Information processing system, material composition search method, material composition search device, and program

Abstract

This information processing system, comprising an annealing-type computing device employing an Ising model, and a material composition search device which converts a material composition combinatorial optimization problem that asymptotically approaches a target physical property value into an Ising model, and causes the computing device to solve the same, includes: an input accepting unit for accepting input of a target value and an allowable variation range of a physical property; a converting unit for converting a formula formulating the material composition combinatorial optimization problem that asymptotically approaches the target value into an Ising model having a data format that can be used by the computing device; an optimal solution calculating unit for using the Ising model to calculate an optimal solution for the material composition that asymptotically approaches the target value; a post-processing unit for performing post-processing to exclude a material contained in a mixed material from the optimal solution of the material composition, within the allowable variation range of the target value; and an output control unit for outputting the post-processed material composition.

Description

Information processing system, material composition search method, material composition search device, and program

[0001] The present disclosure relates to an information processing system, a material composition exploration method, a material composition exploration device, and a program.

[0002] For example, combinatorial optimization problems exist, such as searching for a material composition with optimal physical properties, where the optimal combination is selected from various combinations of elements. As the number of elements increases, the number of combinations of combinatorial optimization problems increases explosively, and it may not be possible to solve them within a realistic time frame. For example, when creating a mixed material by combining 100 types of materials in 1% increments, the number of combinations is 5 x 10 58 This becomes:

[0003] An annealing machine using the Ising model has been proposed as an architecture specialized for solving such combinatorial optimization problems. The annealing machine can efficiently solve combinatorial optimization problems converted into the Ising model.

[0004] Conventionally, a technique for optimizing the thermophysical properties of a refrigerant mixture using a computer architecture specialized for combinatorial optimization problems has been known (see, for example, Non-Patent Document 1).

[0005] "Optimization of Thermophysical Properties of Refrigerant Mixtures Using Digital Annealer," Proceedings of the 2019 Thermal Engineering Conference of the Japan Society of Mechanical Engineers, No. 19-303 [October 12-13, 2019, Nagoya]

[0006] For example, when an annealing machine is used to solve a combinatorial optimization problem for a material composition that asymptotically approaches (approximates) a target physical property value, the resulting composition of the mixed material (the materials contained in the mixed material and their ratios) that asymptotically approaches the target physical property value can be obtained. However, even if the resulting composition of the mixed material asymptotically approaches the target physical property value, there are cases where it is difficult to handle in practice, such as when the mixed material contains a large number of materials.

[0007] The present disclosure aims to provide an information processing system, a material composition search method, a material composition search device, and a program that can reduce the number of materials included in a material composition within an allowable variation range from an optimal solution to a combinatorial optimization problem of a material composition that asymptotically approaches a target physical property value.

[0008] The present disclosure has the following configuration.

[0009] [1] An information processing system having an annealing-type computing device using an Ising model, and a material composition exploration device that converts a combinatorial optimization problem of a material composition that asymptotically approaches a target physical property value into an Ising model and has the computing device solve the problem, wherein the information processing system has the following features: an input receiving unit that receives an input of a target value and an allowable change range of at least one physical property; a conversion unit that converts a mathematical expression that formulates a combinatorial optimization problem of a material composition that asymptotically approaches the target value from a mixture of materials whose physical property values ​​are known, into the Ising model in a data format that can be used by the computing device; an optimal solution calculation unit that calculates an optimal solution of the material composition that asymptotically approaches the target value using the Ising model; a post-processing unit that performs post-processing to remove the material contained in the mixture from the material composition of the calculated optimal solution within the allowable change range of the target value; and an output control unit that outputs the post-processed material composition.

[0010] [2] The information processing system according to [1], wherein the mathematical formula formulates a combinatorial optimization problem of a material composition that asymptotically approaches the target value using an energy function including: a cost function that outputs a value such that the closer the physical property value of the mixed material is to the target value, the more likely it is to be calculated as the optimal solution, and the further the physical property value of the mixed material is from the target value, the less likely it is to be calculated as the optimal solution; and a constraint that outputs a value such that the mixed material is not calculated as the optimal solution when the total of the proportions of materials contained in the mixed material is not 100%.

[0011] [3] The information processing system according to [1] or [2], wherein the formula is the following formula (1):

[0012] In the formula (1), L is the number of properties to be optimized, N is the number of materials whose properties are known, and D k,i is the kth property value of the material i to be optimized, and i is the following formula (2) which expresses the mixture ratio (composition ratio) of material i using the binary method,

[0013] The above D k,0 is the target value of the kth physical property of the mixed material to be optimized, i,j is a number "0" or "1" when the mixing ratio of material i is expressed in binary form, j is a coefficient when the mixing ratio of material i is expressed by the binary method, and the α k , β is a weighting constant.

[0014] [4] The optimal solution calculation unit uses the Ising model obtained by converting the formula (1) into a data format usable by the computing device to calculate the n i,j The information processing system according to [3], wherein the combination of the above is calculated as an optimal solution for the material composition that asymptotically approaches the target value.

[0015] [5] The information processing system according to any one of [1] to [3], wherein the input receiving unit receives from a user a selection of a target value for at least one physical property, a selection of the material to be used as a material composition of the mixed material from a plurality of materials having known physical property values ​​of the at least one physical property, and a selection of an allowable change range for the target value, and the post-processing unit performs post-processing to remove the materials contained in the mixed material in ascending order of mixing ratio from the material composition of the output optimal solution within the allowable change range for the target value.

[0016] [6] The information processing system according to any one of [1] to [3], wherein the input receiving unit receives from a user a selection of a target value for at least one physical property, a selection of the material to be used as the material composition of the mixed material from a plurality of materials having known physical property values ​​of the at least one physical property, and a selection of an allowable change range for the target value, and the post-processing unit performs post-processing to remove the materials included in the mixed material from the material composition of the output optimal solution in the order selected by the user, within the allowable change range for the target value.

[0017] [7] The information processing system according to any one of [1] to [6], wherein the output control unit displays, on a display device, information including the material composition of the optimal solution calculated by the optimal solution calculation unit and the material composition from which at least one of the materials has been removed by the post-processing unit.

[0018] [8] A material composition exploration method executed by an information processing system having an annealing-type computing device using an Ising model and a material composition exploration device that converts a combinatorial optimization problem of a material composition that asymptotically approaches a target physical property value into an Ising model and has the computing device solve the problem, the material composition exploration method comprising: an input receiving step of receiving an input of a target value and an allowable change range of at least one physical property; a conversion step of converting a mathematical expression that formulates a combinatorial optimization problem of a material composition that asymptotically approaches the target value from a mixture of materials whose physical property values ​​are known, into the Ising model in a data format that can be used by the computing device; an optimal solution calculation step of calculating an optimal solution of the material composition that asymptotically approaches the target value using the Ising model; a post-processing step of performing post-processing to remove the material contained in the mixture from the material composition of the calculated optimal solution within the allowable change range of the target value; and an output control step of outputting the post-processed material composition.

[0019] [9] A material composition exploration device connected to an annealing-type computing device using an Ising model via a communication network, converting a combinatorial optimization problem of a material composition asymptotically approaching a target physical property value into an Ising model and causing the computing device to solve the problem, comprising: an input receiving unit that receives input of a target value and an allowable change range of at least one physical property; a conversion unit that converts a mathematical expression that formulates a combinatorial optimization problem of a material composition asymptotically approaching the target value from a mixed material of materials whose physical property values ​​are known into the Ising model in a data format that can be used by the computing device; a linking unit that sends the converted Ising model to the computing device and receives from the computing device an optimal solution of the material composition asymptotically approaching the target value, calculated by the computing device; a post-processing unit that performs post-processing to remove the material contained in the mixed material from the material composition of the received optimal solution within the allowable change range of the target value; and an output control unit that outputs the post-processed material composition.

[0020]

[10] A program for causing a material composition exploration device, which is connected to an annealing-type computing device using an Ising model via a communication network, to convert a combinatorial optimization problem of a material composition asymptotically approaching a target physical property value into an Ising model and cause the computing device to solve the problem, to function as: an input receiving unit that receives input of a target value and an allowable change range of at least one physical property; a conversion unit that converts a mathematical expression that formulates a combinatorial optimization problem of a material composition asymptotically approaching the target value from a mixed material of materials whose physical property values ​​are known into the Ising model in a data format that can be used by the computing device; a linking unit that sends the converted Ising model to the computing device and receives from the computing device an optimal solution of the material composition asymptotically approaching the target value calculated by the computing device; a post-processing unit that performs post-processing to remove the material contained in the mixed material from the material composition of the received optimal solution within the allowable change range of the target value; and an output control unit that outputs the post-processed material composition.

[0021] According to the present disclosure, the number of materials included in the material composition can be reduced within the range of allowable variation from the optimal solution of the combinatorial optimization problem of the material composition that asymptotically approaches the target physical property value.

[0022] FIG. 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 a configuration diagram of an example of solvent information with known physical property values. FIG. 4 is a configuration diagram of an example of an information processing system according to the present embodiment. FIG. 5 is a flowchart showing an example of the processing procedure of a material composition searching method of the information processing system according to the present embodiment. FIG. 6 is a flowchart showing an example of the processing procedure of step S18. FIG. 7 is a configuration diagram showing an example of a combination and mixing ratio of solvents adopted. FIG. 8 is an image diagram of an example of a material composition searching result screen.

[0023] Next, an embodiment of the present invention will be described in detail. However, the present invention is not limited to the following embodiment. In this embodiment, optimization of a mixed solvent containing a solvent with known physical properties will be described as an example of optimization of a mixed material containing a material with known physical properties.

[0024] <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 in Fig. 1 includes an annealing-based computer 10 and a material composition exploration device 12. The annealing-based computer 10 and the material composition exploration 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.

[0025] The annealing computer 10 is an annealing machine that uses an Ising model and is an example of an annealing-based computing device that uses an Ising model. The annealing computer 10 may be realized by a quantum computer, or may be realized by a Digital Annealer (registered trademark), which is a computer architecture that realizes the annealing method using digital circuits.

[0026] Annealing machines solve combinatorial optimization problems that have been reduced to an Ising model through the convergence behavior of that Ising model. The Ising model is a statistical mechanics model that represents the behavior of magnetic materials, and has the property that the spin state is updated so that the energy (Hamiltonian) is minimized due to interactions between spins in the magnetic material, ultimately minimizing the energy. Annealing machines reduce combinatorial optimization problems to an Ising model and find the state that minimizes energy, thereby obtaining that state as the optimal solution to the combinatorial optimization problem.

[0027] The material composition exploration device 12 is an information processing device such as a PC that can be operated by a user. The material composition exploration device 12 may also be an information processing terminal such as a tablet terminal or a smartphone that can be operated by a user. The material composition exploration device 12 accepts input of information necessary for causing an annealing machine to solve a combinatorial optimization problem reduced to an Ising model, and causes the annealing computer 10 to solve the Ising model.

[0028] The material composition searching device 12 receives the optimal solution of the combinatorial optimization problem solved by the annealing-based computer 10, and outputs information such as the solvent composition of the optimal solution and the solvent composition obtained by post-processing the optimal solution as described below on a display device so that the user can confirm it.

[0029] The information processing system 1 in FIG. 1 is merely an example, and may further include a user terminal (not shown) operated by a user, so that the user can access and use the material composition searching device 12 from the user terminal.

[0030] The annealing method computer 10 may also be implemented as a cloud computing service. For example, the annealing method computer 10 may be available by calling an API (application programming interface) via a communication network 18. Furthermore, the annealing method computer 10 is not limited to being implemented as a cloud computing service, but may also be implemented on-premise or operated by another company. The annealing method computer 10 may also be implemented using multiple computers. It goes without saying that the information processing system 1 in FIG. 1 has a variety of system configuration examples depending on the application and purpose.

[0031] <Hardware Configuration> The material composition exploration device 12 in FIG. 1 is realized by, for example, a computer 500 having the hardware configuration shown in FIG.

[0032] 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.

[0033] 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.

[0034] 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.

[0035] 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.

[0036] 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.

[0037] 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 material composition exploration device 12 according to this embodiment can realize various functions as described below. Note that a description of the hardware configuration of the annealing-based computer 10 will be omitted.

[0038] <Example of a problem solved as a combinatorial optimization problem> Below, an example will be described in which a plurality of solvents with known physical property values ​​are mixed together to determine the mixing ratio (composition ratio) of the mixed solvent at which the target physical property asymptotically approaches (approximates) the target value, as a combinatorial optimization problem.

[0039] For example, in this embodiment, a plurality of solvents with known physical property values ​​are used, as shown in Fig. 3. Fig. 3 is a configuration diagram of an example of solvent information with known physical property values. The solvent information in Fig. 3 records one or more physical property values ​​for each solvent identified by the solvent name. In Fig. 3, as an example, the physical property values ​​of three physical properties δD, δP, and δH are recorded.

[0040] In this embodiment, the target property is selected from the solvent information in Fig. 3. The property value of the target property of the mixed solvent is calculated by the following formula (3).

[0041] Physical property value of mixed solvent=Σ(physical property value of single solvent×mixing ratio) (3) In this embodiment, the task to be solved as a combinatorial optimization problem is to search for a mixing ratio of a mixed solvent that will cause a target physical property to approach a target value by mixing multiple types of solvents included in the solvent information in FIG. 3 in increments of, for example, 1%.

[0042] In this embodiment, the problem to be solved is formulated as, for example, the following formula (4) or formula (1). Formula (4) is an example of a formula formulated when there is one target property. Formula (1) is an example of a formula formulated when there are two or more target properties.

[0043]

[0044] In the above formula (4), E is an energy function (evaluation function), N is the number of solvents whose physical properties are known, and D i is the property value of the target property of solvent i to be optimized, and r i is the following formula (2) which expresses the mixing ratio (composition ratio) of solvent i using the binary method,

[0045] D0 is the target value of the target property of the mixed solvent to be optimized, and n i,j is a number of "0" or "1" when the mixing ratio of solvent i is expressed in binary form, and the solvent i is in the ratio c j If solvent i is included, it is set to "1"; if ... j If not included, it becomes "0", and c jis a coefficient when the mixture ratio of solvent i is expressed by the binary method, and α and β are weighting constants.

[0046] In the above formula (1), E is an energy function (evaluation function), L is the number of target properties to be optimized, N is the number of solvents whose property values ​​are known, and D k,i is the kth target property value of solvent i to be optimized, and r i is the above equation (2) expressing the mixing ratio of solvent i using the binary method, and D k,0 is the target value of the kth objective property of the mixed solvent to be optimized, and α k , β is a weighting constant.

[0047] The first term on the right side of the above formula (4) decreases as the value of one of the target properties of the mixed solvent calculated by the above formula (3) approaches the target value of the target property. The second term on the right side of the above formula (4) is a constraint term that becomes "0" (decreases) when the total value of the mixing ratios (proportions) of the solvents contained in the mixed solvent is 1 (100%).

[0048] Furthermore, the first term on the right side of the above formula (1) becomes smaller as the property values ​​of the target properties of the multiple mixed solvents calculated by the above formula (3) approach the target values ​​of each target property. The second term on the right side of the above formula (1) is a constraint term that becomes "0" (becomes smaller) when the total mixing ratio (proportion) of the solvents contained in the mixed solvent is 1 (100%).

[0049] In the example of the above formula (2), the ratio c required to express the mixture ratio of solvent i is j For example, in the first expression of the mixture ratio of solvent i, the ratio c j (c1 = 2 / 100, c2 = 2 / 100, ...c 50 In the second expression of the mixture ratio, the ratio c j (c1 = 1 / 100, c2 = 1 / 100, ... c 100 In the third expression of the mixture ratio, the ratio cj can be expressed as (c1 = 64 / 100, c2 = 32 / 100, c3 = 16 / 100, c4 = 8 / 100, c5 = 4 / 100, c6 = 2 / 100, c7 = 1 / 100) with the number of nodes "m = 7". j (c1 = 512 / 1000, c2 = 256 / 1000, c3 = 128 / 1000, c4 = 64 / 1000, c5 = 32 / 1000, c6 = 16 / 1000, c7 = 8 / 1000, c8 = 4 / 1000, c9 = 2 / 1000, c 10 This can be expressed with the number of nodes "m = 10", such as m = 1 / 1000). For example, the third method of expressing the mixture ratio can be used when mixing in 1% increments, and 7 bits are required to express the mixture ratio of one solvent. When mixing in 0.1% increments, 10 bits are required per solvent, as shown in the fourth method of expressing the mixture ratio.

[0050] The formulated equation (4) or equation (1) is converted into an Ising model in a data format that can be used by the annealing computer 10, and then transmitted from the material composition exploration device 12 to the annealing computer 10. The annealing computer 10 calculates an optimal solution for the solvent composition using the Ising model in the usable data format.

[0051] The calculated optimal solution for the solvent composition is transmitted from the annealing computer 10 to the material composition searching device 12. It is expected that the optimal solution for the solvent composition will not deviate significantly from the target value of the target property, even if, for example, a solvent of a minor component with a small mixing ratio is removed. Therefore, the material composition searching device 12 of this embodiment determines an allowable change range for the target value of the target property, and performs post-processing, for example, by removing the solvent of a minor component with a small mixing ratio from the optimal solution for the solvent composition received from the annealing computer 10, within the allowable change range for the target value of the target property. The post-processed solvent composition approaches the target value of the target property and contains fewer materials.

[0052] The material composition searching device 12 outputs information such as the optimum solution for the solvent composition received from the annealing computer 10 and the solvent composition obtained by post-processing the optimum solution so that the user can confirm it.

[0053] <Configuration> The configuration of the information processing system 1 according to this embodiment will be described. Fig. 4 is a configuration diagram of an example of the information processing system according to this embodiment. Note that in the configuration diagram of Fig. 4, parts that are not necessary for explaining this embodiment are omitted as appropriate.

[0054] 4 includes a call receiving unit 20 and an optimal solution calculation unit 22. The material composition searching device 12 includes an input receiving unit 30, a formulation unit 32, a conversion unit 34, a linking unit 36, a post-processing unit 37, an output control unit 38, a solvent information storage unit 40, a formula storage unit 42, and an allowable change range storage unit 44.

[0055] The input accepting unit 30 is an input interface that accepts input of a target property, a target value of the target property, and an allowable change range of the target value from the user. The input accepting unit 30 may also accept input of solvent information to be used from the user. The input accepting unit 30 stores the input solvent information in the solvent information storage unit 40. The input accepting unit 30 stores the allowable change range of the input target value in the allowable change range storage unit 44. In this way, in this embodiment, a target value and an allowable change range are determined for each target property. A default value for the allowable change range may be set in advance for each property, and the user may change it as needed.

[0056] The formulation unit 32 receives input of the above-mentioned formula (4) or formula (1), which formulates the problem of searching for a mixture ratio of a mixed solvent in which a target property approaches a target value by mixing, for example, multiple types of solvents from the solvent information in Fig. 3 in 1% increments. As described above, formula (4) is an example of a formula formulated when there is one target property, and receives input of weighting constants α and β from the user. Formula (1) is an example of a formula formulated when there are two or more target properties, and receives input of weighting constants α and β from the user. k , β is input.

[0057] The formulation unit 32 receives input of the above formula (4) or (1) by a program that defines the above formula (4) or (1), for example. The formulation unit 32 stores the input formula (4) or (1) in the mathematical formula storage unit 42.

[0058] When there is one target physical property, the conversion unit 34 converts the target physical property, the target value of the target physical property, and the above formula (4) into an Ising model in a data format that can be used by the annealing computer 10. When there are two or more target physical properties, the conversion unit 34 converts the target physical property, the target value of the target physical property, and the above formula (1) into an Ising model in a data format that can be used by the annealing computer 10.

[0059] The collaboration unit 36 ​​transmits the Ising model converted by the conversion unit 34 to the annealing-based computer 10. The collaboration unit 36 ​​also receives the optimal solution calculated by the annealing-based computer 10.

[0060] The post-processing unit 37 performs post-processing to reduce the number of solvents contained in the optimal solution solvent composition calculated by the annealing computer 10 within the allowable change range of the target value of the target physical property. For example, the post-processing unit 37 performs post-processing to remove solvents of trace components with small mixing ratios contained in the optimal solution solvent composition within the allowable change range of the target value of the target physical property. The solvent composition obtained by such post-processing deviates from the target value of the target physical property compared to the optimal solution solvent composition, but the number of solvents contained in the solvent composition is reduced, making it a solvent composition that is easy to use in practice. Note that the solvents to be removed from the optimal solution solvent composition may be selected in order of decreasing mixing ratio, or the user may be allowed to select.

[0061] The output control unit 38 displays the optimal solution solvent composition received by the collaboration unit 36, the solvent composition post-processed by the post-processing unit 37, etc. on the display device 502, allowing the user to confirm the results. The solvent composition displayed on the display device 502 is displayed in a manner that is easy for the user to understand, for example, as a mixing ratio of the solvents contained in the mixed solvent. The output control unit 38 may calculate the physical property values ​​of the target physical properties of the optimal solution solvent composition received by the collaboration unit 36 ​​and the solvent composition post-processed, and display them on the display device 502, allowing the user to confirm the results.

[0062] The call receiving unit 20 receives a call from the material composition exploration device 12 and receives an Ising model converted into a data format usable by the material composition exploration device 12. The optimal solution calculation unit 22 searches for an optimal solution of the mixture ratio of the mixed solvents at which the target physical property asymptotically approaches the target value by determining the state at which the energy (Hamiltonian) of the Ising model received by the call receiving unit 20 is minimized. The call receiving unit 20 transmits the searched optimal solution to the material composition exploration device 12.

[0063] 4 is an example, and various configurations of the information processing system 1 according to this embodiment are possible.

[0064] 5 is a flowchart showing an example of the processing procedure of the material composition searching method of the information processing system according to this embodiment. In step S10, the input receiving unit 30 of the material composition searching device 12 receives input from the user of the target properties of the mixed solvent to be optimized, the target values ​​of the target properties, and the allowable range of change of the target values. Here, it is assumed that the input of the target properties δD, δP, and δH and the target values ​​of the target properties (δD, δP, δH) = (18.0, 12.3, 7.2) is received from the user. In addition, the input receiving unit 30 of the material composition searching device 12 receives weighting constants α, β, or α from the user. k , β is input.

[0065] In step S12, the input receiving unit 30 of the material composition exploration device 12 receives input of solvent information for the solvents to be mixed, for example, as shown in FIG. 3. The solvent information shown in FIG. 3 is table data that stores the physical property values ​​of multiple types of single solvents to be mixed. Note that the solvent information may be input by selecting a table data file stored in the solvent information storage unit 40. Furthermore, the input receiving unit 30 of the material composition exploration device 12 may receive selection of the single solvents to be mixed and the target physical properties of the mixed solvent from the selected table data file.

[0066] In step S14, the formulation unit 32 and the conversion unit 34 of the material composition searching device 12 obtain an Ising model in a data format that can be used by the annealing computer 10, using the above-mentioned formula (4) or (1), which formulates the task of searching for a mixed solvent mixture ratio at which a target physical property approaches a target value by mixing multiple types of solvents in increments of 1%, for example, and the target physical property of the mixed solvent to be optimized and the target value of the target physical property, which were received as input in step S10.

[0067] Note that the technology (library) for converting the formulated formula (4) or formula (1) into a quadratic unconstrained binary optimization (QUBO) format of the evaluation function or into an Ising model in a data format that can be used by the annealing-based computer 10 is provided as a Web API or the like, and is an existing technology. The conversion unit 34 expands the above formula (4) or formula (1) to obtain the matrix element Q of the Ising model shown in the following formula (5): i,j Calculate the matrix element Q i,j is transmitted to the annealing computer 10 as a parameter of the Ising model.

[0068] E = ΣQ i,j n i n j +ΣQ ii n i …(5)

[0069] In step S16, the optimal solution calculation unit 22 of the annealing computer 10 that has received the parameters of the Ising model calculates the n i,j is found as the optimal solution. The n that minimizes the Hamiltonian of the above formula (4) or formula (1) is found. i,j represents the optimal solution for the mixing ratio of the mixed solvents at which the target property approaches the target value.

[0070] As mentioned above, n i,j is a variable that stores the number "0" or "1" when the mixing ratio of solvent i is expressed in binary format. i,j is that the solvent i is in proportion c j If solvent i is included, it is set to "1"; if ... jIf it is not contained, it will be "0". For example, if the solvent i is contained at 33%, the third expression of the mixing ratio above will be {n i,j} = (0, 1, 0, 0, 0, 0, 1).

[0071] In step S18, the linking unit 36 ​​of the material composition searching device 12 determines n θ that minimizes the Hamiltonian of the above formula (4) or formula (1) obtained by the annealing computer 10. i,j The post-processing unit 37 of the material composition searching device 12 performs post-processing to remove solvent from the mixed solvent within the allowable range of change in the target value of the target property from the solvent composition of the optimal solution, for example, according to the processing procedure shown in FIG.

[0072] 6 is a flowchart showing an example of the processing procedure of step S18. In step S30, the post-processing unit 37 acquires information on the solvent composition of the optimal solution obtained by the annealing computer 10. In step S32, the post-processing unit 37 acquires information on the allowable change range of the target value of the objective physical property from the allowable change range storage unit 44.

[0073] In step S34, the post-processing unit 37 creates a new solvent composition by excluding the solvent with the smallest mixing ratio from the solvents included in the solvent composition. In the first processing of step S34, a new solvent composition is created by excluding the solvent with the smallest mixing ratio from the solvents included in the solvent composition of the optimal solution. In the second or subsequent processing of step S34, a new solvent composition is created by excluding the solvent with the smallest mixing ratio from the new solvent composition created in the previous processing of step S34.

[0074] For example, if the solvents included in the solvent composition are {A, B, C, D, E, F, G} and the mixing ratio of the respective solvents is {46:22:12:9:8:2:1}, the post-processing unit 37 creates a new solvent composition in which the mixing ratio is "1" and the solvent "G" is omitted, which has the smallest mixing ratio. The mixing ratios of the new solvent composition are normalized so that they add up to 100%.

[0075] In step S36, the post-processing unit 37 calculates the physical property values ​​of the target properties for the new mixed solvent composition. The physical property values ​​of the mixed solvent can be calculated using the above formula (3).

[0076] In step S38, if all of the physical property values ​​of the target properties of the new solvent composition calculated in step S36 are within the allowable change range of the target value, the post-processing unit 37 returns to the processing of step S34 and creates a new solvent composition by excluding the solvent with the next smallest mixing ratio (the solvent with the smallest mixing ratio among the solvent compositions created in the previous processing of step S34).

[0077] For example, if the solvents included in the optimal solvent composition are {A, B, C, D, E, F, G} and the solvent removed in the previous processing in step S34 was "G," a new solvent composition is created by removing the next smallest solvent, "F."

[0078] The post-processing unit 37 repeats the processes of steps S34 to S38 until it determines that at least one of the target property values ​​of the new solvent composition calculated in step S36 is not within the allowable change range of the target value. Therefore, the optimal solvent composition obtained by the annealing computer 10 reduces the number of solvents contained in the solvent composition within the allowable change range of the target value of the target property.

[0079] On the other hand, if at least one of the target property values ​​of the new solvent composition calculated in step S36 is no longer within the allowable change range of the target value, the post-processing unit 37 proceeds to processing in step S40. In step S40, the post-processing unit 37 adopts the solvent composition before the last solvent was removed in the previous processing in step S34.

[0080] 6 is an example. For example, the selection of solvents to be removed in step S34 is not limited to the order of solvents with the lowest mixing ratio, but may be made taking other information into consideration, or may be made by the user. Furthermore, multiple solvent compositions may be used in step S40.

[0081] Returning to step S20 of the flowchart in Fig. 5, the output control unit 38 outputs the mixed solvent resulting from the post-processing of step S18 and the physical property values ​​of the target physical property of the mixed solvent. The output control unit 38 may also output the mixed solvent that is the optimal solution and the physical property values ​​of the target physical property of the mixed solvent. The output control unit 38 may output the n received as the optimal solution from the link unit 36, for example. i,jThe optimum mixed solvent and information on the mixed solvent, such as the target physical properties of the mixed solvent, can be output.

[0082] The output control unit 38 can output information about the mixed solvent used, such as the mixed solvent obtained as a result of step S18 and the target property values ​​of the mixed solvent, as shown in FIG. 7, for example.

[0083] FIG. 7 is a diagram illustrating an example of a solvent combination and mixing ratio. FIG. 7 shows an example of information including the solvents contained in the mixed solvent, the mixing ratio of the solvents, and the physical properties of the mixed solvent. The physical properties of the mixed solvent can be calculated using Equation (3) above. In the example of FIG. 6, for example, four solvents, acetone, cyclohexanone, sulfolane (tetramethylene sulfone), and toluene, are mixed in a ratio of 2:1:64:33, resulting in a mixed solvent with target properties δD, δP, and δH close to the target values ​​for the target properties (δD, δP, δH) = (18.0, 12.3, 7.2).

[0084] For example, the output control unit 38 may output information about the adopted mixed solvent to a material composition search result screen 1000 as shown in Fig. 8. Fig. 8 is an image diagram of an example of the material composition search result screen. The material composition search result screen 1000 displays a display field 1102 for information input by the user to allow the annealing machine to solve the combinatorial optimization problem reduced to an Ising model, and a display field 1104 for outputting information about the adopted mixed solvent.

[0085] Display field 1102 displays, as an example of information entered by the user, the target property, the target value of the target property, solvent information, a weighting constant, and the allowable change range of the target value. Display field 1104 displays, as an example of information on the adopted mixed solvent, the composition of the mixed solvent (the types of solvents contained in the mixed solvent and the mixing ratio of the solvents) and the property value of the target property.

[0086] By checking the material composition search result screen 1000 in Fig. 8, the user can easily evaluate the adopted mixed solvent. Furthermore, if the user wants to search for another mixed solvent after checking the material composition search result screen 1000 in Fig. 8, the user can readjust the weighting constants included in the above formula (4) or formula (1), for example, and then perform the process of the flowchart shown in Fig. 5. The readjustment of the weighting constants may be performed manually by the user, or may be performed using a program that automatically optimizes the weighting constants.

[0087] 8 may display information about the optimal mixed solvent together with information about the adopted mixed solvent. By displaying the information about the optimal mixed solvent together with information about the adopted mixed solvent, the user can easily compare and evaluate the mixed solvent obtained as the optimal solution with the adopted mixed solvent.

[0088] Furthermore, if the user checks the material composition search result screen 1000 and wishes to change the number (types) of solvents contained in the adopted mixed solvent, the user can, for example, adjust the allowable change range of the target value and then re-process the flowchart shown in FIG. 6 .

[0089] For example, if a user wishes to reduce the number of solvents contained in a mixed solvent, the user can increase the allowable range of change in the target value, thereby making it easier to adopt a solvent composition containing fewer solvents in the mixed solvent, even if the target physical properties deviate somewhat from the target values.

[0090] Furthermore, for example, if the user wishes to increase the number of types of solvents contained in the mixed solvent, the user can narrow the allowable range of change in the target value, thereby making it easier to adopt a solvent composition whose target physical properties are close to the target values, even if the number of solvents contained in the mixed solvent is large.

[0091] The material composition search result screen 1000 in Fig. 8 is one example, and may be provided with a field for adjusting the weighting constant included in the above formula (4) or formula (1), a field for adjusting the allowable change range of the target value, a re-search button for executing processing for re-searching for an optimal solution using the above formula (4) or formula (1) after the weight logarithm has been readjusted, and a post-processing button for executing the processing of the flowchart shown in Fig. 6 using the allowable change range of the readjusted target value. The material composition search result screen 1000 in Fig. 8 may be displayed together with the configuration diagram of Fig. 7.

[0092] The information on the adopted mixed solvent can be used to control, for example, a mixed solvent generator, which generates a mixed solvent by specifying the solvents to be mixed and their mixing ratio. Furthermore, the physical properties of the mixed solvent generated by the mixed solvent generator can be evaluated using an evaluation device. Therefore, the information on the adopted mixed solvent can be compared with the physical properties of the mixed solvent generated by the mixed solvent generator by specifying the information on the mixed solvent, and the accuracy can be improved by feeding back the results of this comparison.

[0093] As described above, according to the information processing system 1 of this embodiment, it is possible to reduce the number of solvents contained in the mixed solvent within the range of allowable variation from the optimal solution of the combinatorial optimization problem of the composition of the mixed solvent that asymptotically approaches the target value of the target physical property.

[0094] Although the present embodiment has been described above, it will be understood that various changes in form and details can be made without departing from the spirit and scope of the claims.

[0095] Although the present invention has been described above based on the 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 from basic application No. 2021-097382 filed with the Japan Patent Office on June 10, 2021, the entire contents of which are incorporated herein by reference.

[0096] REFERENCE SIGNS LIST 1 Information processing system 10 Annealing computer 12 Material composition searching device 18 Communication network 20 Call reception unit 22 Optimum solution calculation unit 30 Input reception unit 32 Formulation unit 34 Conversion unit 36 ​​Linkage unit 37 Post-processing unit 38 Output control unit 40 Solvent information storage unit 42 Formula storage unit 44 Allowable change range storage unit 502 Display device

Claims

1. An information processing system having an annealing-based calculation device using an Ising model, and a material composition search device that converts a combinatorial optimization problem of a material composition that asymptotically approaches a target physical property value into an Ising model and causes the calculation device to solve the problem, an input receiving unit that receives an input of a target value and an allowable change range of at least one physical property; a conversion unit that converts a mathematical expression that formulates a combinatorial optimization problem of a material composition that asymptotically approaches the target value from a mixture of materials with known physical property values ​​into the Ising model in a data format that can be used by the computing device; an optimal solution calculation unit that calculates an optimal solution of a material composition that asymptotically approaches the target value by using the Ising model; a post-processing unit that performs post-processing to remove the material contained in the mixed material from the material composition of the calculated optimal solution within a range of an allowable change width of the target value; an output control unit that outputs the post-processed material composition; An information processing system comprising:

2. The formula is: a cost function that outputs a value such that the closer the physical property value of the mixed material is to the target value, the more likely it is to be calculated as the optimal solution, and the further the physical property value of the mixed material is from the target value, the more difficult it is to calculate the physical property value of the mixed material as the optimal solution; a constraint condition for outputting a value so that the optimum solution is not calculated when the total of the ratios of the materials contained in the mixed material does not reach 100%; The combinatorial optimization problem of the material composition that approaches the target value is formulated by an energy function including 2. The information processing system according to claim 1,

3. 3. The information processing system according to claim 1, wherein the formula is the following formula (1). [0010] However, in the formula (1), L is the number of properties to be optimized, N is the number of materials whose physical properties are known, The above D k,i is the kth property value of material i to be optimized, The r i is the following formula (2) which expresses the mixture ratio (composition ratio) of material i by the binary method, [0025] The above D k,0 is the target value of the kth physical property of the mixed material to be optimized, The n i,j is a number "0" or "1" when the mixture ratio of material i is expressed in binary format, Said c j is a coefficient when the mixture ratio of material i is expressed by the binary method, The a k , β is a weighting constant.

4. The optimal solution calculation unit calculates the n n n n n n n n n n n n n n n n n n n n n i,j The combination of the above is calculated as an optimal solution of the material composition that approaches the target value.

4. The information processing system according to claim 3,

5. the input receiving unit receives, from a user, a selection of a target value of at least one physical property, a selection of the material to be used as a material composition of the mixed material from a plurality of materials having known physical property values ​​of the at least one physical property, and a selection of an allowable change range of the target value; The post-processing unit performs post-processing to remove the materials contained in the mixed material in ascending order of mixing ratio from the material composition of the output optimum solution within a range of an allowable change width of the target value.

3. The information processing system according to claim 1 or 2,

6. the input receiving unit receives, from a user, a selection of a target value of at least one physical property, a selection of the material to be used as a material composition of the mixed material from a plurality of materials having known physical property values ​​of the at least one physical property, and a selection of an allowable change range of the target value; The post-processing unit performs post-processing to remove the materials contained in the mixed material from the material composition of the output optimum solution within a range of an allowable change width of the target value in an order selected by a user.

3. The information processing system according to claim 1 or 2,

7. The output control unit displays, on a display device, information including the material composition of the optimal solution calculated by the optimal solution calculation unit and the material composition from which at least one of the materials has been removed by the post-processing unit.

3. The information processing system according to claim 1 or 2,

8. A material composition exploration method executed by an information processing system having an annealing-based calculation device using an Ising model and a material composition exploration device that converts a combinatorial optimization problem of a material composition that asymptotically approaches a target physical property value into an Ising model and causes the calculation device to solve the problem, comprising: an input receiving step of receiving an input of a target value and an allowable change range of at least one physical property; a conversion step of converting a mathematical expression that formulates a combinatorial optimization problem of a material composition that asymptotically approaches the target value from a mixture of materials with known physical property values ​​into the Ising model in a data format that can be used by the computing device; an optimal solution calculation step of calculating an optimal solution of a material composition that asymptotically approaches the target value using the Ising model; a post-processing step of performing a post-processing step of removing the material contained in the mixed material from the material composition of the calculated optimum solution within a range of an allowable change width of the target value; an output control step of outputting the post-processed material composition; A material composition exploration method comprising:

9. A material composition exploration device that is connected to an annealing-based computing device using an Ising model via a communication network, converts a combinatorial optimization problem of a material composition that asymptotically approaches a target physical property value into an Ising model and causes the computing device to solve the problem, an input receiving unit that receives an input of a target value and an allowable change range of at least one physical property; a conversion unit that converts a mathematical expression that formulates a combinatorial optimization problem of a material composition that asymptotically approaches the target value from a mixture of materials with known physical property values ​​into the Ising model in a data format that can be used by the computing device; a linking unit that transmits the converted Ising model to the computing device and receives from the computing device an optimal solution of a material composition that asymptotically approaches the target value calculated by the computing device; a post-processing unit that performs post-processing to remove the material contained in the mixed material from the material composition of the received optimal solution within a range of an allowable change width of the target value; an output control unit that outputs the post-processed material composition; A material composition exploration device comprising:

10. A material composition exploration device that is connected to an annealing-based computing device using an Ising model via a communication network, converts a combinatorial optimization problem of a material composition that asymptotically approaches a target physical property value into an Ising model, and causes the computing device to solve the problem. an input receiving unit that receives an input of a target value and an allowable change range of at least one physical property; a conversion unit that converts a mathematical expression that formulates a combinatorial optimization problem of a material composition that asymptotically approaches the target value from a mixture of materials with known physical property values ​​into the Ising model in a data format that can be used by the computing device; a linking unit that transmits the converted Ising model to the computing device and receives from the computing device an optimal solution of a material composition that asymptotically approaches the target value calculated by the computing device; a post-processing unit that performs post-processing to remove the material contained in the mixed material from the material composition of the received optimal solution within a range of an allowable change width of the target value; an output control unit that outputs the post-processed material composition; A program to function as a

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