JP2021196863A - System, information processing method, and program - Google Patents

Abstract

To provide a system capable of reducing a measurement error of a quantum state and estimating a solution of a problem, an information processing method, and a program.SOLUTION: A system includes one or a plurality of processors. The one or the plurality of processors perform the processing of: setting mutual action between a plurality of spins corresponding to a prescribed problem in an annealing machine; acquiring a plurality of calculation results obtainable by controlling the annealing machine so as to calculate a low energy state of the plurality of pins from the annealing machine; calculating one representative value from the plurality of calculation results about each of the plurality of spins; and estimating a solution of the prescribed problem on the basis of a representative value of each of the plurality of spins.SELECTED DRAWING: Figure 1

Description

The present invention relates to systems, information processing methods and programs.

In recent years, an annealing machine for estimating a solution to a predetermined problem by setting a desired interaction between a plurality of spins and obtaining the ground state of the plurality of spins has been used.

For example, Patent Document 1 below describes research results on error correction for reducing the influence of decoherence in quantum annealing.

Kristen L. Pudenz, Tameem Albash and Daniel A. Lidar, "Error-corrected quantum annealing with hundreds of qubits", Nature Communications volume 5, Article number: 3243, 2014

Although the technique described in Non-Patent Document 1 can reduce the influence of decoherence on quantum annealing, unintended changes in the quantum state can also occur when measuring the quantum state. There is currently relatively little research on reducing such measurement errors.

Therefore, the present invention provides a system, an information processing method, and a program for estimating the solution of a problem by reducing the measurement error of the quantum state.

The system according to one aspect of the present disclosure includes one or more processors, wherein the one or more processors set the interaction between the plurality of spins corresponding to a predetermined problem in the annealing machine. A plurality of calculation results obtained by controlling the annealing machine so as to calculate the low energy state of the spins are acquired from the annealing machine, and one representative value is calculated from the plurality of calculation results for each of the plurality of spins, and a plurality of calculation results are obtained. Performs a process that estimates the solution of a given problem based on the representative values of each spin.

According to this aspect, it is possible to calculate a representative value with reduced measurement error for each of the plurality of spins, and it is possible to estimate the solution of a predetermined problem with higher accuracy.

INDUSTRIAL APPLICABILITY According to the present invention, it is possible to provide a system, an information processing method and a program for estimating a solution of a problem by reducing a measurement error of a quantum state.

It is a figure which shows the outline of the system which concerns on embodiment of this disclosure. It is a figure which shows an example of the spin value of the annealing machine acquired by the system which concerns on this embodiment. It is a figure which shows the 1st example of the representative value of the spin calculated by the system which concerns on this embodiment. It is a figure which shows the 2nd example of the representative value of the spin calculated by the system which concerns on this embodiment. It is a figure which shows the 3rd example of the typical value of the spin calculated by the system which concerns on this embodiment. It is a figure which shows the structure of the client computer which concerns on this embodiment. It is a figure which shows the structure of the server computer which concerns on this embodiment. It is a flowchart of the process executed by the system which concerns on this embodiment. It is a flowchart of the process executed by the system which concerns on this embodiment.

Hereinafter, embodiments of the present disclosure will be described in detail with reference to the drawings. The same elements are designated by the same reference numerals, and duplicate description will be omitted.

In the present embodiment, a system that calculates low energy states of a plurality of spins corresponding to a solution of a predetermined problem a plurality of times by an annealing machine 20 and estimates a solution of a predetermined problem based on a representative value of each of the plurality of spins. 10 will be described.

<System application example>
FIG. 1 is a diagram showing an outline of the system 10 according to the embodiment of the present disclosure. The system 10 includes a client computer 500, a server computer 600, and an annealing machine 20. The client computer 500 and the server computer 600 are composed of a general-purpose classical computer as described in detail later. The annealing machine 20 is composed of a classical computer or a quantum computer, for example, includes a plurality of qubits, sets a desired Hamiltonian by adjusting the interaction between the qubits, and uses quantum annealing to make a qubit. It may be a quantum computer that obtains the ground state. However, the annealing machine 20 may be a classical computer that reproduces quantum annealing.

The client computer 500 is connected to the server computer 600 via a communication network such as the Internet. The server computer 600 is connected to the annealing machine 20 via a communication network such as a LAN (Local Area Network). The user of the client computer 500 indirectly sends a command to the annealing machine 20 by operating the client computer 500, and uses the annealing machine 20 to estimate a solution to a predetermined problem. The configuration of the system 10 is not limited to that shown in this application example. For example, the annealing machine 20 may be connected to the client computer 500 via a communication network such as a LAN without going through the server computer 600.

FIG. 2 is a diagram showing an example of the spin value of the annealing machine 20 acquired by the system 10 according to the present embodiment. The system 10 sets the interaction between the plurality of spins corresponding to a predetermined problem in the annealing machine 20, and controls the annealing machine 20 to calculate the low energy state of the plurality of spins. The result is obtained from the annealing machine 20. In this example, for the sake of simplicity, the results of calculating the low energy state 6 times for 6 spins are shown, but the number of spins and the number of times the low energy state is calculated are arbitrary.

In this example, the value of the first spin is 1 and the value of the 2nd to 6th spins is 0 in the first calculation. Further, in the second calculation, the values of the first to sixth spins are 0. Further, in the fourth calculation, the values of the first to fourth spins are 0, the values of the fifth spins are 1, and the values of the sixth spins are 0. Here, the Hamming distance between the spin sequence in the first calculation and the spin sequence in the second calculation is 1, and the spin sequence in the first calculation and the spin sequence in the fourth calculation The Hamming distance is 1.

Further, in this example, in the third calculation, the values of the first to sixth spins are 1, and in the fifth calculation, the values of the first to third spins are 1, and the values of the fourth spins are 1. It is 0, and the value of the 5th to 6th spins is 1. Further, in the sixth calculation, the value of the first spin is 0, and the value of the second to sixth spins is 1. Here, the Hamming distance between the spin sequence in the third calculation and the spin sequence in the fifth calculation is 1, and the spin sequence in the third calculation and the spin sequence in the sixth calculation The Hamming distance is 1.

In addition, the Hamming distance between the spin train in any of the 1st, 2nd, and 4th calculations and the spin train in any of the 3rd, 5th, and 6th calculations is 4 or more. Is.

The system 10 clusters a plurality of calculation results based on the Hamming distances relating to the values of the plurality of spins in the plurality of calculation results. In the case of this example, the calculation results of the 1st, 2nd and 4th times are classified into the 1st cluster C1, and the calculation results of the 3rd, 5th and 6th times are classified into the 2nd cluster C2. To.

FIG. 3 is a diagram showing a first example of a representative value of spin calculated by the system 10 according to the present embodiment. FIG. 2 shows an example of calculating representative values of a plurality of spins for the first cluster C1 and the second cluster C2 defined in FIG.

The system 10 calculates one representative value for each one or a plurality of clusters obtained by clustering for each of the plurality of spins. For example, for the calculation results of the first, second, and fourth times included in the first cluster C1, the representative value of each spin is calculated by majority vote. That is, the system 10 calculates for each spin the value with the highest number of observations as a representative value.

The method for calculating the representative value is not limited to the above method, and the system 10 may calculate a value that occupies a predetermined ratio or more with respect to the plurality of calculation results for each of the plurality of spins as the representative value. Here, the predetermined ratio is, for example, 60%. In other words, the system 10 calculates the average value for a plurality of calculation results for each spin, and if the average value is equal to or higher than the upper threshold value (for example, 0.6), the representative value is set to 1, and the average value is the lower threshold value (for example, 0.6). If it is 0.4) or less, the representative value may be 0.

By the calculation of the representative value by the system 10, the representative value of the spin train with respect to the first cluster C1 becomes 0000000, and the representative value of the spin train with respect to the second cluster C2 becomes 111111. As described above, the representative value of the calculated spin sequence does not necessarily have to be the spin sequence included in the original cluster. The system 10 calculates the energy of a plurality of spins based on the representative value for each one or a plurality of clusters, and estimates the value of the plurality of spins having the lowest energy as the solution of a predetermined problem. In the case of this example, the system 10 calculates the energy when the values of the 1st to 6th spins are 0000000 and the energy when the values of the 1st to 6th spins are 111111, and the energy becomes the lowest. Estimate the values of multiple spins as the solution to a given problem. The energy of a plurality of spins is calculated by substituting a representative value into the Hamiltonian of the plurality of spins.

As described above, the system 10 according to the present embodiment can obtain a spin value with reduced measurement error by calculating a representative value for each of the plurality of spins, and can solve a predetermined problem with higher accuracy. It can be estimated well. Further, even when a plurality of calculation results include not only the ground state but also the excited state, the system 10 separates and measures the calculation results corresponding to different energy levels by clustering the plurality of calculation results. It is possible to obtain a spin value closer to the ground state while reducing the error.

FIG. 4 is a diagram showing a second example of a representative value of spin calculated by the system 10 according to the present embodiment. In this example, the Hamming distance between the spin sequence in the first calculation and the spin sequence in the second calculation is 1, and the spin sequence in the first calculation and the spin sequence in the third calculation The Hamming distance of is 1 and the Hamming distance between the spin sequence in the second calculation and the spin sequence in the fourth calculation is 1. Therefore, when clustering a plurality of calculation results based on the Hamming distance, the calculation results of the first to fourth times are classified into one cluster.

In the examples shown in FIGS. 2 and 3, it was possible to calculate the representative value by majority vote for the 1st to 6th spins included in each cluster, but in this example, the majority vote regarding the calculation result of 4 times for the 1st spin. The representative value cannot be calculated by. That is, as for the value of the first spin, 0 and 1 each appear at a ratio of 50%, and it is not clear which value should be adopted. As described above, when a value occupying a predetermined ratio or more with respect to a plurality of calculation results does not appear for one spin among the plurality of spins, the system 10 excludes two values of one spin and the one spin. Estimate the solution of a given problem based on the representative values of multiple spins.

In the system 10, the value of the first spin is 1, the value of the 2nd to 6th spins is the representative value by majority vote, the first representative value (101110), and the value of the first spin is 0, and the 2nd to 6th spins are set to 0. The energy is calculated for each of the second representative value (001110) in which the spin value is the representative value by majority voting, and the values of the plurality of spins having the lowest energy are estimated as the solution of the predetermined problem.

As described above, the system 10 according to the present embodiment can obtain a spin value closer to the ground state even when the representative value cannot be calculated by majority voting for any one of the plurality of spins. ..

FIG. 5 is a diagram showing a third example of a representative value of spin calculated by the system 10 according to the present embodiment. In this example, the Hamming distance between the spin sequence in the first calculation and the spin sequence in the third calculation is 2, and the spin sequence in the first calculation and the spin sequence in the fourth calculation The Hamming distance of is 2 and the Hamming distance between the spin sequence in the second calculation and the spin sequence in the fourth calculation is 2. Therefore, when clustering a plurality of calculation results based on the Hamming distance, the calculation results of the first to fourth times are classified into one cluster.

In the examples shown in FIGS. 2 and 3, it was possible to calculate the representative value by majority vote for the 1st to 6th spins included in each cluster, but in this example, 4 times for the 1st spin and the 2nd spin. The representative value cannot be calculated by majority vote on the calculation result. That is, as for the values of the first spin and the second spin, 0 and 1 appear at a ratio of 50%, respectively, and it is not clear which value should be adopted. As described above, when a value occupying a predetermined ratio or more with respect to a plurality of calculation results does not appear for one or more spins among the plurality of spins, the system 10 is based on the Hamming distance for the value of the one or more spins. Then, the values of one or more spins are clustered, and the representative value of one or more spins is calculated for each one or a plurality of clusters obtained by the clustering. Then, the solution of a predetermined problem is estimated based on the representative value of one or more spins and the representative value of a plurality of spins excluding the one or more spins. In this way, for one or more spins for which the representative value cannot be calculated by majority voting, clustering is performed recursively and the representative value of the cluster is calculated.

The system 10 clusters the first spin and the second spin for which the representative value cannot be calculated by majority voting. In the case of this example, the pattern "10" appears at a rate of 50%, and the pattern "01" appears at a pattern of 50%. Therefore, the system 10 has two types of patterns, "10" and "01". Is calculated as a representative value of a cluster of values of the first spin and the second spin.

In the system 10, the representative value of the clusters of the first spin and the second spin is "10", and the values of the third to sixth spins are the representative values by majority decision, respectively, and the first representative value (101110), the first spin, and the first spin. The energy is calculated for each of the second representative value (011110) in which the representative value of the cluster of the second spin is "01" and the values of the third to sixth spins are the representative values by majority decision, and the energy becomes the lowest. Estimate the values of multiple spins as the solution to a given problem.

As described above, the system 10 according to the present embodiment can obtain a spin value closer to the ground state even when the representative value cannot be calculated by majority voting for one or more spins among the plurality of spins. can.

<Example of configuration>
FIG. 6 is a block diagram showing a client computer 500 according to an embodiment. The client computer 500 is typically one for interconnecting one or more processing units (CPUs) 502, one or more networks or other communication interfaces 508, memory 504, and components thereof. Alternatively, it includes a plurality of communication buses 514.

The client computer 500 may also include a user interface 506 comprising a display device 510 and a keyboard and / or mouse (or any other pointing device) 512.

The memory 504 is a high speed random access memory such as, for example, DRAM, SRAM, DDR RAM or other random access solid-state storage, and is also one or more magnetic disk storage devices, optical disk storage devices, flash memory devices, or It may be a non-volatile memory such as another non-volatile solid-state storage device.

Further, as another example of the memory 504, one or a plurality of storage devices installed remotely from the CPU 502 may be used. In certain embodiments, memory 504 stores the following programs, modules and data structures, or subsets thereof.

The operating system 516 includes, for example, procedures for processing various basic system services and performing tasks using hardware.

The network communication module 518, for example, connects the client computer 500 to another computer, one or more communication network interfaces 508, and one or more communications such as the Internet, other wide area networks, local area networks, metropolitan area networks, and the like. Used to connect over the network.

The annealing machine control module 520 receives, for example, input of information for setting a plurality of spins of the annealing machine 20 and a Hamiltonian of the spins by a keyboard and / or a mouse 512, and transmits the input to the server computer 600. The annealing machine control module 520 obtains a plurality of calculation results obtained by controlling the annealing machine 20 so as to calculate low energy states of a plurality of spins from the annealing machine 20 via the server computer 600, or a server computer. Obtained directly from the annealing machine 20 without going through the 600.

The calculation module 522 calculates one representative value from a plurality of calculation results by the annealing machine 20 for each of the plurality of spins. The calculation module 522 clusters a plurality of calculation results based on the Hamming distances related to the values of the plurality of spins in the plurality of calculation results, and for each of the plurality of spins, for each one or a plurality of clusters obtained by the clustering. Calculate one representative value.

The estimation module 524 estimates the solution of a predetermined problem based on the representative values of each of the plurality of spins. The estimation module 524 calculates, for example, the energies of a plurality of spins based on the representative values for each one or a plurality of clusters obtained by the calculation module 522, and the values of the plurality of spins having the lowest energy are used to solve a predetermined problem. I presume.

The client application 530 includes, for example, a web browser.

The one or more processing devices (CPUs) 502 read each module from the memory 504 as needed and execute it. For example, one or more processing devices (CPUs) 502 may configure a communication unit by executing the network communication module 518 stored in the memory 504. Further, the one or more processing devices (CPUs) 502 may configure the annealing machine control unit by executing the annealing machine control module 520 stored in the memory 504, or execute the calculation module 522. By doing so, the calculation unit may be configured, or by executing the estimation module 524, the estimation unit may be configured. Here, the annealing machine control unit, the calculation unit, and the estimation unit may be configured inside the CPU 502.

In another embodiment, the annealing machine control module 520, the calculation module 522, and the estimation module 524 may be a stand-alone application stored in the memory 504 of the client computer 500. Stand-alone applications include, but are not limited to, annealing machine control applications, calculation applications, and estimation applications. In yet another embodiment, the annealing machine control module 520, the calculation module 522 and the estimation module 524 may be add-ons or plug-ins to other applications. For example, the annealing machine control module 520 may be a plug-in to a web browser application or an email application.

In certain embodiments, received data items may be cached locally in memory 504. Similarly, information about the low energy state of spins obtained by the annealing machine 20 may be locally cached in memory 504.

Each of the elements shown above may be stored in one or more of the aforementioned storage devices. Each of the modules shown above corresponds to a set of instructions for performing the functions described above. The modules or programs shown above (ie, sets of instructions) need not be implemented as separate software programs, procedures or modules, so various subsets of these modules may be combined or combined in various embodiments. Alternatively, it may be reconstructed. In certain embodiments, memory 504 may store a subset of the modules and data structures shown above. Furthermore, memory 504 may store additional modules and data structures not described above.

FIG. 7 is a block diagram showing a server computer 600 according to an embodiment. The server computer 600 is typically one for interconnecting one or more processing units (CPUs) 602, one or more networks or other communication interfaces 608, memory 604, and components thereof. Alternatively, it includes a plurality of communication buses 610.

The server system 600 may optionally include a user interface 606, which may include a display device (not shown) and a keyboard and / or mouse (not shown).

The memory 604 is a high speed random access memory such as, for example, DRAM, SRAM, DDR RAM or other random access solid-state storage, and is also one or more magnetic disk storage devices, optical disk storage devices, flash memory devices, or It may be a non-volatile memory such as another non-volatile solid-state storage device.

Further, another example of the memory 604 may be one or a plurality of storage devices installed remotely from the CPU 602. In certain embodiments, memory 604 stores the following programs, modules and data structures, or subsets thereof.

The operating system 612 includes, for example, procedures for processing various basic system services and performing tasks using hardware.

The network communication module 614, for example, connects the server system 600 to another computer, one or more communication network interfaces 606 and one or more communication networks such as the Internet, other wide area networks, local area networks, metropolitan area networks, and the like. Used to connect via.

The annealing machine control module 616 receives, for example, information for setting a plurality of spins of the annealing machine 20 and Hamiltonians of the spins from the client computer 500, and controls the annealing machine 20. The annealing machine control module 616 acquires a plurality of calculation results obtained by controlling the annealing machine 20 so as to calculate low energy states of a plurality of spins from the annealing machine 20.

The calculation module 618 calculates one representative value from a plurality of calculation results by the annealing machine 20 for each of the plurality of spins. The calculation module 618 clusters a plurality of calculation results based on the Hamming distances related to the values of the plurality of spins in the plurality of calculation results, and for each of the plurality of spins, for each one or a plurality of clusters obtained by the clustering. Calculate one representative value.

The estimation module 620 estimates the solution of a predetermined problem based on the representative values of each of the plurality of spins. The estimation module 620 calculates the energies of a plurality of spins based on the representative values for each one or a plurality of clusters obtained by the calculation module 618, and determines the values of the plurality of spins having the lowest energy to solve a predetermined problem. I presume.

Each of the elements shown above may be stored in one or more of the storage devices described above. Each of the modules shown above corresponds to a set of instructions for performing the functions described above. The modules or programs shown above (ie, sets of instructions) need not be implemented as separate software programs, procedures or modules, and thus various subsets of these modules are combined or combined in various embodiments. Alternatively, it can be reconstructed. In certain embodiments, memory 604 may store a subset of the modules and data structures shown above. Furthermore, memory 604 may store additional modules and data structures not described above.

FIG. 7 shows a "server computer", although FIG. 7 is intended to describe various features that may be present in a set of servers, rather than as a structural outline of the embodiments described herein. There is. In practice, and as will be appreciated by those skilled in the art, items shown separately could be combined and some items could be separated. For example, the items shown separately in FIG. 7 could be implemented on a single server, and a single item could be implemented by one or more servers.

<Operation explanation>
Next, the operation of the system 10 according to the present embodiment will be described. 8 and 9 are flowcharts showing an example of the processing of the system 10 according to the present embodiment. In the example shown in FIG. 8, in step S15, the system 10 estimates a solution to a predetermined problem based on the low energy state determined by the annealing machine 20.

(Step S10)
The system 10 first sets the annealing machine 20 to interact between a plurality of spins corresponding to a given problem.

(Step S11)
The system 10 controls the annealing machine 20 to calculate the low energy states of the plurality of spins, and acquires a plurality of calculation results obtained from the annealing machine 20.

(Step S12)
The system 10 clusters a plurality of calculation results based on the Hamming distances relating to the values of the plurality of spins in the plurality of calculation results.

(Step S13)
After that, the system 10 executes the process shown in FIG. 9 when a value occupying a predetermined ratio or more with respect to the plurality of calculation results does not appear for one or more spins among the plurality of spins. On the other hand, when a value occupying a predetermined ratio or more with respect to the plurality of calculation results appears for all of the plurality of spins, the system 10 executes the processes of steps S14 and S15.

(Step S14)
After that, the system 10 calculates one representative value for each one or a plurality of clusters obtained by clustering for each of the plurality of spins.

(Step S15)
Finally, the system 10 calculates the energies of the plurality of spins for each one or a plurality of clusters based on the representative values, and estimates the values of the plurality of spins having the lowest energy as the solution to the predetermined problem.

As a result, the system 10 according to the present embodiment can reduce the measurement error by calculating the representative value for each of the plurality of spins, and can estimate the solution of a predetermined problem more accurately.

(Step S20)
When a value occupying a predetermined ratio or more does not appear for a plurality of calculation results, it is considered that a group of spins to be decomposed into two or more clusters is classified into one cluster in step S12. Therefore, the system 10 recursively performs clustering for one or more spins in which a value occupying a predetermined ratio or more does not appear in the plurality of calculation results.

(Step S21)
Further, the system 10 calculates a representative value for each one or a plurality of clusters calculated for one or more spins in which a value occupying a predetermined ratio or more does not appear in the plurality of calculation results.

(Step S22)
The system 10 then estimates a solution to a given problem based on the representative values of one or more spins and the representative values of the plurality of spins excluding the one or more spins.

As a result, the system 10 according to the present embodiment reduces the measurement error for each of the plurality of spins even when the value occupying a predetermined ratio or more with respect to the plurality of calculation results does not appear for one or more spins. The representative value can be calculated as described above, and the solution of a predetermined problem can be estimated more accurately.

The disclosed technique is not limited to each of the above-described embodiments, and can be implemented in various other forms within a range that does not deviate from the gist of the disclosed technique. For this reason, each of the above embodiments is merely an example in all respects and is not to be construed in a limited manner. For example, the above-mentioned processing steps can be arbitrarily changed in order or executed in parallel within a range that does not cause a contradiction in the processing contents.

The program of the embodiment of the present disclosure may be provided stored in a computer-readable storage medium. The storage medium can store the program in a "non-temporary tangible medium". Programs include, but are not limited to, software programs and computer programs as examples.

10 ... System, 20 ... Interface machine, 21a ... 1st spin, 21b ... 2nd spin, 21c ... 3rd spin, 22a ... 1st auxiliary spin, 22b ... 2nd auxiliary spin, 22c ... 3rd auxiliary spin, 500 ... Client computer, 502 ... CPU, 504 ... Memory, 506 ... User interface, 508 ... Network communication interface, 510 ... Display, 512 ... Keyboard / mouse, 514 ... Communication bus, 516 ... Operating system, 518 ... Network communication module, 520 ... Annealing machine control module, 522 ... calculation module, 524 ... estimation module, 530 ... client application, 600 ... server computer, 602 ... CPU, 604 ... memory, 606 ... user interface, 608 ... network communication interface, 610 ... communication bus, 612. ... operating system, 614 ... network communication module, 616 ... annealing machine control module, 618 ... calculation module, 620 ... estimation module

Claims (8)

It ’s a system,
Includes one or more processors
The one or more processors
Set the interaction between multiple spins corresponding to a given problem on the annealing machine and
A plurality of calculation results obtained by controlling the annealing machine so as to calculate the low energy states of the plurality of spins are obtained from the annealing machine.
For each of the plurality of spins, one representative value is calculated from the plurality of calculation results.
Estimate the solution of the predetermined problem based on the representative value of each of the plurality of spins.
The system that performs the process. The plurality of calculation results are clustered based on the Hamming distances related to the values of the plurality of spins in the plurality of calculation results.
To calculate the representative value
Including calculating one representative value for each one or a plurality of clusters obtained by the clustering.
The above estimation is
Including estimating the predetermined solution based on one representative value for each of the one or more clusters.
The system according to claim 1. The above estimation is
It includes calculating the energy of the plurality of spins based on the representative value for each of the one or a plurality of clusters, and estimating the value of the plurality of spins having the lowest energy as the solution of the predetermined problem.
The system according to claim 2. To calculate the representative value
For each of the plurality of spins, a value that occupies a predetermined ratio or more with respect to the plurality of calculation results is calculated as the representative value.
The system according to any one of claims 1 to 3. The above estimation is
If a value that occupies a predetermined ratio or more with respect to the plurality of calculation results does not appear for one or more of the plurality of spins, the one or more is based on the Hamming distance for the value of the one or more spins. The spin values of the above are clustered, the representative value of the one or more spins is calculated for each one or a plurality of clusters obtained by the clustering, and the representative value of the one or more spins and the one or more of the above. Including estimating the solution of the predetermined problem based on the representative values of the plurality of spins excluding the spins.
The system according to claim 4. If a value that occupies a predetermined ratio or more with respect to the plurality of calculation results does not appear for one or more of the plurality of spins, the one or more is based on the Hamming distance for the value of the one or more spins. The spin values of the above are recursively clustered, the representative value of the one or more spins is calculated for each one or a plurality of clusters obtained by the clustering, and the representative value of the one or more spins and the above 1 are obtained. Including estimating the solution of the predetermined problem based on the representative values of the plurality of spins excluding one or more spins.
The system according to claim 5. An information processing method performed by a system that includes one or more processors.
Previous term One or more processors
The interaction between multiple spins corresponding to a given problem is set in the annealing machine and
A plurality of calculation results obtained by controlling the annealing machine so as to calculate the low energy states of the plurality of spins are obtained from the annealing machine.
For each of the plurality of spins, one representative value is calculated from the plurality of calculation results.
Estimate the solution of the predetermined problem based on the representative value of each of the plurality of spins.
An information processing method that executes processing. To one or more processors included in the system
The interaction between multiple spins corresponding to a given problem is set in the annealing machine and
A plurality of calculation results obtained by controlling the annealing machine so as to calculate the low energy states of the plurality of spins are obtained from the annealing machine.
For each of the plurality of spins, one representative value is calculated from the plurality of calculation results.
Estimate the solution of the predetermined problem based on the representative value of each of the plurality of spins.
A program that executes processing.

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