Information processing device, information processing system, program, and method for assisting with creation of ising model

Abstract

An information processing device for assisting in the creation of an Ising model for causing an annealing-type optimization machine to solve the problem of searching for an optimal solution for a composite material having a compounding constraint condition, the information processing device characterized by comprising: an input reception unit that receives an input of the compounding constraint condition and an objective function in which the characteristics of the composite material have been formulated according to the compounding; and a data creation unit that creates an Ising model that causes the annealing-type optimization machine to solve the optimal solution for a compounding that satisfies a constraint conditional expression in which the compounding constraint condition is formulated and in which the characteristics are optimized, wherein with regard to substances to be mixed into the composite material, an amount ri of a substance i is represented by bits, and whether the substance i is included in the composite material is represented by a bit, the constraint conditional expression includes a condition satisfying expressions (1) and (2), and the constraint conditional expression is formulated so as not to be calculated as an optimal solution of the compounding if at least one of expressions (1) and (2) is not satisfied.

Description

Information processing device, information processing system, program, and Ising model creation support method

[0001] The present disclosure relates to an information processing device, an information processing system, a program, and an Ising model creation support method.

[0002] Conventionally, a technique has been known in which stable combinations of the A site, B site, and anion site in a perovskite crystal structure are calculated at high speed even when there are a huge number of combinations, by performing a ground state search using a simulated annealing method using an Ising model or QUBO (Quadratic Unconstrained Binary Optimization) (see, for example, Patent Document 1).

[0003] Japanese Patent Application Laid-Open No. 2021-033768

[0004] For example, there are problems in which the optimal combination is selected from various combinations of compounds, such as searching for the composition of a composite material with optimal properties. Annealing-type optimization machines can solve problems in which the optimal combination is formulated using the Ising model.

[0005] Furthermore, when selecting the optimal combination from various combinations, such as when searching for the composition of a composite material with optimal properties, constraints on the combination are often imposed. For example, if there are combinations of materials that are incompatible, conditions on the combination of materials are imposed as constraints on the combination. In the Ising model, constraints on the combination can be imposed as constraints.

[0006] In the Ising model, constraints (penalty functions) have the role of preventing combinations that do not satisfy the combination constraints from being selected as optimal combinations. However, the constraints must be expressed in Ising-type mathematical expressions (constraint terms), but it has not been easy to express the combination constraints in terms of constraint terms.

[0007] An object of the present disclosure is to provide an information processing device, an information processing system, a program, and an Ising model creation support method that can support the creation of an Ising model for having an annealing-type optimization machine solve an optimal solution search problem for a composite material that has formulation constraints.

[0008] The present disclosure has the following configuration.

[0009] [1] An information processing device that supports the creation of an Ising model for causing an annealing optimization machine to solve an optimal solution search problem for a composite material having a blending constraint condition, comprising: an input receiving unit configured to receive input of an objective function that formulates the properties of the composite material according to the blending and the blending constraint condition; and a data creating unit configured to create an Ising model for causing the annealing optimization machine to solve the optimal blending solution that satisfies the constraint condition formula that formulates the blending constraint condition and optimizes the properties, wherein a substance to be mixed into the composite material is a substance i in an amount r ｉ is expressed in bit notation, and whether or not the substance i is included in the composite material is expressed in bit notation, and the constraint condition formula includes a condition that satisfies the following formula (1) and formula (2):

[0010] The q Ａ０ is an auxiliary variable that is "0" when substance A is contained in the composite material and is "1" when substance A is not contained in the composite material, and Ｂ０ is an auxiliary variable that is "0" when substance B is contained in the composite material and is "1" when substance B is not contained in the composite material, Ｂ is the amount r of substance B mixed into the composite material Ｂ is the number of bits required to represent q Ｂｊ is a number "0" or "1" in binary representation of the blend of substance B, and the constraint condition equation is formulated so that the blend is not calculated as an optimal solution if at least one of equations (1) and (2) is not satisfied.

[0011] [2] The constraint equation further includes a condition that satisfies the following equations (3) and (4):

[0012] The q Ａ０ is an auxiliary variable that is "0" when substance A is contained in the composite material and is "1" when substance A is not contained in the composite material, and Ｂ０ is an auxiliary variable that is "0" when substance B is contained in the composite material and is "1" when substance B is not contained in the composite material, Ａ is the amount r of substance A mixed into the composite material Ａ is the number of bits required to represent q Ａｊ is a number "0" or "1" in binary representation of the blend of substance A, and the constraint condition equation is formulated so that the blend is not calculated as an optimal solution if at least one of equations (3) and (4) is not satisfied.

[0013] [3] When the condition regarding the amount of the substance to be mixed into the composite material is set by a continuous number, the substance to be mixed into the composite material is determined by the amount r of substance i. ｉ is expressed in bit notation in the following formula (5), and whether or not the substance i is included in the composite material is expressed in bit notation,

[0014] The q ｉｊ is a binary representation of the composition of substance i, which is a number of "0" or "1", j is the coefficient of the binary representation of the composition of material i, １ is the amount of the smallest unit of the substance to be mixed, ｉ is C ｍ <M ｉ，ＭＡＸ The largest natural number M ｉ，ＭＡＸ is the amount r of substance i ｉ The information processing device according to [1] or [2], wherein the maximum amount is

[0015] [4] When the conditions regarding the amounts of the substances to be mixed into the composite material are set as discrete numbers, the amount r of substance i isｉ is expressed in bit notation, and whether or not the substance i is included in the composite material is expressed in bit notation.

[0016] [5] The information processing device according to any one of [1] to [4], wherein the formulas (1) and (2) are conditions of the composition constraint that when substance A is used, substance B is not used.

[0017] [6] The information processing device according to [2], wherein the formulas (3) and (4) are conditions of the composition constraint that substance A is not used when substance B is used.

[0018] [7] An information processing system having an annealing optimization machine and an information processing device that supports the creation of an Ising model for causing the annealing optimization machine to solve an optimal solution search problem for a composite material with a blending constraint condition, wherein the information processing system has an input receiving unit configured to receive input of an objective function that formulates the properties of the composite material according to the blend and the blending constraint condition, and a data creating unit configured to create an Ising model for causing the annealing optimization machine to solve the optimal solution for the blend that satisfies the constraint condition formula that formulates the blending constraint condition and optimizes the properties, wherein a substance to be mixed into the composite material is a substance i in an amount r ｉ is expressed in bit notation, and whether or not the substance i is included in the composite material is expressed in bit notation, and the constraint condition formula includes a condition that satisfies the following formula (1) and formula (2):

[0019] The q Ａ０ is an auxiliary variable that is "0" when substance A is contained in the composite material and is "1" when substance A is not contained in the composite material, and Ｂ０ is an auxiliary variable that is "0" when substance B is contained in the composite material and is "1" when substance B is not contained in the composite material, Ｂ is the amount r of substance B mixed into the composite material Ｂ is the number of bits required to represent q Ｂｊis a number "0" or "1" in binary representation of the blend of substance B, and the constraint condition equation is formulated so that the blend is not calculated as an optimal solution if at least one of equations (1) and (2) is not satisfied.

[0020] [8] An information processing device that supports the creation of an Ising model for causing an annealing optimization machine to solve an optimal solution search problem for a composite material with a blending constraint condition is caused to execute the following steps: receiving an objective function that formulates the properties of the composite material according to the blending and an input of the blending constraint condition; and creating an Ising model for causing the annealing optimization machine to solve the optimal solution for the blending that satisfies the constraint condition formula that formulates the blending constraint condition and optimizes the properties; and ｉ is expressed in bit notation, and whether or not the substance i is included in the composite material is expressed in bit notation, and the constraint condition formula includes a condition that satisfies the following formula (1) and formula (2):

[0021] The q Ａ０ is an auxiliary variable that is "0" when substance A is contained in the composite material and is "1" when substance A is not contained in the composite material, and Ｂ０ is an auxiliary variable that is "0" when substance B is contained in the composite material and is "1" when substance B is not contained in the composite material, Ｂ is the amount r of substance B mixed into the composite material Ｂ is the number of bits required to represent q Ｂｊ is a number "0" or "1" in binary representation of the blend of substance B, and the constraint condition equation is formulated so that the blend is not calculated as an optimal solution if at least one of equations (1) and (2) is not satisfied.

[0022] [9] An Ising model creation support method for an information processing device that supports creation of an Ising model for causing an annealing optimization machine to solve an optimal solution search problem for a composite material having a blending constraint condition, comprising: receiving an input of an objective function that formulates the properties of the composite material according to the blending and the blending constraint condition; and creating an Ising model for causing the annealing optimization machine to solve the optimal blending solution that satisfies the constraint condition formula that formulates the blending constraint condition and optimizes the properties; and ｉ is expressed in bit notation, and whether or not the substance i is included in the composite material is expressed in bit notation, and the constraint condition formula includes a condition that satisfies the following formula (1) and formula (2):

[0023] The q Ａ０ is an auxiliary variable that is "0" when substance A is contained in the composite material and is "1" when substance A is not contained in the composite material, and Ｂ０ is an auxiliary variable that is "0" when substance B is contained in the composite material and is "1" when substance B is not contained in the composite material, Ｂ is the amount r of substance B mixed into the composite material Ｂ is the number of bits required to represent q Ｂｊ is a number "0" or "1" in binary representation of the composition of substance B, and the constraint condition equation is formulated so that the composition is not calculated as an optimal solution when at least one of equations (1) and (2) is not satisfied.

[0024]

[10] An information processing device that supports the creation of an Ising model for causing an annealing optimization machine to solve an optimal solution search problem for a composite material having a blending constraint condition, the information processing device comprising: an input receiving unit configured to receive input of an objective function that formulates the properties of the composite material according to the blending and the blending constraint condition; and a data creating unit configured to create an Ising model for causing the annealing optimization machine to solve the optimal blending solution that satisfies the constraint condition formula that formulates the blending constraint condition and optimizes the properties, wherein a substance to be mixed into the composite material is a substance i in an amount r ｉ is expressed in bit notation, and whether or not the substance i is included in the composite material is expressed in bit notation, and the constraint condition formula includes conditions that satisfy the following formulas (6), (7), and (8):

[0025] The q ｉ０ is an auxiliary variable that is "0" when the substance i is contained in the composite material and is "1" when the substance i is not contained in the composite material, ｉ is the amount r of substance i mixed into the composite material ｉ is the number of bits required to represent q ｉｊ is a number "0" or "1" in binary representation of the composition of substance i, N is the number of substances i to which a constraint is imposed by equation (8), and the constraint equation is formulated so that the composition is not calculated as an optimal solution when at least one of equations (6), (7), and (8) is not satisfied.

[0026] According to the present disclosure, it is possible to provide an information processing device, an information processing system, a program, and an Ising model creation support method that can support the creation of an Ising model for having an annealing-type optimization machine solve an optimal solution search problem for a composite material that has formulation constraints.

[0027] 1 is a configuration diagram of an example of an information processing system according to the present embodiment. FIG. 2 is a hardware configuration diagram of an example of a computer according to the present embodiment. FIG. 3 is an explanatory diagram of an example of a formulation constraint condition. FIG. 4 is an explanatory diagram of an example of a formulation constraint condition. FIG. 5 is a configuration diagram of an example of an information processing system according to the present embodiment. FIG. 6 is a diagram explaining an example of a bit notation of a substance. FIG. 7 is a diagram explaining a specific example of the bit notation of "substance 1". FIG. 8 is a diagram explaining a specific example of the bit notation of "substance 1". FIG. 9 is a diagram explaining a specific example of the bit notation of "substance 1". FIG. 10 is a diagram explaining an example of the bit notation of a substance. FIG. 11 is a diagram explaining an example of the bit notation of the composition of a composite material. FIG. 12 is an explanatory diagram of an example of the constraint conditions shown in formulas (12) and (13). FIG. 13 is an explanatory diagram of an example of the constraint conditions shown in formulas (14) and (15). FIG. 14 is an explanatory diagram of an example of the constraint conditions shown in formulas (14) and (15). FIG. 15 is an explanatory diagram of an example of the use of the constraint conditions shown in formulas (14) and (15). FIG. 1 is a diagram for explaining an example of using the constraints shown in formulas (14) and (15). FIG. 2 is a diagram for explaining an example of using the constraints shown in formulas (14) and (15). FIG. 3 is a diagram for explaining an example of using the constraints shown in formulas (14) and (15) and formulas (16) and (17). FIG. 4 is a diagram for explaining an example of using the constraints shown in formulas (14) and (15) and formulas (16) and (17). FIG. 5 is a flowchart showing an example of the processing procedure of the information processing system according to this embodiment. FIG. 6 is a diagram for explaining an example of using the constraints shown in formula (18). FIG. 7 is a diagram for explaining an example of using the constraints shown in formula (18).

[0028] Next, an embodiment of the present invention will be described in detail, but the present invention is not limited to the following embodiment.

[0029] <System Configuration> Fig. 1 is a configuration diagram of an example of an information processing system according to this embodiment. The information processing system 1 shown in Fig. 1 has an annealing-type optimization machine 10 and an information processing device 12. The annealing-type optimization machine 10 and the information processing device 12 are connected to each other so as to be able to communicate data via a communication network 18 such as a local area network (LAN) or the Internet.

[0030] The annealing optimization machine 10 is an example of a device that uses an Ising model to solve an optimal solution search problem (optimization problem). An optimization problem is a problem of finding a solution that minimizes or maximizes an objective function among solutions that satisfy constraints. In an optimization problem, the solution to be found is expressed using decision variables. The objective function is a function in which the value to be minimized or maximized is expressed using decision variables. Constraints are relational expressions that express requirements that must be satisfied using decision variables.

[0031] A combinatorial optimization problem is an optimization problem with a combinatorial structure, which is a problem of finding a combination of decision variables that minimizes or maximizes an objective function among combinations of decision variables that satisfy constraints.

[0032] The annealing optimization machine 10 may be realized by a quantum computer using a quantum annealing method, or may be realized by an Ising machine (annealing machine) in which the quantum annealing method is realized by a digital circuit such as an FPGA (Field Programmable Gate Array) or a GPU (Graphics Processing Unit). The annealing optimization machine 10 may be realized by, for example, Digital Annealer (registered trademark), which is an example of an Ising machine.

[0033] The annealing optimization machine 10 solves an optimization problem reduced to an Ising model by the convergence operation of the Ising model. The Ising model can also be expressed using QUBO. The energy function of the Ising model and the cost function of QUBO are equivalent through variable transformation.

[0034] The Ising model is a statistical mechanical model that represents the behavior of magnetic materials. The Ising model has the property that the spin state is updated so that the energy (Hamiltonian) is minimized due to the interaction between spins of the magnetic material, and the energy is ultimately minimized. The annealing-type optimization machine 10 reduces the optimization problem to the Ising model, finds the state that minimizes the energy, and solves that state as the optimal solution to the optimization problem.

[0035] The information processing device 12 is a device operated by a user, such as a PC, a tablet terminal, or a smartphone. The information processing device 12 assists a user who wants the annealing-type optimization machine 10 to solve an optimization problem in creating an Ising model for the annealing-type optimization machine 10 to solve the optimization problem, as will be described later.

[0036] Furthermore, the information processing device 12 creates input information for the annealing-type optimization machine 10 based on a user operation, which is input to the annealing-type optimization machine 10 in order to solve the optimization problem. The input information to be input to the annealing-type optimization machine 10 includes an objective function and constraint conditions written in an Ising format created as described below.

[0037] By inputting input information for the annealing optimization machine 10 into the annealing optimization machine 10, the user can make the annealing optimization machine 10 solve the optimization problem reduced to an Ising model.

[0038] In this way, the information processing device 12 supports the user in creating an Ising model for causing the annealing-type optimization machine 10 to solve the optimization problem. The information processing device 12 also receives the optimal solution of the optimization problem solved by the annealing-type optimization machine 10, and outputs the optimal solution so that the user can confirm it, for example by displaying it on a display device.

[0039] Note that the information processing system 1 in FIG. 1 is just one example, and the information processing system 1 may be configured such that a user accesses and uses the information processing device 12 from a user terminal (not shown) connected to the information processing device 12 via a communication network 18.

[0040] The annealing-type optimization machine 10 may also be realized as a cloud computing service. For example, the annealing-type optimization machine 10 may be available by calling an API (Application Programming Interface) via a communication network 18.

[0041] Furthermore, the annealing-type optimization machine 10 is not limited to being realized as a cloud computing service, but may be realized on-premise or operated by another company. The annealing-type optimization machine 10 may also be realized by multiple computers.

[0042] In addition, in a form in which a user accesses and uses the information processing device 12, the information processing device 12 may be realized as a cloud computing service, may be realized on-premise, may be operated by another company, or may be realized by multiple computers. It goes without saying that there are various system configuration examples for the information processing system 1 in Figure 1 depending on the use and purpose.

[0043] <Hardware Configuration> The information processing apparatus 12 in FIG. 1 is realized by, for example, a computer 500 having the hardware configuration shown in FIG.

[0044] Fig. 2 is a diagram showing an example of the hardware configuration of a computer according to this embodiment. The computer 500 in Fig. 2 includes an input device 501, a display device 502, an external I / F 503, a RAM 504, a ROM 505, a CPU 506, a communication I / F 507, and an HDD 508, all of which are interconnected by a bus B. The input device 501 and the display device 502 may be connected to each other for use.

[0045] The input device 501 includes a touch panel, operation keys, buttons, a keyboard, a mouse, etc., which are used by the user to input various signals. The display device 502 includes a display such as a liquid crystal or organic EL display for displaying a screen, a speaker for outputting audio data such as voice and sound, etc. The communication I / F 507 is an interface for the computer 500 to perform data communication.

[0046] The HDD 508 is an example of a non-volatile storage device that stores programs and data. The stored programs and data include an OS, which is basic software that controls the entire computer 500, and applications that provide various functions on the OS. Note that the computer 500 may use a drive device that uses flash memory as a storage medium (e.g., a solid-state drive (SSD)) instead of the HDD 508.

[0047] The external I / F 503 is an interface with an external device. The external device may be a recording medium 503a. This allows the computer 500 to read and / or write data from and to the recording medium 503a via the external I / F 503. The recording medium 503a may be a flexible disk, a CD, a DVD, an SD memory card, a USB memory, or the like.

[0048] The ROM 505 is an example of a non-volatile semiconductor memory (storage device) that can retain programs and data even when the power is turned off. The ROM 505 stores programs and data such as the BIOS, OS settings, and network settings that are executed when the computer 500 starts up. The RAM 504 is an example of a volatile semiconductor memory (storage device) that temporarily retains programs and data.

[0049] The CPU 506 is a computing device that reads programs and data from storage devices such as the ROM 505 and HDD 508 onto the RAM 504 and executes processing to realize overall control and functions of the computer 500. The information processing device 12 according to this embodiment can realize various functions as described below. Note that a description of the hardware configuration of the annealing-type optimization machine 10 will be omitted.

[0050] <Example of a problem solved as an optimization problem> Hereinafter, an example will be described in which a composition of a composite material having optimal properties is solved as a combinatorial optimization problem among compositions of composite materials that have blending constraints.

[0051] For example, in this embodiment, blending constraint conditions such as those shown in Fig. 3 are used. Fig. 3 is an explanatory diagram of an example of blending constraint conditions. A composite material is composed of multiple substance groups. Fig. 3 shows an example in which a composite material is composed of "substance group 1" and "substance group 2". Fig. 3 shows an example in which blending constraint conditions exist for each substance group that makes up the composite material.

[0052] The blending constraint conditions in Figure 3 have the following items: number of mixtures, continuous / discrete, and amount. The number of mixtures is a condition related to the number of mixtures of substances included in a substance group to be mixed into a composite material, and a minimum and maximum number of mixtures are set. The continuous / discrete condition is a condition related to the amount of substance to be mixed into a composite material, and it is set whether the amount of substance to be mixed into a composite material is a continuous number or a discrete number.

[0053] The quantity is a condition related to the amount of a substance to be mixed into the composite material, and the amount of the substance to be mixed into the composite material is set. If the amount of a substance to be mixed into the composite material is a continuous number, the minimum and maximum amounts are set as the quantity. If the amount of a substance to be mixed into the composite material is a discrete number, the amount is set as the amount of that substance.

[0054] For example, the blending constraint conditions in Figure 3 indicate that "Substance Group 1" contains five types of "Substance 1" to "Substance 5," and that from the five types of "Substance 1" to "Substance 5," one to three types of substances are to be mixed into the composite material. Also, the blending constraint conditions in Figure 3 indicate that "Substance Group 2" contains three types of "Substance 6" to "Substance 8," and that from the three types of "Substance 6" to "Substance 8," zero to two types of substances are to be mixed into the composite material.

[0055] Furthermore, in this embodiment, blending constraint conditions such as those shown in Fig. 4 are used. Fig. 4 is an explanatory diagram of an example of blending constraint conditions. Fig. 4 shows an example of conditions related to combinations of substances included in the substance group shown in Fig. 3, and when there is a combination of substances that is incompatible with each other, a combination of substances to be avoided is set. As shown in Fig. 4, the combination of substances to be avoided may be set within the same substance group, such as the combination of "Substance 1" and "Substance 4" in Fig. 3, or may be set within different substance groups, such as the combination of "Substance 1" and "Substance 6" in Fig. 3.

[0056] In this embodiment, the objective is to find an optimal solution for the compounding of materials that satisfies the compounding constraints shown in FIGS. 3 and 4 and optimizes the properties of the composite material.

[0057] <Functional Configuration> The configuration of the information processing system 1 according to this embodiment will be described. Fig. 5 is a configuration diagram of an example of the information processing system according to this embodiment. Note that in the configuration diagram of Fig. 5, portions that are not necessary for explaining this embodiment are omitted as appropriate.

[0058] 5 includes a call receiving unit 20 and an optimal solution calculation unit 22. The information processing device 12 includes an input receiving unit 30, a conversion unit 32, a data creation unit 34, a display unit 36, a substance information storage unit 50, and a constraint equation information storage unit 52.

[0059] The input receiving unit 30 is an input interface that receives user operations. The input receiving unit 30 receives, from the user, input of information necessary for causing the annealing-based optimization machine 10 to solve a combinatorial optimization problem. For example, the input receiving unit 30 receives input of an objective function that formulates the characteristics of a composite material according to the blend of substances.

[0060] The objective function is a formula of the properties of the composite material according to the material blend, and is created so that the smaller the value, the more the properties desired by the user. For example, the properties desired by the user may be high performance, low cost, etc. Furthermore, for example, the input receiving unit 30 receives input of blending constraint conditions such as those shown in FIGS. 3 and 4.

[0061] The conversion unit 32 converts the combination constraint conditions into a constraint condition formula. The constraint condition formula is an Ising-type mathematical expression that formulates the combination constraint conditions. The constraint condition formula is formulated so that it becomes "0" when the combination constraint conditions are met and becomes a large value when the combination constraint conditions are not met.

[0062] For example, the constraint equation is formulated so that it takes a large value when, for each substance group that constitutes the composite material, at least one of the conditions regarding the number of substances included in the substance group to be mixed into the composite material and the conditions regarding the amount of substance to be mixed into the composite material is not satisfied.

[0063] The equality-type constraint shown in the following equation (6) and the inequality-type constraint shown in the following equation (7) can be expressed by an Ising-type formula.

[0064] The data creation unit 34 creates an Ising model E, such as the following equation (8), from the objective function and the constraint equation to be solved by the annealing-type optimization machine 10: E=E １ +E ２ …(8) E １ is the objective function written in Ising form. ２ is a constraint equation written in Ising format. ２ The number of is determined according to the number of combination constraint conditions, and is included in the Ising model E as one or more terms (constraint terms).

[0065] Also, E １ and E ２ is an Ising type formula, it can be expressed in QUBO type as shown in the following formula (9).

[0066] The data creation unit 34 creates input information in a data format usable by the annealing-type optimization machine 10 from the above equation (8), and transmits it to the annealing-type optimization machine 10. The display unit 36 ​​displays the optimal solution received from the annealing-type optimization machine 10 on the display device 502 for the user to confirm. The optimal solution displayed on the display device 502 is displayed as information on the composition of a composite material, for example, which is easy for the user to understand.

[0067] The substance information storage unit 50 stores the properties (performance, cost, etc.) of substances included in a substance group. For example, the properties of a composite material can be expressed as the sum of values ​​obtained by multiplying the properties of the substances mixed into the composite material by the compounding ratio.

[0068] The call receiving unit 20 of the annealing-type optimization machine 10 receives a call from the information processing device 12 and receives, from the information processing device 12, input information for the annealing-type optimization machine 10 created from the above equation (8).

[0069] The optimal solution calculation unit 22 calculates the optimal solution {x ｉ} to obtain the Ising model E. ｉ} is to obtain E ２ The conditions of the composition constraints expressed by E １ This is equivalent to obtaining a composite material composition that minimizes the objective function expressed as

[0070] The optimal solution calculation unit 22 can calculate, as an optimal solution, a material combination that satisfies the constraint condition equation that formulates the combination constraint conditions and optimizes the properties of the composite material. The call receiving unit 20 transmits the optimal solution calculated by the optimal solution calculation unit 22 to the information processing device 12.

[0071] 5 is an example. Various configurations are possible for the information processing system 1 according to this embodiment. In addition, in this embodiment, an example has been described in which the input receiving unit 30 receives input of the combination constraint conditions, but it may also receive input of a formulated constraint condition expression.

[0072] <Bit representation of substances> The following bit representation for expressing the amount of each substance is necessary to express the conditions of the composition constraints in the Ising model. For example, the bit representation of substances is as shown in Figure 6.

[0073] 6 is a diagram illustrating an example of bit representation of a substance. A substance is represented by the amount r of substance i in Equation (10). ｉ is expressed in bits, and the auxiliary variable q of material i ｉ０ The bit representation indicates whether or not substance i is included in the composite material.

[0074] q ｉｊ is the binary representation of the composition of substance i, either "0" or "1". ｊ is bit q in the binary representation of the composition of material iｉｊ is the coefficient of C ０ is the significant figure of the amount of material to be mixed. ｉ is C ｍ <M ｉ，ＭＡＸ is the largest natural number such that ｉ，ＭＡＸ is the amount of substance i, r ｉ The maximum amount of M ｉ，ＭＩＮ is the amount of substance i, r ｉ is the minimum amount.

[0075] Auxiliary variable q ｉ０ is the amount of substance i, r ｉ is not 0 (substance i is included in the composite material), the amount of substance i r ｉ is 0 (substance i is not included in the composite material), it is "1".

[0076] For example, the bit representation of "Substance 1" with one significant digit after the decimal point and an amount of "2 to 10" is as shown in Figures 7A to 7C. Figures 7A to 7C are diagrams for explaining specific examples of the bit representation of "Substance 1".

[0077] Maximum amount M of "Substance 1" ｉ，ＭＡＸ is "10". Therefore, C ｍ <M ｉ，ＭＡＸ m is the largest natural number such that ｉ The number of bits that need to be reserved for "Substance 1" is the auxiliary variable n ｉ０ This adds an auxiliary bit representing the digits, making it a total of 8 bits.

[0078] For example, if the amount of "Substance 1" is "4.2", the value of the auxiliary bit is "0" because "Substance 1" is included in the composite material. The bit values ​​for "j=1 to 7" to represent the amount of "Substance 1" of "4.2" are "1" for bit "j=2" which represents the amount of "0.2", bit "j=4" which represents the amount of "0.8", and bit "j=6" which represents the amount of "3.2".

[0079] Furthermore, for example, the bit representation of a substance may be as shown in Fig. 8. Fig. 8 is a diagram for explaining an example of the bit representation of a substance. The amount r of substance i ｉ is expressed in bits in equation (11), and the auxiliary variable n ｉ０The bit representation indicates whether or not substance i is included in the composite material.

[0080] The amount of substance is "M ｉ，１ , M ｉ，２ , ..., M ｉ，Ｌ ", the quantity r of substance i is a discrete number ｉ M ｉ，Ｌ and the auxiliary variable n of material i ｉ０ The bit representation indicates whether or not substance i is included in the composite material.

[0081] By using the above bit notation to express the amount of each substance, the composition of a composite material can be expressed in bits as shown in Fig. 9. Fig. 9 is a diagram illustrating an example of bit notation of the composition of a composite material.

[0082] Figure 9 shows an example of a composite material where "Substance Group 1" contains five types of "Substance 1" to "Substance 5." "Substance 1," "Substance 2," and "Substance 5" are examples of substances whose amounts are set as continuous numbers. "Substance 3" and "Substance 4" are examples of substances whose amounts are set as discrete numbers.

[0083] The number of bits that need to be reserved for "Substance 1" to "Substance 5" depends on whether the amount of the substance to be mixed into the composite material is set as a continuous number or a discrete number, and on the amount of the substance, as described above. １ｊ ~q ５ｊ is a bit representation of the amount of "Substance 1" to "Substance 5." For example, if the minimum unit of amount is 0.1 and the maximum amount of "Substance 1" is "30," the amount of "Substance 1" is q １１ ~q １９ The quantity of "Substance 3" which has three discrete quantities, "3", "5", and "10", can be expressed in bits by q ３１ ~q ３３ can be expressed in bits by

[0084] When used in the annealing type optimization machine 10, the bit representation is the one-dimensional vector representation {x ｉBy connecting the bit representations of the substances contained in all the substance groups that make up the composite material, the composition of the composite material can be expressed as a one-dimensional vector representation {x ｉ} can be expressed as follows.

[0085] <Constraints> In this embodiment, when solving a combinatorial optimization problem to determine the compounding of materials that optimizes the properties of a composite material composed of a plurality of substance groups, the following constraints are imposed.

[0086] <Constraint 1> In this embodiment, the constraints shown in formulas (12) and (13) are imposed for each material i.

[0087] In the case of substance i, the quantity of which is set as a continuous number, m ｉ is C ｍ <M ｉ，ＭＡＸ In the case of a substance i whose quantity is set as a discrete number, m included in Equation (12) and Equation (13) is the largest natural number such that ｉ is the amount r of substance i ｉ Therefore, m ｉ +1 is the auxiliary variable q ｉ０ , which indicates the number of bits reserved for substance i plus an extra bit representing

[0088] The inequality constraint in equation (12) is the auxiliary variable q ｉ０ is "1", the second term on the left side is determined to be "0", and the auxiliary variable q ｉ０ If is "0", the second term on the left side is "1 to m ｉ This is a constraint for determining whether "

[0089] The inequality constraint in equation (13) is the auxiliary variable q ｉ０ is "0", the second term on the left side is not "0". The inequality constraints in Equation (12) and Equation (13) are ｉ０ But, r ｉ >0 when q ｉ０ = 0 and r ｉ When q = 0 ｉ０This is a constraint to ensure that .times. ...

[0090] 10A and 10B are explanatory diagrams of examples of constraints shown in formulas (12) and (13). Calculation examples of formulas (12) and (13) for "substance 1" are shown in FIGS. 10A and 10B. For "substance 1" with an amount of "2 to 10", m ｉ becomes "7".

[0091] When "Substance 1" is used, the constraint is met if the bit array representing the blending amount of "Substance 1" contains a bit of "1," as shown in the table in Figure 10A. Also, when "Substance 1" is used, the constraint is violated if the bit array representing the blending amount of "Substance 1" does not contain a bit of "1."

[0092] When "Substance 1" is not used, the constraint is met if the bit array representing the blending amount of "Substance 1" does not contain a bit of "1," as shown in the table in Figure 10B. Also, when "Substance 1" is not used, the constraint is violated if the bit array representing the blending amount of "Substance 1" contains a bit of "1."

[0093] Note that the constraints shown in formulas (12) and (13) are imposed for each substance i, so if there are 20 substances i, 20×2=40 constraints are imposed. ｉ０ This is a constraint.

[0094] Constraint 2 In this embodiment, when there are combinations of substances that are incompatible with each other, the constraints shown in formulas (14) and (15) are imposed for each combination of substances that should be avoided. Here, an example will be described in which substances A and B are incompatible with each other. Formulas (14) and (15) represent the constraint that substance B should not be used when substance A is used.

[0095] In the case of substance B, the quantity of which is set as a continuous number, m ｂ is C ｍ <M ｉ，ＭＡＸ In the case of substance B whose quantity is set as a discrete number, m Ｂis the amount of substance B, r ｉ Therefore, m Ｂ +1 is the auxiliary variable q Ｂ０ 1. The number of bits reserved for substance B plus an additional bit representing

[0096] The inequality constraint in equation (14) is the auxiliary variable q Ａ０ If is "1", the second term on the left side is "0 to m Ｂ " and the auxiliary variable q Ａ０ is "0", the constraint for determining whether the second term on the left side is "0".

[0097] The inequality constraint in equation (15) is the auxiliary variable q Ａ０ is "1", the second term on the left side is allowed to be "0". Note that the inequality constraints in Equations (14) and (15) are based on the auxiliary variable q ｉ０ But, r ｉ >0 when q ｉ０ = 0 and r ｉ When q = 0 ｉ０ It is necessary to impose the constraint that ∇ = 1.

[0098] 11A and 11B are explanatory diagrams of examples of the constraints shown in formulas (14) and (15). FIG. 11A shows an example of calculation of formulas (14) and (15) of the constraints for substance B when substance A is used. For substance B with an amount of "2 to 10", m ｂ becomes "7".

[0099] As shown in the table in Figure 11A, the constraint "When substance A is used, substance B should not be used" is satisfied if the bit array representing the blending amount of substance B does not contain a bit of "1." Also, the constraint "When substance A is used, substance B should not be used" is violated if the bit array representing the blending amount of substance B contains a bit of "1."

[0100] The constraint "substance B is used when substance A is not used" is satisfied if the bit array representing the blending amount of substance B contains a bit of "1", as shown in the table in FIG. 11B. The constraint "substance B is used when substance A is not used" is violated if the bit array representing the blending amount of substance B does not contain a bit of "1".

[0101] Note that the constraints shown in formulas (14) and (15) are imposed on each combination of incompatible substances. To ensure the converse, the constraints shown in formulas (16) and (17) are also imposed on substance A. Formulas (16) and (17) express the constraint that substance A should not be used when substance B is used.

[0102] In the case of substance A, the quantity of which is set as a continuous number, m ａ is C ｍ <M ｉ，ＭＡＸ In the case of substance A whose quantity is set as a discrete number, m Ａ is the amount of substance A, r ｉ Therefore, m Ａ +1 is the auxiliary variable q Ａ０ 1. The number of bits reserved for substance A is shown, along with the auxiliary bit representing

[0103] The inequality constraint in equation (16) is the auxiliary variable q Ｂ０ If is "1", the second term on the left side is "0 to m Ａ " and the auxiliary variable q Ｂ０ is "0", the constraint for determining whether the second term on the left side is "0".

[0104] The inequality constraint in equation (17) is the auxiliary variable q Ｂ０ If is "1", the second term on the left side is "0 to m Ｂ The constraints of the inequality in Equation (16) and Equation (17) are the constraints for determining whether the auxiliary variable q ｉ０ But, r ｉ >0 when q ｉ０ = 0 and r ｉWhen q = 0 ｉ０ It is necessary to impose the constraint that ∇ = 1.

[0105] A specific example of this embodiment will be further described. FIGS. 12A to 12D are diagrams for explaining examples of using the constraints shown in equations (14) and (15). In FIGS. 12A to 12D, m Ｂ An example of substance B where is "7" is shown below.

[0106] The constraint "When substance A is used, substance B is not used" in FIG. 12A is Ａ０ is "0", and the auxiliary variable q Ｂ０ is "1", and the bit array representing the blending amount of substance B does not contain a bit of "1", so this condition is satisfied.

[0107] The constraint "Use substance B when substance A is not used" in Figure 12B is Ａ０ is "1", and the auxiliary variable q Ｂ０ is "0", and the bit array representing the blending amount of substance B contains a bit of "1", so this is satisfied.

[0108] The constraint in FIG. 12C, "When substance A is not used, substance B is not used either," is Ａ０ is "1", and the auxiliary variable q Ｂ０ is "1", and the bit array representing the blending amount of substance B does not contain a bit of "1", so this condition is satisfied.

[0109] The constraint "When substance A is used, substance B is also used" in Figure 12D is Ａ０ is "0", and the auxiliary variable q Ｂ０ is "0", and the bit array representing the blending amount of substance B contains a bit of "1", so this is not satisfied and a constraint violation occurs.

[0110] 12A to 12D show an example in which a constraint is imposed on material B. To make the opposite true, an example in which a similar constraint is imposed on material A will be described.

[0111] 13A and 13B are diagrams illustrating examples of using the constraints shown in equations (14), (15), (16), and (17). Ａand m Ｂ Here is an example where the value is "7".

[0112] The constraint "When substance A is not used, substance B is used" in Figure 13A is Ａ０ is "0", and the auxiliary variable q Ｂ０ is "1", and the bit array representing the blending amount of substance B does not contain a bit of "1", so this condition is satisfied.

[0113] The constraint "When substance B is used, substance A is not used" in Figure 13B is Ａ０ is "1", and the auxiliary variable q Ｂ０ is "0", and the bit array representing the blending amount of substance A does not contain a bit of "1", so this condition is satisfied.

[0114] In this way, the constraints shown in the equations (16) and (17), which are the inverse of the constraints shown in the equations (14) and (15), also hold.

[0115] According to this embodiment, when there is a combination of substances with incompatibility, it is possible to impose constraints on each combination of substances that should be avoided so that the combination of incompatible substances is not selected as the optimal combination. For example, if there is a combination of substances that will not mix due to incompatibility, such as miscibility, and such a combination is known in advance, it is possible to avoid unnecessary searches by imposing constraints as described above.

[0116] <Constraint 3> In this embodiment, when there is a combination of substances that are incompatible with each other, in addition to imposing the constraints shown in the above-described formulas (12) and (13) for each substance i, the constraint shown in formula (18) is imposed on the substance i to which a constraint is to be applied.

[0117] N included in formula (18) is the number of substances i to which a constraint is imposed by formula (18). The left side is the number of substances i that are not used among the substances i to which a constraint is imposed. The inequality constraint in formula (18) is a constraint for determining whether the number of unused substances i is equal to or greater than "N-1".

[0118] Here, an example will be described in which substances A and B are an incompatible combination and therefore substances A and B are not used simultaneously. Fig. 15 is a diagram illustrating an example of using the constraint condition shown in formula (18). Note that Fig. 15 shows an example in which the number of substances i to which the constraint condition is imposed is "2".

[0119] The constraint "When substance A is used, substance B is not used" in Figure 15(A) is Ａ０ is "0", and the auxiliary variable q Ｂ０ is "1" and the left side is "1", so it is satisfied.

[0120] The constraint "Use material B when material A is not used" in Figure 15(B) is Ａ０ is "1", and the auxiliary variable q Ｂ０ is "0" and the left side is "1", so the condition is satisfied.

[0121] The constraint in Figure 15(C) that "when substance A is not used, substance B is not used either" is Ａ０ is "1", and the auxiliary variable q Ｂ０ is "1" and the left side is "2", so the condition is satisfied.

[0122] The constraint "When substance A is used, substance B is also used" in Figure 15(D) is Ａ０ is "0", and the auxiliary variable q Ｂ０ is "0" and the left side is "0", so equation (18) is not satisfied, resulting in a constraint violation.

[0123] Next, an example will be described in which substances A, B, and C are an incompatible combination, and substances A, B, and C are not used simultaneously. Fig. 16 is a diagram illustrating an example of using the constraint condition shown in formula (18). Note that Fig. 16 shows an example in which the number of substances i to which the constraint condition is imposed is "3."

[0124] There are eight combinations of using and not using substances A, B, and C, as shown in the table of FIG. 16. Auxiliary variable q Ａ０ is "0" when substance A is used and "1" when it is not used. Ｂ０ is "0" when substance B is used and "1" when it is not used.Ｃ０ is "0" when substance C is used and "1" when it is not used.

[0125] The constraint "do not use any of material A, material B, and material C" is expressed by the auxiliary variable q Ａ０ is "1", and the auxiliary variable q Ｂ０ is "1", and the auxiliary variable q Ｃ０ is "1" and the left side is "3", so the condition is satisfied.

[0126] The constraint "use only substance A" is Ａ０ is "0", and the auxiliary variable q Ｂ０ is "1", and the auxiliary variable q Ｃ０ is "1" and the left side is "2", so the condition is satisfied.

[0127] The constraint "only use substance B" is Ａ０ is "1", and the auxiliary variable q Ｂ０ is "0", and the auxiliary variable q Ｃ０ is "1" and the left side is "2", so the condition is satisfied.

[0128] The constraint "use only substance C" is Ａ０ is "1", and the auxiliary variable q Ｂ０ is "1", and the auxiliary variable q Ｃ０ is "0" and the left side is "2", so the condition is satisfied.

[0129] The constraint "use material B and material C" is Ａ０ is "1", and the auxiliary variable q Ｂ０ is "0", and the auxiliary variable q Ｃ０ is "0" and the left side is "1", so equation (18) is not satisfied, resulting in a constraint violation.

[0130] The constraint "use material A and material C" is Ａ０ is "0", and the auxiliary variable q Ｂ０ is "1", and the auxiliary variable q Ｃ０ is "0" and the left side is "1", so equation (18) is not satisfied, resulting in a constraint violation.

[0131] The constraint "use material A and material B" is Ａ０ is "0", and the auxiliary variable q Ｂ０ is "0", and the auxiliary variable q Ｃ０ is "1" and the left side is "1", so equation (18) is not satisfied, resulting in a constraint violation.

[0132] The constraint "use material A, material B, and material C" is expressed by the auxiliary variable q Ａ０ is "0", and the auxiliary variable q Ｂ０ is "0", and the auxiliary variable q Ｃ０ is "0" and the left side is "0", so equation (18) is not satisfied, resulting in a constraint violation.

[0133] According to this embodiment, when there is a combination of substances that are incompatible with each other, it is possible to impose constraints so that the combination of incompatible substances is not selected as the optimal combination. For example, when there is a combination of substances that are incompatible with each other and cannot be mixed, and the combination is known in advance, it is possible to avoid unnecessary searches by imposing constraints as described above.

[0134] <Processing> FIG. 14 is a flowchart showing an example of a processing procedure of the information processing system according to this embodiment.

[0135] In step S100, the information processing device 12 receives from a user input of information necessary for causing the annealing-type optimization machine 10 to solve the combinatorial optimization problem. For example, the information processing device 12 receives input of an objective function that formulates the properties of a composite material according to the blend of substances. The information processing device 12 also receives input of blend constraint conditions.

[0136] In step S102, the information processing device 12 converts the combination constraint conditions input in step S100 into a constraint condition formula. The information processing device 12 converts the combination constraint conditions into a constraint condition formula based on the information of the constraint condition formula defined for the substance i stored in the constraint condition formula information storage unit 52. Note that the process of converting the combination constraint conditions into a constraint condition formula may be performed by the user.

[0137] In step S104, the information processing device 12 creates an Ising model to be solved by the annealing-type optimization machine 10 from the objective function and the constraint condition equation.

[0138] In step S106, the information processing device 12 creates input information in a data format usable by the annealing-type optimization machine 10 from the created Ising model, and transmits the information to the annealing-type optimization machine 10. The input information in a data format usable by the annealing-type optimization machine 10 includes the contents of the objective function and constraint condition equations. The input information for the annealing-type optimization machine 10 is, for example, an electronic file to be transmitted to the annealing-type optimization machine 10.

[0139] In step S108, the information processing device 12 transmits input information for the annealing-type optimization machine 10 to the annealing-type optimization machine 10. The annealing-type optimization machine 10 calculates an optimal solution (a material combination that optimizes the properties of the composite material) from among solutions that satisfy the constraint conditions (combination constraint conditions) in accordance with the received input information.

[0140] In step S110, the annealing-type optimization machine 10 transmits information representing the calculated optimal solution to the information processing device 12. The information processing device 12 converts the information (bit information) representing the optimal solution received from the annealing-type optimization machine 10 into user-friendly information such as the composition of substances in the composite material, and outputs the information. For example, the information processing device 12 displays the composition (substance names) of the composite material of the optimal solution and the amounts of those substances.

[0141] The composite material composition searched for as an optimal solution in this embodiment can be used to control a composite material production device, such as an aluminum alloy production device, which produces a composite material by specifying the materials to be mixed and the amounts of the materials. This embodiment can also be used to search for a compounding composition for a semiconductor material, for example, as a composite material. Examples of semiconductor materials include resist materials, adhesives, pressure-sensitive adhesives, and encapsulants, and are composite materials that contain multiple resins, additives, and / or fillers.

[0142] As described above, the information processing system 1 according to this embodiment can assist in creating an Ising model for causing the annealing optimization machine 10 to solve an optimization problem of a composite material that has composition constraints.

[0143] Although the present embodiment has been described above, it will be understood that various changes in form and details are possible without departing from the spirit and scope of the claims. While the present invention has been described above based on examples, the present invention is not limited to the above examples and various modifications are possible within the scope of the claims. This application claims priority to basic application No. 2023-222639 filed with the Japan Patent Office on December 28, 2023, and basic application No. 2024-033063 filed with the Japan Patent Office on March 5, 2024, the entire contents of which are incorporated herein by reference.

[0144] REFERENCE SIGNS LIST 1 Information processing system 10 Annealing type optimization machine 12 Information processing device 18 Communication network 20 Call reception unit 22 Optimal solution calculation unit 30 Input reception unit 32 Conversion unit 34 Data creation unit 36 ​​Display unit 50 Material information storage unit 52 Constraint condition equation information storage unit

Claims

1. An information processing device that supports the creation of an Ising model for making an annealing type optimization machine solve an optimal solution search problem for a composite material with a combination constraint condition, an input receiving unit configured to receive input of an objective function that formulates the properties of the composite material according to the blend and a constraint condition for the blend; a data creation unit configured to create an Ising model for causing the annealing optimization machine to find an optimal solution for the blend that satisfies a constraint condition formula that formulates the blend constraint conditions and optimizes the characteristics; and and The substance to be mixed into the composite material is a substance i in an amount r ｉ is represented by a bit, and whether or not the substance i is included in the composite material is represented by a bit, The constraint condition formula includes a condition that satisfies the following formula (1) and formula (2): [Equation 1] The q Ａ０ is an auxiliary variable that is "0" when substance A is contained in the composite material and is "1" when substance A is not contained in the composite material, The q Ｂ０ is an auxiliary variable that is "0" when substance B is contained in the composite material and is "1" when substance B is not contained in the composite material, Said m Ｂ is the amount r of substance B mixed into the composite material Ｂ is the number of bits required to represent The q Ｂｊ is a binary representation of the composition of substance B, either "0" or "1"; The constraint condition equation is formulated so that the optimum solution of the blend is not calculated when at least one of the equations (1) and (2) is not satisfied. An information processing device characterized by:

2. The constraint equation further includes a condition that satisfies the following equations (3) and (4): [Equation 2] The q Ａ０ is an auxiliary variable that is "0" when substance A is contained in the composite material and is "1" when substance A is not contained in the composite material, The q Ｂ０ is an auxiliary variable that is "0" when substance B is contained in the composite material and is "1" when substance B is not contained in the composite material, Said m Ａ is the amount r of substance A mixed into the composite material Ａ is the number of bits required to represent The q Ａｊ is a binary representation of the composition of substance A, either "0" or "1"; The constraint condition equation is formulated so that the optimum solution of the blend is not calculated when at least one of the equations (3) and (4) is not satisfied.

2. The information processing device according to claim 1,

3. When the condition regarding the amount of the substance to be mixed into the composite material is set as a continuous number, the substance to be mixed into the composite material is determined by the amount r of substance i. ｉ is expressed in bit notation in the following formula (5), and whether or not the substance i is included in the composite material is expressed in bit notation, [Equation 3] The q ｉｊ is a number "0" or "1" representing the binary representation of the composition of material i, Said C j is the coefficient of the binary representation of the composition of material i, Said C １ is the amount of the smallest unit of the substance to be mixed, Said m ｉ is C ｍ <M ｉ，ＭＡＸ is the largest natural number such that Said M ｉ，ＭＡＸ is the amount r of substance i ｉ is the maximum amount of 3. The information processing device according to claim 1.

4. When the conditions regarding the amount of the substance to be mixed into the composite material are set as discrete numbers, the substance to be mixed into the composite material is determined by the amount r of substance i. ｉ is expressed in bit notation, and whether or not the substance i is included in the composite material is expressed in bit notation.

3. The information processing device according to claim 1.

5. The above formulas (1) and (2) are the conditions of the composition constraint that when substance A is used, substance B is not used.

3. The information processing device according to claim 1.

6. The above formulas (3) and (4) are the conditions of the blending constraint that substance A is not used when substance B is used.

3. The information processing device according to claim 2.

7. An information processing system having an annealing-type optimization machine and an information processing device that supports creation of an Ising model for causing the annealing-type optimization machine to solve an optimal solution search problem for a composite material with a blending constraint condition, an input receiving unit configured to receive input of an objective function that formulates the properties of the composite material according to the blend and a constraint condition for the blend; a data creation unit configured to create an Ising model for causing the annealing optimization machine to find an optimal solution for the blend that satisfies a constraint condition formula that formulates the blend constraint conditions and optimizes the characteristics; and and The substance to be mixed into the composite material is a substance i in an amount r ｉ is represented by a bit, and whether or not the substance i is included in the composite material is represented by a bit, The constraint condition formula includes a condition that satisfies the following formula (1) and formula (2): [Equation 4] The q Ａ０ is an auxiliary variable that is "0" when substance A is contained in the composite material and is "1" when substance A is not contained in the composite material, The q Ｂ０ is an auxiliary variable that is "0" when substance B is contained in the composite material and is "1" when substance B is not contained in the composite material, Said m Ｂ is the amount r of substance B mixed into the composite material Ｂ is the number of bits required to represent The q Ｂｊ is a binary representation of the composition of substance B, either "0" or "1"; The constraint condition equation is formulated so that the optimum solution of the blend is not calculated when at least one of the equations (1) and (2) is not satisfied. An information processing system characterized by:

8. An information processing device that supports the creation of an Ising model to allow an annealing-type optimization machine to solve the problem of finding an optimal solution for a composite material with compounding constraints. a step of receiving input of an objective function that formulates the properties of the composite material according to the blend and a constraint condition of the blend; a step of creating an Ising model for causing the annealing-type optimization machine to find an optimal solution for the blend that satisfies a constraint condition formula that formulates the conditions for the blend constraints and optimizes the characteristics; Execute The substance to be mixed into the composite material is a substance i in an amount r ｉ is represented by a bit, and whether or not the substance i is included in the composite material is represented by a bit, The constraint condition formula includes a condition that satisfies the following formula (1) and formula (2): [Equation 5] The q Ａ０ is an auxiliary variable that is "0" when substance A is contained in the composite material and is "1" when substance A is not contained in the composite material, The q Ｂ０ is an auxiliary variable that is "0" when substance B is contained in the composite material and is "1" when substance B is not contained in the composite material, Said m Ｂ is the amount r of substance B mixed into the composite material Ｂ is the number of bits required to represent The q Ｂｊ is a binary representation of the composition of substance B, either "0" or "1"; The constraint condition equation is formulated so that the optimum solution of the blend is not calculated when at least one of the equations (1) and (2) is not satisfied. A program characterized by.

9. An Ising model creation support method for an information processing device that supports creation of an Ising model for causing an annealing-type optimization machine to solve an optimal solution search problem for a composite material with a blending constraint condition, comprising: receiving input of an objective function that formulates the properties of the composite material according to the blend and a constraint condition for the blend; performing a process of creating an Ising model for causing the annealing optimization machine to find an optimal solution for the blend that satisfies a constraint condition formula that formulates the conditions for the blend constraints and optimizes the characteristics; The substance to be mixed into the composite material is a substance i in an amount r ｉ is represented by a bit, and whether or not the substance i is included in the composite material is represented by a bit, The constraint condition formula includes a condition that satisfies the following formula (1) and formula (2): [Equation 6] The q Ａ０ is an auxiliary variable that is "0" when substance A is contained in the composite material and is "1" when substance A is not contained in the composite material, The q Ｂ０ is an auxiliary variable that is "0" when substance B is contained in the composite material and is "1" when substance B is not contained in the composite material, Said m Ｂ is the amount r of substance B mixed into the composite material Ｂ is the number of bits required to represent The q Ｂｊ is a binary representation of the composition of substance B, either "0" or "1"; The constraint condition equation is formulated so that the optimum solution of the blend is not calculated when at least one of the equations (1) and (2) is not satisfied. An Ising model creation support method characterized by the above.

10. An information processing device that supports the creation of an Ising model for making an annealing type optimization machine solve an optimal solution search problem for a composite material with a combination constraint condition, an input receiving unit configured to receive input of an objective function that formulates the properties of the composite material according to the blend and a constraint condition for the blend; a data creation unit configured to create an Ising model for causing the annealing optimization machine to find an optimal solution for the blend that satisfies a constraint condition formula that formulates the blend constraint conditions and optimizes the characteristics; and and The substance to be mixed into the composite material is a substance i in an amount r ｉ is represented by a bit, and whether or not the substance i is included in the composite material is represented by a bit, The constraint condition formula includes conditions that satisfy the following formulas (6), (7), and (8): [Equation 7] The q ｉ０ is an auxiliary variable that is "0" when substance i is contained in the composite material and is "1" when substance i is not contained in the composite material; Said m ｉ is the amount r of substance i mixed into the composite material ｉ is the number of bits required to represent The q ｉｊ is a number "0" or "1" representing the binary representation of the composition of material i, N is the number of materials i that impose constraints according to equation (8), The constraint condition equation is formulated so that the optimum solution of the blend is not calculated when at least one of the equations (6), (7), and (8) is not satisfied. An information processing device characterized by: