, a touch panel input pad or a numeric keypad.

[0058] The information processing device 100 may have, in addition to the components described above, a camera, for example. Furthermore, the information processing device 100 may have, in addition to the components described above, a printer, scanner, microphone, or speaker, for example. Also, the information processing device 100 may have multiple recording medium interfaces 304 and recording mediums 305, for example. Furthermore, the information processing device 100 does not necessarily have, for example, a display 306 or an input device 307. Also, the information processing device 100 does not necessarily have, for example, recording medium interfaces 304 and recording mediums 305.

[0059] (Example hardware configuration of chemical calculation system 201) Next, we will describe an example of the hardware configuration of the chemical calculation device 201 using Figure 4.

[0060] Figure 4 is a block diagram showing an example of the hardware configuration of the chemical calculation device 201. In Figure 4, the chemical calculation device 201 includes a CPU 401, memory 402, network interface 403, recording medium interface 404, and recording medium 405. The chemical calculation device 201 further includes a housing interface 406 and a housing 407. Each component is connected by a bus 400.

[0061] Here, the CPU 401 controls the entire chemical calculation device 201. The memory 402 includes, for example, ROM, RAM, and flash ROM. Specifically, for example, flash ROM and ROM store various programs, and RAM is used as the work area for the CPU 401. Programs stored in memory 402 are loaded into the CPU 401, causing the CPU 401 to execute the coded processes.

[0062] The network interface 403 is connected to network 210 via a communication line, and then connects to other computers via network 210. The network interface 403 manages the internal interface with network 210 and controls the input and output of data from other computers. The network interface 403 is, for example, a modem or a LAN adapter.

[0063] The recording medium interface (I / F) 404 controls the reading and writing of data to the recording medium (SSD) 405 according to the control of the CPU 401. The recording medium interface (I / F) 404 is, for example, a disk drive, SSD, or USB port. The recording medium (SSD) 405 is a non-volatile memory that stores the data written under the control of the recording medium interface (I / F) 404. The recording medium (SSD) 405 is, for example, a disk, semiconductor memory, or USB memory. The recording medium (SSD) 405 may be detachable from the chemical calculation device (CMS) 201.

[0064] The chassis interface 406 controls access to the chassis 407 according to the control of the CPU 401. The chassis interface 406 uses a microwave pulse generator to convert the output signal from the CPU 401 into an input signal for the chassis 407 and transmits it to the chassis 407. The chassis interface 406 uses a microwave pulse demodulator to convert the output signal from the chassis 407 into an input signal for the CPU 401 and transmits it to the CPU 401. The chassis 407 is a computing device equipped with one or more qubit chips cooled to an extremely low temperature of 10 mK. A qubit chip represents, for example, a logical qubit. The chassis 407 uses one or more qubit chips to perform predetermined calculations in response to input signals and outputs an output signal corresponding to the result of the predetermined calculations.

[0065] In addition to the components described above, the chemical calculation device 201 may also have, for example, a keyboard, mouse, display, printer, scanner, microphone, speaker, etc. Furthermore, the chemical calculation device 201 may have multiple recording medium interfaces 404 and 405. Alternatively, the chemical calculation device 201 may not have recording medium interfaces 404 and 405. Also, the qubit chip in the housing 407 may be controlled by a method other than microwaves. The qubit chip in the housing 407 may, for example, realize an optical qubit.

[0066] (Example hardware configuration for client device 202) The hardware configuration example for client device 202 is specifically the same as the hardware configuration example for information processing device 100 shown in Figure 3, so a detailed explanation is omitted.

[0067] (Example of the functional configuration of the information processing device 100) Next, an example of the functional configuration of the information processing device 100 will be described using Figure 5.

[0068] Figure 5 is a block diagram showing an example of the functional configuration of the information processing device 100. The information processing device 100 includes a storage unit 500, an acquisition unit 501, a division unit 502, an iteration unit 503, and an output unit 504. The iteration unit 503 includes an estimation unit 511 and a calculation unit 512.

[0069] The storage unit 500 is implemented by a storage area such as the memory 302 or recording medium 305 shown in Figure 3. The following description will focus on the case where the storage unit 500 is included in the information processing device 100, but is not limited to this case. For example, the storage unit 500 may be included in a device different from the information processing device 100, and the contents of the storage unit 500 may be accessible from the information processing device 100.

[0070] The acquisition unit 501 to the output unit 504 function as an example of a control unit. Specifically, the acquisition unit 501 to the output unit 504 realize their functions, for example, by having the CPU 301 execute a program stored in a storage area such as the memory 302 or recording medium 305 shown in Figure 3, or by using the network I / F 303. The processing results of each functional unit are stored in a storage area such as the memory 302 or recording medium 305 shown in Figure 3.

[0071] The storage unit 500 stores various types of information that are referenced or updated during processing of each functional unit. The storage unit 500 stores, for example, structural information that shows the structure of the target molecule. The structural information includes, for example, the coordinates of each of the multiple atoms that make up the target molecule. The structural information includes, for example, the types of each of the multiple atoms that make up the target molecule. The structural information includes, for example, the index of each of the multiple atoms that make up the target molecule. The structural information is acquired, for example, by the acquisition unit 501. The structural information may be pre-set by, for example, the user. The structural information is referenced, for example, by the iteration unit 503.

[0072] The memory unit 500 stores, for example, a basis set. A basis set is a set of functions that represent molecular orbitals. Examples of basis sets include cc-pV5Z, cc-pVQZ, cc-pVTZ, cc-pVDZ, or STO-3G. A basis set is retrieved, for example, by the acquisition unit 501. A basis set may be pre-set by, for example, the user. A basis set is referenced, for example, by the iteration unit 503.

[0073] The memory unit 500 stores, for example, the number of divisions. The number of divisions indicates, for example, how many fragments the structure of the target molecule will be divided into. The number of divisions is, for example, the number of fragments. The number of divisions is retrieved, for example, by the retrieval unit 501. The number of divisions may be set in advance by, for example, the user. The number of divisions is referenced, for example, by the division unit 502.

[0074] The storage unit 500 stores fragment information, for example, indicating each of the multiple fragments obtained by dividing the structure of the target molecule. The fragment information includes, for example, the index of each atom belonging to the fragment from among the multiple atoms that make up the target molecule. The fragment information is generated, for example, by the division unit 502. The fragment information may be acquired, for example, by the acquisition unit 501. The fragment information may be pre-set by, for example, the user. The fragment information is referenced, for example, by the iteration unit 503.

[0075] The acquisition unit 501 acquires various types of information used in the processing of each functional unit. The acquisition unit 501 stores the acquired information in the storage unit 500 or outputs it to each functional unit. The acquisition unit 501 may also output the information stored in the storage unit 500 to each functional unit. The acquisition unit 501 acquires various types of information, for example, based on user input. The acquisition unit 501 may also receive various types of information from a device other than the information processing device 100, for example.

[0076] The acquisition unit 501 acquires, for example, a processing request that requests to perform quantum chemical calculations on a target molecule. The processing request may include, for example, structural information. The processing request may include, for example, a basis set. The processing request may include, for example, the number of divisions. The processing request may include, for example, fragment information. Specifically, the acquisition unit 501 acquires a processing request by accepting input of a processing request based on user operation input. Specifically, the acquisition unit 501 may acquire a processing request by receiving a processing request from another computer. The other computer is, for example, a client device 202.

[0077] The acquisition unit 501 acquires structural information, for example. Specifically, the acquisition unit 501 acquires structural information by extracting it from a processing request. Specifically, the acquisition unit 501 may acquire structural information by accepting input of structural information based on user operation input. Specifically, the acquisition unit 501 may acquire structural information by receiving structural information from another computer. The other computer is, for example, a client device 202.

[0078] The acquisition unit 501 acquires, for example, a basis function set. Specifically, the acquisition unit 501 acquires a basis function set by extracting it from a processing request. Specifically, the acquisition unit 501 may acquire a basis function set by accepting input of a basis function set based on user operation input. Specifically, the acquisition unit 501 may acquire a basis function set by receiving a basis function set from another computer. The other computer is, for example, a client device 202.

[0079] The acquisition unit 501 acquires, for example, the number of divisions. Specifically, the acquisition unit 501 acquires the number of divisions by extracting the number of divisions from the processing request. Specifically, the acquisition unit 501 may acquire the number of divisions by accepting input of the number of divisions based on user operation input. Specifically, the acquisition unit 501 may acquire the number of divisions by receiving the number of divisions from another computer. The other computer is, for example, the client device 202.

[0080] The acquisition unit 501 acquires fragment information, for example. Specifically, the acquisition unit 501 acquires fragment information by extracting it from a processing request. Specifically, the acquisition unit 501 may acquire fragment information by accepting fragment information input based on user operation input. Specifically, the acquisition unit 501 may acquire fragment information by receiving fragment information from another computer. The other computer is, for example, a client device 202.

[0081] The acquisition unit 501 may receive a start trigger to initiate processing in any of the functional units. A start trigger may be, for example, a predetermined operation input by a user. A start trigger may also be, for example, the receipt of predetermined information from another computer. A start trigger may also be, for example, the output of predetermined information by any of the functional units. The acquisition unit 501 accepts, for example, the acquisition of a processing request as a start trigger to initiate processing in the splitting unit 502 and the iteration unit 503.

[0082] The splitting unit 502 generates fragment information for each fragment by dividing the structure of the target molecule into multiple fragments equal to the number of divisions obtained by the acquisition unit 501, based on the structural information acquired by the acquisition unit 501. For example, the splitting unit 502 divides the structure of the target molecule into multiple fragments such that each fragment contains an atom other than hydrogen and a hydrogen atom directly connected to that atom. This allows the splitting unit 502 to reduce the workload on the user when generating fragment information.

[0083] The iterative unit 503 calculates the energy of the target molecule based on the energy of each of the multiple fragments obtained by dividing the structure of the target molecule using a molecular decomposition method. The molecular decomposition method is, for example, BE or DMET. The iterative unit 503 sets the Hamiltonian for each of the multiple fragments based on, for example, structural information, basis set, and fragment information.

[0084] The iterative unit 503 repeatedly performs a series of processes by the estimation unit 511 and the calculation unit 512, for example, until a predetermined termination condition is met. The predetermined termination condition is set in advance by the user, for example. The predetermined termination condition is that the sum of the number of atoms in each fragment matches the number of atoms in the molecule. This allows the iterative unit 503 to perform quantum chemical calculations to calculate the energy of the target molecule.

[0085] For each fragment, the estimation unit 511 estimates noise-free candidate values ​​that are solutions for each of the multiple parameters of the first variational quantum circuit that represents the Hamiltonian of the fragment.

[0086] The estimation unit 511 obtains, for example, multiple candidate values ​​for each fragment that can be solutions for each parameter of the first variational quantum circuit calculated by VQE. Specifically, the estimation unit 511 sets up the first variational quantum circuit for each fragment. Specifically, the estimation unit 511 sets up one or more second variational quantum circuits for each fragment that are logically equivalent to the first variational quantum circuit, have multiple parameters in common with the first variational quantum circuit, and are larger in scale than the first variational quantum circuit.

[0087] A second variational quantum circuit is formed, for example, by connecting one or more pairs of a first variational quantum circuit and a third variational quantum circuit (which is the first variational quantum circuit with its front and back reversed), and then connecting the first variational quantum circuit. Therefore, the second variational quantum circuit has several parameters in common with the first variational quantum circuit. The second variational quantum circuit is thought to be affected, for example, by a multiple of the reference noise that may occur when the first variational quantum circuit is executed.

[0088] Specifically, the estimation unit 511 calculates first candidate values ​​that can be solutions for each parameter of the first variational quantum circuit by VQE, by executing the set first variational quantum circuit for each fragment. The first candidate values ​​are treated as candidate values ​​affected by a reference noise of 1x. The estimation unit 511 may execute the first variational quantum circuit on the information processing device 100 or on the chemical calculation device 201.

[0089] Specifically, the estimation unit 511 calculates second candidate values ​​that can be solutions for each parameter of the first variational quantum circuit by VQE, by executing each set second variational quantum circuit for each fragment. The second candidate values ​​are treated as candidate values ​​influenced by a multiple of the reference noise. The estimation unit 511 may execute each second variational quantum circuit on the information processing device 100 or on the chemical calculation device 201.

[0090] As a result, the estimation unit 511 can obtain multiple candidate values ​​with different degrees of noise influence, and can estimate candidate values ​​that are not affected by the noise. Specifically, the estimation unit 511 can treat the noise as being affected by zero times the reference noise, and can estimate candidate values ​​that are assumed to have not been affected by the reference noise.

[0091] The estimation unit 511 estimates, for example, for each fragment, a noise-free candidate value that is a solution for each parameter of the first variational quantum circuit, based on a plurality of candidate values ​​obtained. The plurality of candidate values ​​include, for example, a calculated first candidate value and a calculated second candidate value. Specifically, for each fragment, the estimation unit 511 estimates a candidate value that is assumed to be unaffected by the reference noise, based on a plurality of candidate values ​​obtained by linear approximation, for each parameter of the first variational quantum circuit. As a result, the estimation unit 511 can accurately calculate the solution for each parameter of the first variational quantum circuit for each fragment.

[0092] The calculation unit 512 calculates the energy of each fragment based on the noise-removed candidate values ​​estimated by the estimation unit 511 for each parameter. The calculation unit 512 calculates the RDM for each fragment based on the noise-removed candidate values ​​estimated by the estimation unit 511 for each parameter. The calculation unit 512 calculates the energy of each fragment based on the calculated RDM. This allows the calculation unit 512 to accurately calculate the energy of each fragment, removing the effects of noise originating from the actual quantum computer.

[0093] The iterative unit 503 calculates the energy of the target molecule based on the energy of each fragment calculated by the estimation unit 511 and the calculation unit 512 in a series of processes. For example, the iterative unit 503 calculates the sum of the calculated energies of each fragment as the energy of the target molecule. In this way, the iterative unit 503 can appropriately calculate the energy of the target molecule.

[0094] The iterative unit 503 determines whether the termination condition is met when it has calculated the energy of each fragment through a series of processes performed by the estimation unit 511 and the calculation unit 512. The termination condition is, for example, that the sum of the number of atoms corresponding to each fragment matches the number of atoms corresponding to the target molecule. This allows the iterative unit 503 to determine whether it has finished appropriately calculating the energy of each fragment.

[0095] The termination condition may be, for example, that the statistical value of the change in the energy of each fragment calculated this time compared to the energy of each fragment calculated last time is less than or equal to a threshold. The threshold can be, for example, pre-set by the user. The statistical value can be, for example, the maximum value, minimum value, mean value, mode value, or median value.

[0096] The iterative unit 503 updates the Hamiltonian of each fragment if the termination condition is not met. This allows the iterative unit 503 to optimize the Hamiltonian of each fragment. The iterative unit 503 can then recalculate the energy of each fragment.

[0097] The iterative unit 503 re-executes the series of processes performed by the estimation unit 511 and the calculation unit 512 in accordance with the update of the Hamiltonian of each fragment. This allows the iterative unit 503 to repeatedly perform the series of processes performed by the estimation unit 511 and the calculation unit 512 until a predetermined termination condition is met. The iterative unit 503 can optimize the energy of each fragment.

[0098] The output unit 504 outputs the processing result of at least one of the functional units. The output format can be, for example, display on a screen, print to a printer, transmit to an external device via the network interface 303, or store in a storage area such as the memory 302 or recording medium 305. This allows the output unit 504 to notify the user of the processing result of at least one of the functional units, thereby improving the usability of the information processing device 100.

[0099] The output unit 504 outputs, for example, the energy corresponding to the target molecule calculated by the iteration unit 503. Specifically, the output unit 504 outputs the energy corresponding to the target molecule in a way that the user can refer to. Specifically, the output unit 504 may transmit the energy corresponding to the target molecule to another computer. The other computer may be, for example, a client device 202. This makes the energy corresponding to the target molecule accessible externally by the output unit 504.

[0100] The output unit 504 may, for example, output the energy corresponding to each fragment calculated by the iteration unit 503. Specifically, the output unit 504 outputs the energy corresponding to each fragment in a way that is accessible to the user. Specifically, the output unit 504 may transmit the energy corresponding to each fragment to another computer. The other computer may be, for example, a client device 202. This allows the output unit 504 to make the energy corresponding to each fragment accessible externally.

[0101] Here, we have described a case in which the information processing device 100 includes an acquisition unit 501, a division unit 502, an iteration unit 503, and an output unit 504, but it is not limited to this. For example, the information processing device 100 may not include any of the functional units. Specifically, the information processing device 100 may not include the division unit 502. In this case, the information processing device 100 may cooperate with another computer that operates as the division unit 502. The other computer may be, for example, a chemical calculation device 201.

[0102] (Example of operation of the information processing device 100) Next, we will explain an example of the operation of the information processing device 100 using Figures 6 to 9. First, we will explain the operational policy of the information processing device 100 using Figure 6.

[0103] Figure 6 is an explanatory diagram illustrating the operational strategy. In Figure 6, it is assumed that the values ​​of the variational quantum circuit parameters p1 to p10 were calculated by VQE by executing variational quantum circuits with different degrees of noise influence for each LiH molecule via a noisy quantum simulator.

[0104] Specifically, let's assume that a variational quantum circuit that is unaffected by noise is executed via a noisy quantum simulator. Furthermore, let's assume that a variational quantum circuit that is affected by a reference noise, a variational quantum circuit that is affected by three times the reference noise, and a variational quantum circuit that is affected by five times the reference noise are executed via a noisy quantum simulator.

[0105] Graph 600 in Figure 6 shows the values ​​of the variational quantum circuit parameters p1 to p10 calculated by VQE by executing variational quantum circuits with different degrees of noise influence. Here, the values ​​of the variational quantum circuit parameters p1 to p10 calculated by VQE by executing a variational quantum circuit in which no noise influence occurs are indicated with the identifier "noise-free circuit".

[0106] Furthermore, by executing a variational quantum circuit in which the influence of the reference noise occurs, the values ​​of the variational quantum circuit parameters p1 to p10 calculated by VQE are indicated with the identifier "Original Circuit". Furthermore, by executing a variational quantum circuit in which the influence of the reference noise is three times greater, the values ​​of the variational quantum circuit parameters p1 to p10 calculated by VQE are indicated with the identifier "Circuit 3x". Furthermore, by executing a variational quantum circuit in which the influence of the reference noise is five times greater, the values ​​of the variational quantum circuit parameters p1 to p10 calculated by VQE are indicated with the identifier "Circuit 5x".

[0107] As shown in Graph 600, the values ​​of the variational quantum circuit parameters p1 to p10 change monotonically in accordance with the change in the degree of noise influence. Therefore, if multiple values ​​of the variational quantum circuit parameters p1 to p10 that are affected by noise are known, it is thought that it will be possible to estimate the values ​​that are not affected by noise.

[0108] Therefore, the information processing device 100 operates with the aim of improving the accuracy of calculating molecular energy by estimating values ​​for the variational quantum circuit parameters that are unaffected by noise during the process of implementing the molecular partitioning method using VQE. Next, we will move on to explaining Figures 7 and 8 and describe an example of the operation of the information processing device 100.

[0109] Figures 7 and 8 are explanatory diagrams illustrating an example of the operation of the information processing device 100. In Figure 7, the information processing device 100 divides the structure of the target molecule into multiple fragments. The information processing device 100 sets the Hamiltonian for each fragment. The information processing device 100 repeatedly performs a series of processes to calculate the energy of each fragment until the termination condition is met.

[0110] The termination condition is that the sum of the number of atoms in each fragment matches the number of atoms in the molecule. If the termination condition is not met, the information processing device 100 updates the Hamiltonian of each fragment. Here, we will explain how the information processing device 100 performs the series of processes to calculate the energy of each fragment.

[0111] (7-1) The information processing device 100 sets up, for example, a variational quantum circuit 700 that represents the Hamiltonian of each fragment. The variational quantum circuit 700 is treated as being affected by a reference noise of 1x. The noise is caused by the components of the variational quantum circuit 700. The components correspond to quantum gates, etc. The variational quantum circuit 700 has a parameter θ→. θ→ indicates that θ has an arrow attached to its upper part. θ→=[θ1,θ2,···,θ n ] where n is the number of parameters.

[0112] (7-2) The information processing device 100 sets up a variational quantum circuit 710 that, for each fragment, is treated as being affected by three times the noise. Specifically, if the variational quantum circuit 700 is U, the information processing device 100 sets up a variational quantum circuit 710 by sequentially connecting U, U†, and U. Since the variational quantum circuit 710 includes the same components as the variational quantum circuit 700, but three times the amount of the variational quantum circuit 700, it is treated as being affected by three times the reference noise. Since the variational quantum circuit 710 is a combination of U and U†, it has a parameter θ→ that is common to the variational quantum circuit 700.

[0113] (7-3) For each fragment, the information processing apparatus 100 sets, for example, a variational quantum circuit 720 that is treated as being affected by five times the reference noise. Specifically, if the variational quantum circuit 700 is denoted as U, the information processing apparatus 100 sets a variational quantum circuit 720 obtained by sequentially connecting U, U†, U, U†, and U. Since the variational quantum circuit 720 includes five times as many of the same components as the variational quantum circuit 700, it is treated as being affected by five times the reference noise. Because the variational quantum circuit 720 is a combination of U and U†, it shares the parameter vector θ with the variational quantum circuit 700. Next, the description proceeds to FIG. 8.

[0114] In FIG. 8, (8-1) For each fragment, the information processing apparatus 100 executes the variational quantum circuit 700 using the chemical calculation apparatus 201, thereby calculating, by VQE, the value of the parameter vector θ that is affected by one time the reference noise. Specifically, the information processing apparatus 100 obtains the value θ1 of the parameter vector θ (1) , θ2 (1) , ···, θ n (1) is calculated.

[0115] (8-2) For each fragment, the information processing apparatus 100 executes the variational quantum circuit 710 using the chemical calculation apparatus 201, thereby calculating, by VQE, the value of the parameter vector θ that is affected by three times the reference noise. Specifically, the information processing apparatus 100 obtains the value θ1 of the parameter vector θ (3) , θ2 (3) , ···, θ n (3) is calculated.

[0116] (8-3) For each fragment, the information processing apparatus 100 executes the variational quantum circuit 720 using the chemical calculation apparatus 201, thereby calculating, by VQE, the value of the parameter vector θ that is affected by five times the reference noise. Specifically, the information processing apparatus 100 obtains the value θ1 of the parameter vector θ (5) , θ2 (5) , ···, θ n(5) Calculate.

[0117] (8-4) For each fragment, the information processing device 100 calculates a value of parameter θ→ that will be treated as unaffected by the reference noise, based on the calculated value of parameter θ→. Specifically, the information processing device 100 calculates the value of parameter θ→ θ1 (0) θ2 (0) ,···,θ n (0) Calculate.

[0118] In the example shown in Figure 8, the information processing device 100 specifically, as shown in Graph 810, sets the value θ1 for the parameter θ1 (1) and value θ1 (3) and value θ1 (5) Based on this, the value θ1 is treated as unaffected by noise by linear approximation. (0) Similarly, the information processing device 100 calculates the value θ2 for the parameter θ2, as shown in graph 820. (1) and value θ2 (3) and value θ2 (5) Based on this, the value θ2 is treated as unaffected by noise using linear approximation. (0) The information processing device 100 calculates the parameters θ3, ...θ. n In contrast, the value θ3 is treated as unaffected by noise. (0) ,···θ n (0) Calculate.

[0119] (8-5) The information processing device 100 calculates the value of the parameter θ→ θ1 for each fragment. (0) θ2 (0) ,···,θ n (0)Based on this, the 1,2-RDM is calculated. For each fragment, the information processing device 100 calculates the energy and number of atoms of that fragment based on the calculated 1,2-RDM. In this way, the information processing device 100 can suppress the effects of noise in the actual quantum computer and calculate the energy and number of atoms of the fragments with high accuracy. Next, we will move on to the explanation of Figure 9 and describe an example of the effect of the information processing device 100.

[0120] Figure 9 is an explanatory diagram illustrating an example of the effect. In Figure 9, the conventional method and the proposed method using the information processing device 100 are compared. The conventional method calculates the energy of the molecule by applying VQE to the BE. As described above, the proposed method calculates the values ​​of parameters that are treated as unaffected by noise during the process of calculating the energy of the molecule by applying VQE to the BE. In the example in Figure 9, the molecule is assumed to be C3H8.

[0121] Graph 900 shows the difference in molecular energy between the conventional method and the proposed method, with the molecular energy calculated by FCI being considered the correct value. As shown in Graph 900, the proposed method can reduce the error in molecular energy compared to the conventional method.

[0122] (Overall processing procedure) Next, an example of the overall processing procedure executed by the information processing device 100 will be described using Figure 10. The overall processing is realized, for example, by the CPU 301 shown in Figure 3, storage areas such as memory 302 and recording medium 305, and network I / F 303.

[0123] Figure 10 is a flowchart showing an example of the overall processing procedure. In Figure 10, the information processing device 100 calculates the 1-RDM corresponding to the molecule (step S1001). Then, the information processing device 100 divides the molecule into multiple fragments (step S1002).

[0124] Next, the information processing apparatus 100 selects the i-th fragment (step S1003). Then, the information processing apparatus 100 generates a Hamiltonian for the selected fragment based on the penalty value (step S1004).

[0125] Next, the information processing apparatus 100 calculates a noise-free solution for each parameter of the variational quantum circuit with respect to the selected fragment by executing a calculation process described later with reference to Fig. 11 (step S1005). Then, the information processing apparatus 100 calculates the 1,2-RDM corresponding to the selected fragment (step S1006).

[0126] Next, the information processing apparatus 100 calculates the energy and the number of atoms of the selected fragment (step S1007). Then, the information processing apparatus 100 determines whether or not i≧N holds (step S1008). N is the total number of fragments.

[0127] Here, when i<N holds (step S1008: No), the information processing apparatus 100 increments i and returns to the process of step S1003. On the other hand, when i≧N holds (step S1008: Yes), the information processing apparatus 100 proceeds to the process of step S1009.

[0128] In step S1009, the information processing apparatus 100 calculates the energy of the molecule by integrating the energies of the respective fragments (step S1009). Next, the information processing apparatus 100 determines whether or not the sum of the number of atoms corresponding to each fragment matches the number of atoms corresponding to the molecule (step S1010).

[0129] Here, if they do not match (step S1010: No), the information processing apparatus 100 proceeds to the process of step S1011. On the other hand, if they match (step S1010: Yes), the information processing apparatus 100 proceeds to the process of step S1012.

[0130] In step S1011, the information processing device 100 updates the penalty value (step S1011), sets i to 0, and returns to the process in step S1003. In step S1012, the information processing device 100 outputs the energy and number of atoms of the molecule (step S1012) and terminates the entire process.

[0131] (Calculation process procedure) Next, an example of a calculation process performed by the information processing device 100 will be explained using Figure 11. The calculation process is realized, for example, by the CPU 301 shown in Figure 3, storage areas such as memory 302 and recording medium 305, and network I / F 303.

[0132] Figure 11 is a flowchart showing an example of the calculation process. In Figure 11, the information processing device 100 sets up a reference quantum circuit based on the Hamiltonian of the selected fragment (step S1101).

[0133] Next, the information processing device 100 superimposes the set reference quantum circuits to set up multiple variational quantum circuits, each with a different depth (step S1102). Then, the information processing device 100 calculates a noisy solution for each parameter of the reference quantum circuit by executing each variational quantum circuit (step S1103).

[0134] Next, the information processing device 100 calculates a noise-free solution for each parameter of the reference quantum circuit based on the noise-inducing solution (step S1104). Then, the information processing device 100 terminates the calculation process.

[0135] Here, the information processing device 100 may execute some steps of the flowcharts in Figures 10 and 11 in a different order. Alternatively, the information processing device 100 may omit some steps of the flowcharts in Figures 10 and 11.

[0136] (Examples of applications of the information processing device 100) The information processing device 100 can be applied, for example, to fields such as drug discovery or materials development. Specifically, the information processing device 100 can be applied in fields such as drug discovery or materials development when it is desirable to perform quantum chemical calculations to calculate the ground state energy of molecules in order to analyze the structure or properties of molecules that are candidates for drugs or materials. As a result, the information processing device 100 can reduce the processing time required to perform quantum chemical calculations while maintaining the accuracy of the quantum chemical calculations, making it easier to calculate the ground state energy of molecules, and thus contributing to fields such as drug discovery or materials development.

[0137] As explained above, the information processing device 100 can calculate the energy of a molecule based on the energy of each of the multiple fragments obtained by dividing the molecular structure using a molecular partitioning method. The information processing device 100 can identify multiple parameters of the first variational quantum circuit that represents the Hamiltonian of each fragment. The information processing device 100 can obtain multiple candidate values ​​that can be solutions for each parameter, calculated by VQE, for each fragment. The information processing device 100 can estimate a noise-removed candidate value for each parameter, based on the multiple candidate values ​​obtained for each fragment. The information processing device 100 can calculate the energy of a fragment based on the noise-removed candidate value estimated for each parameter. As a result, the information processing device 100 can improve the accuracy of calculating the energy of the molecule.

[0138] According to the information processing device 100, it is possible to set up one or more second variational quantum circuits that are logically equivalent to the first variational quantum circuit, have multiple parameters in common with the first variational quantum circuit, and are larger in scale than the first variational quantum circuit. According to the information processing device 100, for each fragment, multiple candidate values ​​that can be solutions for each parameter can be calculated by VQE using each second variational quantum circuit and the first variational quantum circuit via an actual quantum computer. As a result, the information processing device 100 can calculate multiple candidate values ​​that are useful when estimating noise-free candidate values.

[0139] According to the information processing device 100, a second variational quantum circuit can be set up by connecting one or more pairs of a first variational quantum circuit and a third variational quantum circuit which is the first variational quantum circuit with its front and back reversed, and then connecting the first variational quantum circuit. As a result, the information processing device 100 can set up a second variational quantum circuit which has a different degree of noise influence than the first variational quantum circuit, and can calculate candidate values ​​that are useful when estimating candidate values ​​from which noise has been removed.

[0140] According to the information processing device 100, the energy of the molecule can be calculated based on the energy of each fragment that has been calculated. This allows the information processing device 100 to complete the quantum chemical calculation to determine the energy of the molecule.

[0141] According to the information processing device 100, if the termination condition is not met when calculating the energy of each fragment, the Hamiltonian of each fragment can be updated. According to the information processing device 100, the estimation process and the calculation process can be re-executed according to the updated Hamiltonian of each fragment. In this way, the information processing device 100 can optimize the Hamiltonian and calculate the energy of the molecule with high accuracy.

[0142] According to the information processing device 100, the structure of a molecule can be divided into multiple fragments. This allows the information processing device 100 to identify these multiple fragments within its own system. The information processing device 100 can reduce the workload on the user when dividing the structure of a molecule into multiple fragments.

[0143] According to the information processing device 100, DMET can be used as the molecular partitioning method. This allows the information processing device 100 to improve the accuracy of calculating molecular energy using DMET.

[0144] The information processing method described in this embodiment can be implemented by executing a pre-prepared program on a computer such as a PC or workstation. The information processing program described in this embodiment is recorded on a computer-readable recording medium and executed by being read from the recording medium by the computer. The recording medium can be a hard disk, flexible disk, CD (Compact Disc)-ROM, MO (Magneto Optical Disc), DVD (Digital Versatile Disc), etc. Furthermore, the information processing program described in this embodiment may be distributed via a network such as the Internet.

[0145] With regard to the embodiments described above, the following additional information is disclosed.

[0146] (Note 1) When calculating the energy of a molecule based on the energy of each of the multiple fragments obtained by dividing the molecular structure using a molecular decomposition method, For each of the aforementioned fragments, a noise-removed candidate value is estimated based on a plurality of candidate values ​​that can be solutions for each of the multiple parameters of the first variational quantum circuit that represents the Hamiltonian of the fragment, calculated by a variational quantum eigenvalue solver. For each of the aforementioned fragments, the energy of the fragment is calculated based on the noise-removed candidate values ​​estimated for each of the aforementioned parameters. An information processing program characterized by having a computer perform the processing.

[0147] (Note 2) With respect to each of the fragments, using a quantum computer, the following calculations are performed using a variational quantum eigenvalue solver to calculate the multiple candidate values ​​that can be solutions for each of the parameters, each of which is logically equivalent to the first variational quantum circuit, has the multiple parameters common to the first variational quantum circuit, and is larger in scale than the first variational quantum circuit, and the first variational quantum circuit. An information processing program as described in Appendix 1, characterized in that it causes a computer to perform the processing.

[0148] (Note 3) The information processing program according to Note 2, characterized in that the second variational quantum circuit is formed by connecting one or more pairs of the first variational quantum circuit and a third variational quantum circuit which is the first variational quantum circuit with its front and back reversed, and then connecting the first variational quantum circuit.

[0149] (Note 4) Based on the calculated energy of each of the aforementioned fragments, the energy of the molecule is calculated. An information processing program according to any one of the appendices 1 to 3, characterized in that it causes the computer to perform the processing.

[0150] (Note 5) If the termination condition is not met when calculating the energy of each of the aforementioned fragments, the Hamiltonian of each of the aforementioned fragments shall be updated. The computer is made to perform the process, The information processing program according to Appendix 4, characterized in that the estimation process and the calculation process are re-executed in accordance with the updating of the Hamiltonian of each of the fragments.

[0151] (Note 6) Dividing the structure of the molecule into the plurality of fragments, An information processing program according to any one of the appendices 1 to 5, characterized in that it causes the computer to perform the processing.

[0152] (Note 7) The information processing program according to any one of Notes 1 to 6, characterized in that the molecular partitioning method is Density Matrix Embedding Theory or Bootstrap Embedding.

[0153] (Note 8) When calculating the energy of a molecule based on the energy of each of the multiple fragments obtained by dividing the molecular structure using a molecular decomposition method, For each of the aforementioned fragments, a noise-removed candidate value is estimated based on a plurality of candidate values ​​that can be solutions for each of the multiple parameters of the first variational quantum circuit that represents the Hamiltonian of the fragment, calculated by a variational quantum eigenvalue solver. For each of the aforementioned fragments, the energy of the fragment is calculated based on the noise-removed candidate values ​​estimated for each of the aforementioned parameters. An information processing method characterized in that the processing is performed by a computer.

[0154] (Note 9) When calculating the energy of a molecule based on the energy of each of the multiple fragments obtained by dividing the molecular structure using a molecular decomposition method, For each of the aforementioned fragments, a noise-removed candidate value is estimated based on a plurality of candidate values ​​that can be solutions for each of the multiple parameters of the first variational quantum circuit that represents the Hamiltonian of the fragment, calculated by a variational quantum eigenvalue solver. For each of the aforementioned fragments, the energy of the fragment is calculated based on the noise-removed candidate values ​​estimated for each of the aforementioned parameters. An information processing device characterized by having a control unit. [Explanation of Symbols]

[0155] 100 Information Processing Devices 110 Structure 111 Fragments 120 First Variational Quantum Circuit 121 parameters 131-133, 140 Candidate values 200 Information Processing Systems 201 Chemical calculation equipment 202 Client Devices 210 Network 300,400 buses 301,401 CPU 302,402 memory 303,403 Network I / F 304,404 Recording medium I / F 305,405 recording media 306 displays 307 Input device 406 Chassis I / F 407 cabinets 500 storage section 501 Acquisition Department 502 Split part 503 Repeat section 504 Output section 511 Estimation Department 512 Calculation Unit 600, 810, 820, 900 graph 700, 710, 720 Variational Quantum Circuits

Claims

1. When calculating the energy of a molecule based on the energy of each of the multiple fragments obtained by dividing the molecular structure using a molecular decomposition method, For each of the aforementioned fragments, a noise-removed candidate value is estimated based on a plurality of candidate values ​​that can be solutions for the parameter, calculated by a variational quantum eigenvalue solver, for each of the multiple parameters of the first variational quantum circuit that represents the Hamiltonian of the fragment. For each of the aforementioned fragments, the energy of the fragment is calculated based on the noise-removed candidate values ​​estimated for each of the aforementioned parameters. An information processing program characterized by having a computer perform the processing.

2. Using a quantum computer, with respect to each of the fragments, the following is performed: using the first variational quantum circuit and the first variational quantum circuit, each of the two second variational quantum circuits which are logically equivalent to the first variational quantum circuit, have the same set of parameters as the first variational quantum circuit, and are larger in scale than the first variational quantum circuit, the variational quantum eigenvalue solver calculates the multiple candidate values ​​that can be solutions for each of the parameters. The information processing program according to claim 1, characterized in that it causes a computer to perform the processing.

3. The information processing program according to claim 2, characterized in that the second variational quantum circuit is formed by connecting one or more pairs of the first variational quantum circuit and a third variational quantum circuit which is the first variational quantum circuit with its front and back reversed, and then connecting the first variational quantum circuit.

4. Based on the calculated energies of each of the aforementioned fragments, the energy of the molecule is calculated. An information processing program according to any one of claims 1 to 3, characterized in that it causes the computer to perform the processing.

5. If the termination condition is not met when calculating the energy of each of the aforementioned fragments, the Hamiltonian of each of the aforementioned fragments is updated. The computer is made to perform the process, The information processing program according to claim 4, characterized in that the estimation process and the calculation process are re-executed in accordance with the update of the Hamiltonian of each of the fragments.

6. When calculating the energy of a molecule based on the energy of each of the multiple fragments obtained by dividing the molecular structure using a molecular decomposition method, For each of the aforementioned fragments, a noise-removed candidate value is estimated based on a plurality of candidate values ​​that can be solutions for the parameter, calculated by a variational quantum eigenvalue solver, for each of the multiple parameters of the first variational quantum circuit that represents the Hamiltonian of the fragment. For each of the aforementioned fragments, the energy of the fragment is calculated based on the noise-removed candidate values ​​estimated for each of the aforementioned parameters. An information processing method characterized in that the processing is performed by a computer.

7. When calculating the energy of a molecule based on the energy of each of the multiple fragments obtained by dividing the molecular structure using a molecular decomposition method, For each of the aforementioned fragments, a noise-removed candidate value is estimated based on a plurality of candidate values ​​that can be solutions for the parameter, calculated by a variational quantum eigenvalue solver, for each of the multiple parameters of the first variational quantum circuit that represents the Hamiltonian of the fragment. For each of the aforementioned fragments, the energy of the fragment is calculated based on the noise-removed candidate values ​​estimated for each of the aforementioned parameters. An information processing device characterized by having a control unit.

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