Information processing system, material composition search method, material composition search apparatus, and program
The information processing system using an annealing machine with an Ising model addresses combinatorial optimization problems by reducing the number of materials in the optimal material composition, ensuring practical applicability.
Patent Information
- Authority / Receiving Office
- JP · JP
- Patent Type
- Patents
- Current Assignee / Owner
- RESONAC CORP
- Filing Date
- 2022-06-07
- Publication Date
- 2026-05-19
AI Technical Summary
Combinatorial optimization problems, such as determining optimal material compositions, become unsolvable within a realistic timeframe due to the exponential increase in combinations as the number of elements increases, and even when a solution is found, it is difficult to handle in practice due to the large number of materials involved.
An information processing system using an annealing machine with an Ising model to solve combinatorial optimization problems, followed by post-processing to exclude materials within an allowable change width, reducing the number of materials in the solution.
The system effectively reduces the number of materials in the optimal material composition while maintaining target physical properties, making it practical for application.
Smart Images
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Abstract
Description
[Technical Field]
[0001] This disclosure relates to an information processing system, a material composition search method, a material composition search apparatus, and a program. [Background technology]
[0002] For example, there are combinatorial optimization problems that involve selecting the optimal combination from a variety of combinations of elements, such as searching for a material composition with optimal physical properties. Combinatorial optimization problems can become unsolvable within a realistic timeframe because the number of combinations increases exponentially as the number of elements increases. For example, when creating a mixed material by combining 100 different materials in 1% increments, the number of combinations is 5 × 10⁻¹⁰. 58 This is the result.
[0003] As an architecture specifically designed to solve such combinatorial optimization problems, an annealing machine using the Ising model has been proposed. The annealing machine can efficiently solve combinatorial optimization problems that have been transformed into an Ising model.
[0004] Conventionally, techniques for optimizing the thermophysical properties of mixed refrigerants using computer architectures specialized for combinatorial optimization problems are known (see, for example, Non-Patent Document 1). [Prior art documents] [Non-patent literature]
[0005] [Non-Patent Document 1] "Optimization of Thermophysical Properties of Mixed Refrigerants Using a Digital Annealer," Proceedings of the Japan Society of Mechanical Engineers Thermal Engineering Conference 2019, No. 19-303 [October 12-13, 2019, Nagoya] [Overview of the project] [Problems that the invention aims to solve]
[0006] For example, when solving the combinatorial optimization problem of a material composition that approaches (approximates) a target physical property value using an annealing machine, the composition of the mixed material that approaches the target physical property value (the materials contained in the mixed material and the ratio of those materials) is obtained as a result. However, even if the composition of the resulting mixed material approaches the target physical property value, there are cases where it is difficult to handle in practice, such as when the number of materials contained in the mixed material is large.
[0007] An object of the present disclosure is 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 the range of an allowable change width from the optimal solution of the combinatorial optimization problem of a material composition that approaches a target physical property value.
Means for Solving the Problem
[0008] The present disclosure has the following configuration.
[0009] [1] An information processing system having a calculation device of an annealing method using an Ising model and a material composition search device that converts a combinatorial optimization problem of a material composition that approaches a target physical property value into an Ising model and causes the calculation device to solve it, an input reception unit that receives an input of at least one target value of a physical property and an allowable change width, a conversion unit that converts a mathematical formula formulating a combinatorial optimization problem of a material composition that approaches the target value from a mixed material of materials with known physical property values into the Ising model in a data format that can be used by the calculation device, an optimal solution calculation unit that calculates an optimal solution of the material composition that approaches the target value using the Ising model, a post-processing unit that performs post-processing to exclude the materials included in the mixed material within the range of the allowable change width of the target value from the calculated optimal solution of the material composition, an output control unit that outputs the post-processed material composition, characterized by having the above.
[0010] [2] The mathematical 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 easier it is to be calculated as the optimal solution, and the farther the physical property value of the mixed material is from the target value, the more difficult it is to be calculated as the optimal solution, A constraint condition that outputs a value so that it is not calculated as the optimal solution when the total ratio of the materials contained in the mixed material does not reach 100%, By an energy function including, the combinatorial optimization problem of the material composition approaching the target value is formulated. The information processing system according to [1], characterized in that.
[0011] [3] The mathematical formula is the formula (1) below, and the information processing system according to [1] or [2].
[0012]
Number
[0013]
Number
[0014] [4] The optimal solution calculation unit uses the Ising model obtained by converting equation (1) into a data format usable by the computing device to find the n that minimizes the energy function of equation (1). i,j The combination of these elements is calculated as the optimal solution for material composition that asymptotically approaches the target value. The information processing system described in [3] is characterized by the following:
[0015] [5] The input receiving unit receives from the user the selection of a target value for at least one physical property, the selection of a material to be used as the material composition of the mixed material from a plurality of materials whose physical property values for at least one physical property are known, and the selection of an allowable range of change for the target value. The post-processing unit performs a post-processing step from the output optimal solution material composition, removing the materials contained in the mixed material in order of increasing mixing ratio, within the allowable range of change of the target value. An information processing system as described in any one of the following [1] to [3], characterized by:
[0016] [6] The input receiving unit receives from the user the selection of a target value for at least one physical property, the selection of a material to be used as the material composition of the mixed material from a plurality of materials whose physical property values for at least one physical property are known, and the selection of an allowable range of change for the target value. The post-processing unit performs a post-processing step in which it removes the materials contained in the mixed material from the output optimal solution's material composition in the order selected by the user, within the allowable range of change of the target value. An information processing system as described in any one of the following [1] to [3], characterized by:
[0017] [7] The output control unit displays information on a display device that includes 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. An information processing system as described in any one of the following paragraphs [1] to [6], characterized by:
[0018] [8] A material composition search method executed by an information processing system having an annealing computing device using an Ising model and a material composition search device that converts a combinatorial optimization problem of material compositions asymptotically approaching target material properties into an Ising model and has the computing device solve it, An input receiving step that accepts input for a target value and allowable range of change for at least one physical property, A conversion step of converting a mathematical formula that formulates a combinatorial optimization problem for material compositions that asymptotically approach the target value from a mixture of materials with known physical properties into the Ising model in a data format usable by the computing device, An optimal solution calculation step, which uses the Ising model to calculate the optimal solution for a material composition that asymptotically approaches the target value, A post-processing step involves performing a post-processing operation to remove the material contained in the mixed material from the calculated optimal solution material composition, within the allowable range of change of the target value, An output control step that outputs the post-processed material composition, A method for exploring material compositions, characterized by having the following features.
[0019] [9] A material composition search device connected via a communication network to an annealing-type computing device using an Ising model, which converts a combinatorial optimization problem of material compositions that asymptotically approaches target material properties into an Ising model and has the computing device solve it, An input receiving unit that accepts input of a target value and allowable range of change for at least one physical property, A conversion unit that converts a mathematical formula that defines a combinatorial optimization problem of material compositions that asymptotically approach the target value from a mixture of materials with known physical properties into the Ising model in a data format usable by the computing device, A coordinating unit that transmits the converted Ising model to the computing device and receives from the computing device the optimal solution for material composition that asymptotically approaches the target value calculated by the computing device, A post-processing unit performs post-processing on the material composition of the received optimal solution, removing the material contained in the mixed material within the allowable range of change of the target value, An output control unit that outputs the post-processed material composition, A material composition search device characterized by having the following features.
[0020]
[10] A material composition search device is connected via a communication network to an annealing-type computing device using the Ising model, which converts a combinatorial optimization problem of material compositions that asymptotically approach target material properties into an Ising model and has the computing device solve it, An input receiving unit that accepts input of a target value and an allowable range of change for at least one physical property, A conversion unit that converts a mathematical formula that defines a problem of optimizing the combination of material compositions from a mixture of materials with known physical properties to asymptotically approach the target value into the Ising model in a data format usable by the computing device. A coordinating unit transmits the converted Ising model to the computing device and receives from the computing device the optimal solution for the material composition that asymptotically approaches the target value calculated by the computing device. A post-processing unit performs post-processing to remove the material contained in the mixed material from the material composition of the received optimal solution, within the allowable range of change of the target value. An output control unit that outputs the post-processed material composition, A program designed to function as such. [Effects of the Invention]
[0021] According to this disclosure, the number of materials included in the material composition can be reduced within an acceptable range of variation by obtaining the optimal solution to a combination optimization problem of material composition that asymptotically approaches the target material properties. [Brief explanation of the drawing]
[0022] [Figure 1] This is a diagram illustrating an example of an information processing system according to this embodiment. [Figure 2] This is a hardware configuration diagram of an example of a computer according to this embodiment. [Figure 3] This is a diagram illustrating an example of solvent information with known physical properties. [Figure 4] This is a diagram illustrating an example of an information processing system according to this embodiment. [Figure 5]This flowchart shows an example of the processing procedure for the material composition search method of the information processing system according to this embodiment. [Figure 6] This flowchart shows an example of the processing procedure for step S18. [Figure 7] This is a diagram showing an example of the combination and mixing ratio of solvents used. [Figure 8] This is an illustrative image of an example of a material composition search results screen. [Modes for carrying out the invention]
[0023] Next, embodiments of the present invention will be described in detail. However, the present invention is not limited to the following embodiments. In this embodiment, as an example of optimizing a mixed material containing materials with known physical properties, the optimization of a mixed solvent containing a solvent with known physical properties will be described.
[0024] <System Configuration> Figure 1 is a configuration diagram of an example of an information processing system according to this embodiment. The information processing system 1 in Figure 1 includes an annealing computer 10 and a material composition search device 12. The annealing computer 10 and the material composition search device 12 are connected via a communication network 18 such as a local area network (LAN) or the internet, enabling data communication.
[0025] The annealing computer 10 is an annealing machine using the Ising model, and is an example of a computing device using the Ising model's annealing method. The annealing computer 10 may be implemented as a quantum computer, or as a digital annealer (registered trademark), which is a computer architecture that implements the annealing method using digital circuits.
[0026] An annealing machine solves a combinatorial optimization problem reduced to the Ising model by using the convergence behavior of that Ising model. The Ising model is a statistical mechanics model that describes the behavior of magnetic materials, and it has the property that the spin state is updated in such a way that the energy (Hamiltonian) is minimized due to the interaction between the spins of the magnetic material, ultimately resulting in the minimum energy. By reducing the combinatorial optimization problem to the Ising model and finding the state that minimizes the energy, the annealing machine can obtain that state as the optimal solution to the combinatorial optimization problem.
[0027] The material composition search device 12 is an information processing device that can be operated by a user, such as a PC. The material composition search device 12 may also be an information processing terminal that can be operated by a user, such as a tablet or smartphone. The material composition search device 12 accepts input of information necessary to have an annealing machine solve a combinatorial optimization problem reduced to an Ising model, and has the annealing computer 10 solve the Ising model.
[0028] The material composition search device 12 receives the optimal solution to the combinatorial optimization problem solved by the annealing computer 10, and outputs information such as the solvent composition of the optimal solution and the solvent composition after post-processing of the optimal solution as described later, to a display device so that the user can confirm it.
[0029] Note that the information processing system 1 in Figure 1 is just one example, and it may also include a user terminal (not shown) operated by the user, and the user may access and use the material composition search device 12 from the user terminal.
[0030] Furthermore, the annealing computer 10 may be implemented as a cloud computing service. For example, the annealing computer 10 may be available by calling an API (Application Programming Interface) via a communication network 18. Moreover, the annealing computer 10 is not limited to being implemented as a cloud computing service; it may also be implemented on-premises or operated by another company. The annealing computer 10 may be implemented using multiple computers. Needless to say, the information processing system 1 in Figure 1 can have various system configurations depending on the application and purpose.
[0031] <Hardware Configuration> The material composition search device 12 shown in Figure 1 is implemented, for example, by a computer 500 with the hardware configuration shown in Figure 2.
[0032] Figure 2 is a hardware configuration diagram of an example of a computer according to this embodiment. The computer 500 in Figure 2 is equipped with an input device 501, a display device 502, an external interface 503, RAM 504, ROM 505, a CPU 506, a communication interface 507, and an HDD 508, and each is interconnected via bus B. Note that the input device 501 and the display device 502 may be used in a connected configuration.
[0033] The input device 501 includes a touch panel, operation keys and buttons, a keyboard and mouse, etc., used by the user to input various signals. The display device 502 consists of a display such as a liquid crystal or organic EL that displays the screen, and a speaker that outputs sound data such as voice and sound. The communication interface 507 is an interface for the computer 500 to perform data communication.
[0034] Furthermore, HDD508 is an example of a non-volatile storage device that stores programs and data. The programs and data stored include the OS, which is the basic software that controls the entire computer 500, and applications that provide various functions on the OS. Note that computer 500 may use a drive device that uses flash memory as a storage medium (for example, a solid-state drive: SSD) instead of HDD508.
[0035] External I / F 503 is an interface to external devices. External devices include recording media 503a, etc. This allows computer 500 to read and / or write to recording media 503a via external I / F 503. Recording media 503a include flexible disks, CDs, DVDs, SD memory cards, USB memory, etc.
[0036] ROM505 is an example of non-volatile semiconductor memory (storage device) that can retain programs and data even when the power is turned off. ROM505 stores programs and data such as the BIOS, OS settings, and network settings that are executed when the computer 500 starts up. RAM504 is an example of volatile semiconductor memory (storage device) that temporarily holds programs and data.
[0037] The CPU 506 is a computing unit that controls and implements the functions of the entire computer 500 by reading programs and data from storage devices such as ROM 505 and HDD 508 onto RAM 504 and executing processing. The material composition search device 12 according to this embodiment can implement various functions as described later. The hardware configuration of the annealing computer 10 will not be described.
[0038] <Example of a problem to be solved as a combinatorial optimization problem> The following section describes an example of solving a combinatorial optimization problem to determine the mixing ratio (composition ratio) of a mixed solvent whose physical properties are known, so that the desired physical properties asymptotically approach (approximate) the target values.
[0039] For example, in the present embodiment, a plurality of solvents with known physical property values as shown in FIG. 3 are used. FIG. 3 is a configuration diagram of an example of solvent information with known physical property values. The solvent information in FIG. 3 records the physical property values of one or more physical properties for each solvent specified 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 the present embodiment, the target physical property is selected from the solvent information in FIG. 3. Further, the physical property value of the target physical property of the mixed solvent is calculated by the following formula (3).
[0041] Physical property value of the mixed solvent = Σ (physical property value of the single solvent × mixing ratio) … (3) In the present embodiment, the problem to be solved is to search for the mixing ratio of the mixed solvent in which the target physical property approaches the target value by mixing a plurality of types of solvents from the solvents included in the solvent information in FIG. 3, for example, in 1% increments, and regard it as a problem to be solved as a combinatorial optimization problem.
[0042] In the present 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 mathematical formula formulated when there is one target physical property. Formula (1) is an example of a mathematical formula formulated when there are two or more target physical properties.
[0043]
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[0044]
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[0045]
number
[0046] Furthermore, in equation (1) above, E is the energy function (evaluation function), L is the number of target properties to optimize. N is the number of solvents whose physical properties are known. D k,i This is the physical property value of the k-th target property that we want to optimize for solvent i. r i This is the above equation (2) which expresses the mixing ratio of solvent i using the binary method, D k,0 This is the target value of the k-th desired property of the mixed solvent that we want to optimize. α k β is the weighting constant.
[0047] The first term on the right-hand side of equation (4) above decreases as the physical property value of one of the target physical properties of the mixed solvent calculated by equation (3) above approaches the target value of the target physical property. The second term on the right-hand side of equation (4) above is a constraint term that becomes "0" (decreases) when the sum of the mixing ratios (ratios) of the solvents contained in the mixed solvent is 1 (100%).
[0048] Furthermore, the first term on the right-hand side of equation (1) above decreases as the physical properties of the multiple mixed solvents calculated by equation (3) above approach the target values of each individual physical property. The second term on the right-hand side of equation (1) above is a constraint term that becomes "0" (decreases) when the sum of the mixing ratios (ratios) of the solvents contained in the mixed solvent is 1 (100%).
[0049] In the example of equation (2) above, the ratio c required to express the mixing ratio of solvent i depends on how the mixing ratio of solvent i is expressed. j The number of nodes m differs. For example, in the first way of expressing the mixing ratio of solvent i, the ratio c j (c1=2 / 100, c2=2 / 100, ...c 50 It can be expressed with the number of nodes "m=50" as in =2 / 100). In the second way of expressing the mixing ratio, the ratio c j (c1=1 / 100, c2=1 / 100, ...c 100 It can be expressed as the number of nodes "m=100" (e.g., =1 / 100). In the third way of expressing the mixing ratio, the ratio c j This can be expressed with a number of nodes "m=7" as (c1=64 / 100, c2=32 / 100, c3=16 / 100, c4=8 / 100, c5=4 / 100, c6=2 / 100, c7=1 / 100). In addition, in the fourth method of expressing the mixing ratio, the ratio c 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 It can be represented with a node count of "m=10", such as =1 / 1000. For example, the third method of representing the mixing ratio can be used when mixing in 1% increments, and 7 bits are required to represent the mixing ratio of one solvent. Note that when mixing in 0.1% increments, 10 bits per solvent are required, as shown in the fourth method of representing the mixing ratio.
[0050] The formulated equation (4) or equation (1) above is converted into an Ising model in a data format usable by the annealing computer 10, and then transmitted from the material composition search device 12 to the annealing computer 10. The annealing computer 10 uses the Ising model in the usable data format to calculate the optimal solution for the solvent composition.
[0051] The calculated optimal solvent composition is transmitted from the annealing computer 10 to the material composition search device 12. It is expected that even if trace components of the solvent with small mixing ratios are removed, the optimal solvent composition will not deviate significantly from the target values of the desired physical properties. Therefore, the material composition search device 12 of this embodiment determines the allowable range of change for the target value of the desired physical property, and performs post-processing to remove trace components of the solvent with a small mixing ratio, for example, within the allowable range of change for the target value of the desired physical property, from the optimal solution of the solvent composition received from the annealing computer 10. The post-processed solvent composition asymptotically approaches the target value of the desired physical property, and the number of materials contained in that solvent composition becomes small.
[0052] The material composition search device 12 outputs information such as the optimal solvent composition received from the annealing computer 10, and the solvent composition obtained by post-processing that optimal solution, so that the user can review it.
[0053] <Structure> The configuration of the information processing system 1 according to this embodiment will now be described. Figure 4 is a configuration diagram of an example of the information processing system according to this embodiment. Note that parts of the configuration diagram in Figure 4 that are not necessary for the explanation of this embodiment have been omitted as appropriate.
[0054] The annealing computer 10 of the information processing system 1 shown in Figure 4 has a call reception unit 20 and an optimal solution calculation unit 22. The material composition search device 12 has an input reception unit 30, a formulation unit 32, a conversion unit 34, a linkage unit 36, a post-processing unit 37, an output control unit 38, a solvent information storage unit 40, a mathematical formula storage unit 42, and an allowable change range storage unit 44.
[0055] The input receiving unit 30 is an input interface that receives input from the user regarding the target physical property, the target value of that physical property, and the allowable range of change of the target value. The input receiving unit 30 may also receive input from the user regarding the solvent to be used. The input receiving unit 30 stores the input solvent information in the solvent information storage unit 40. The input receiving unit 30 stores the allowable range of change of the input target value in the allowable range of change storage unit 44. In this embodiment, the target value and the allowable range of change are determined for the target physical property. Default values for the allowable range of change may be set in advance for each physical property, and the user may change them as needed.
[0056] The formulation unit 32 accepts the input of either equation (4) or equation (1) above, which formulates the task of searching for a mixing ratio of a mixed solvent in which the target physical properties asymptotically approach the target value by mixing multiple types of solvents from among the solvents included in the solvent information in Figure 3, for example in 1% increments. As described above, equation (4) is an example of a formula formulated when there is one target physical property, and accepts the input of weight constants α and β from the user. Equation (1) is an example of a formula formulated when there are two or more target physical properties, and accepts the weight constants α k It accepts input β.
[0057] The formulation unit 32 accepts the input of the above formula (4) or formula (1) by a program that defines the above formula (4) or formula (1). The formulation unit 32 stores the input formula (4) or formula (1) in the formula storage unit 42.
[0058] If there is one target physical property, the conversion unit 34 converts the target physical property, its target value, and the above equation (4) into an Ising model in a data format usable by the annealing computer 10. If there are two or more target physical properties, the conversion unit 34 converts the target physical property, its target value, and the above equation (1) into an Ising model in a data format usable by the annealing computer 10.
[0059] The linking unit 36 transmits the Ising model converted by the conversion unit 34 to the annealing computer 10. The linking unit 36 also receives the optimal solution calculated by the annealing computer 10.
[0060] The post-processing unit 37 performs post-processing to reduce the number of solvents in the optimal solvent composition calculated by the annealing computer 10, within the allowable range of change of the target value of the desired physical property. For example, the post-processing unit 37 removes trace components of solvents with small mixing ratios from the optimal solvent composition, within the allowable range of change of the target value of the desired physical property. The solvent composition obtained through such post-processing deviates from the target value of the desired physical property compared to the optimal solvent composition, but the number of solvents in the solvent composition is reduced, resulting in a solvent composition that is easier to use in practical applications. The selection of solvents to remove from the optimal solvent composition may be done in order of increasing mixing ratio, or the user may be allowed to select them.
[0061] The output control unit 38 displays the optimal solvent composition received by the linkage unit 36, the solvent composition after post-processing 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 way that is easy for the user to understand, for example, as the mixing ratio of the solvents contained in the mixed solvent. The output control unit 38 may also calculate the physical property values of the target physical properties of the optimal solvent composition received by the linkage unit 36 and the post-processed solvent composition, and display them on the display device 502, allowing the user to confirm the results.
[0062] The call reception unit 20 receives a call from the material composition search device 12 and receives an Ising model converted into a data format usable by the material composition search device 12. The optimal solution calculation unit 22 searches for the optimal mixing ratio of the mixed solvent that asymptotically approaches the target physical properties by determining the state in which the energy (Hamiltonian) of the Ising model received by the call reception unit 20 is minimized. The call reception unit 20 transmits the searched optimal solution to the material composition search device 12.
[0063] Note that the configuration diagram in Figure 4 is just one example. Various configurations of the information processing system 1 according to this embodiment are possible.
[0064] <Processing> Figure 5 is a flowchart showing an example of the processing procedure for the material composition search method of the information processing system according to this embodiment. In step S10, the input receiving unit 30 of the material composition search device 12 receives input from the user of the target physical properties of the mixed solvent to be optimized, the target values of those target physical properties, and the allowable range of change of those target values. Here, it is assumed that the input of the target physical properties δD, δP, and δH, and the target values of those target physical properties (δD0, δP0, δH0) = (18.0, 12.3, 7.2) has been received from the user. The input receiving unit 30 of the material composition search device 12 also receives input from the user of weighting constants α, β or α k It accepts input β.
[0065] In step S12, the input receiving unit 30 of the material composition search device 12 receives input of solvent information to be mixed, for example, as shown in Figure 3. The solvent information shown in Figure 3 is tabular data that stores the physical property values of multiple types of single solvents to be mixed. The input of solvent information may also be performed by selecting a tabular data file stored in the solvent information storage unit 40. Alternatively, the input receiving unit 30 of the material composition search device 12 may accept the selection of single solvents to be mixed and the target physical properties of the mixed solvent from the selected tabular data file.
[0066] In step S14, the formulation unit 32 and conversion unit 34 of the material composition search device 12 use equation (4) or equation (1) above, which formulates the task of searching for a mixing ratio of a mixed solvent in which the desired physical properties asymptotically approach a target value by mixing multiple types of solvents, for example in 1% increments, and the desired physical properties of the mixed solvent to be optimized, which were input in step S10, to obtain an Ising model in a data format usable by the annealing computer 10.
[0067] Furthermore, technologies (libraries) for converting the formulated equation (4) or equation (1) into a quadratic unconstrained binary optimization (QUBO) form of the evaluation function, or into an Ising model in a data format usable by the annealing computer 10, are provided as Web APIs, etc., and are existing technologies. The conversion unit 34 expands the above equation (4) or equation (1) to obtain the matrix element Q of the Ising model shown in equation (5) below. i,j Calculate this matrix element Q i,j This is sent to the annealing computer 10 as parameters 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, which has received the parameters of the Ising model, calculates the n that minimizes the Hamiltonian in equation (4) or equation (1). i,j We find the optimal solution where n is the smallest value of the Hamiltonian in equation (4) or equation (1) above. i,j This represents the optimal mixing ratio of the mixed solvents at which the desired physical properties asymptotically approach the target value.
[0070] Furthermore, as mentioned above, n i,j n is a variable that stores the number "0" or "1" when the mixing ratio of solvent i is expressed using the binary method. i,j The solvent i is in ratio c j If present, it is "1", and solvent i is in ratio c j If it is not included, it will be "0". For example, if solvent i is present at 33%, then in the third method of expressing the mixing ratio above, {n i,j}=(0,1,0,0,0,0,1).
[0071] In step S18, the linkage unit 36 of the material composition search device 12 determines the n that minimizes the Hamiltonian of equation (4) or equation (1) obtained by the annealing computer 10. i,jThe optimal solution is received. The post-processing unit 37 of the material composition search device 12 performs a post-processing step to remove the solvent from the mixed solvent, within the range of the allowable change in the target value of the desired physical property, using a processing procedure such as that shown in Figure 6.
[0072] Figure 6 is a flowchart showing an example of the processing procedure in step S18. In step S30, the post-processing unit 37 obtains information on the optimal solvent composition determined by the annealing computer 10. In step S32, the post-processing unit 37 obtains information on the allowable change range of the target value of the target 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 removing the solvent with the smallest mixing ratio from the solvents included in the solvent composition. In the first step S34, a new solvent composition is created by removing the solvent with the smallest mixing ratio from the solvents included in the optimal solvent composition. In subsequent steps S34, a new solvent composition is created by removing the solvent with the smallest mixing ratio from the new solvent composition created in the previous step S34.
[0074] For example, if the solvents in the solvent composition are {A, B, C, D, E, F, G} and the mixing ratio of each solvent is {46:22:12:9:8:2:1}, the post-processing unit 37 will create a new solvent composition by removing solvent "G", which has the smallest mixing ratio of "1". The mixing ratio of the new solvent composition will be normalized so that the total mixing ratio is 100%.
[0075] In step S36, the post-processing unit 37 calculates the physical properties of the mixed solvent with the new solvent composition. The physical properties of the mixed solvent can be calculated from the above equation (3).
[0076] In step S38, if all the physical properties of the new solvent composition calculated in step S36 are within the acceptable range of change of the target values, the post-processing unit 37 returns to the process in step S34 and then creates a new solvent composition by removing the solvent with the smallest mixing ratio (the solvent with the smallest mixing ratio in the solvent composition created in the previous step S34 process).
[0077] For example, if the solvents in the optimal solvent composition are {A, B, C, D, E, F, G}, and the solvent removed in the previous step S34 was "G", then a new solvent composition is created by removing the next smallest solvent, "F".
[0078] The post-processing unit 37 repeats the processes in steps S34 to S38 until it determines that at least one of the physical properties of the new solvent composition calculated in step S36 is not within the allowable range of change of the target value. Therefore, the optimal solvent composition obtained by the annealing computer 10 has a reduced number of solvents included in that solvent composition, within the allowable range of change of the target value of the target physical property.
[0079] Meanwhile, if at least one of the physical properties of the new solvent composition calculated in step S36 is no longer within the range of the allowable change of the target value, the post-processing unit 37 proceeds to the process in step S40. In step S40, the post-processing unit 37 adopts the solvent composition before the last solvent was removed in the previous process in step S34.
[0080] Note that the flowchart in Figure 6 is just one example. For example, the selection of solvents to be removed in step S34 is not limited to the order of solvents with the smallest mixing ratio; other information may be taken into consideration, or the user may be allowed to make the selection. Also, there may be multiple solvent compositions used in step S40.
[0081] Returning to step S20 of the flowchart in Figure 5, the output control unit 38 outputs the mixed solvent, which is the result of the post-processing in step S18, and the physical properties of the target physical properties of the mixed solvent. Alternatively, the output control unit 38 may output the optimal mixed solvent and the physical properties of the target physical properties of the mixed solvent. The output control unit 38 receives, for example, the optimal solution from the linkage unit 36. i,j From this, it can output information about the mixed solvent, such as the optimal mixed solvent and the physical properties of that mixed solvent.
[0082] Furthermore, the output control unit 38 can output information about the adopted mixed solvent, such as the mixed solvent resulting from step S18, and the physical properties of the target physical properties of the mixed solvent, as shown in Figure 7, for example.
[0083] Figure 7 is a diagram showing an example of the combination and mixing ratio of solvents used. Figure 7 shows an example of information including the solvents contained in the mixed solvent, the mixing ratio of those solvents, and the physical properties of the mixed solvent. The physical properties of the mixed solvent can be calculated from the above equation (3). Also, for example, in the example of Figure 6, by mixing four types of solvents, acetone, cyclohexanone, sulfolane (tetramethylene sulfone), and toluene, in a ratio of 2:1:64:33, the mixed solvent will have target physical properties δD, δP, and δH close to the target values (δD0, δP0, δH0) = (18.0, 12.3, 7.2).
[0084] For example, the output control unit 38 may output information about the adopted mixed solvent to the material composition search result screen 1000, as shown in Figure 8. Figure 8 is an illustrative 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 entered by the user to solve a combinatorial optimization problem reduced to an Ising model using an annealing machine, and a display field 1104 for outputting information about the adopted mixed solvent.
[0085] Display field 1102 shows an example of user-entered information, including the target physical property, the target value of the target physical property, solvent information, weighting constants, and the allowable range of change for the target value. Display field 1104 shows an example of information on the adopted mixed solvent, including the composition of the mixed solvent (types of solvents contained in the mixed solvent and their mixing ratio) and the physical property value of the target physical property.
[0086] By reviewing the material composition search results screen 1000 in Figure 8, users can more easily evaluate the adopted mixed solvent. Furthermore, if the user wishes to explore other mixed solvents after reviewing the material composition search results screen 1000 in Figure 8, they can, for example, readjust the weight constants included in equation (4) or equation (1) above, and then follow the flowchart shown in Figure 5. The weight constants can be readjusted manually by the user, or they can be automatically optimized using a program.
[0087] Furthermore, the material composition search results screen 1000 in Figure 8 may display information on the optimal solution's mixed solvent along with information on the adopted mixed solvent. By displaying information on the optimal solution's mixed solvent along with information on the adopted mixed solvent, users can more easily compare and evaluate the mixed solvent obtained as the optimal solution with the adopted mixed solvent.
[0088] Furthermore, if the user, after reviewing the material composition search results screen 1000, wishes to change the number (types) of solvents included in the adopted mixed solvent, they can, for example, adjust the allowable range of change for the target value and then reprocess the flowchart shown in Figure 6.
[0089] For example, if a user wants to reduce the number of solvents included in a mixed solvent, they can increase the allowable range of variation for the target value mentioned above. This makes it easier to adopt a solvent composition with fewer solvents, even if the desired physical properties deviate somewhat from the target value.
[0090] Furthermore, if, for example, the user wants to increase the number of solvents included in the mixed solvent, they can reduce the allowable range of change in the target value mentioned above. This makes it easier to adopt a solvent composition with properties close to the target value, even if the number of solvents in the mixed solvent is large.
[0091] The material composition search results screen 1000 in Figure 8 is just an example, and may include fields for adjusting the weight constants included in equation (4) or equation (1) above, fields for adjusting the allowable range of change of the target value, a re-search button to execute a process to re-search for the optimal solution using equation (4) or equation (1) after the weight logarithm has been readjusted, and a post-processing button to execute the flowchart process shown in Figure 6 using the allowable range of change of the target value after readjustment. The material composition search results screen 1000 in Figure 8 may also be displayed including the configuration diagram in Figure 7.
[0092] The information on the selected mixed solvent can be used to control, for example, a mixed solvent generator that produces a mixed solvent by specifying the solvents to be mixed and their mixing ratio. Furthermore, the physical properties of the mixed solvent produced by the above-mentioned mixed solvent generator can be evaluated using an evaluation device. Therefore, the information on the selected mixed solvent can be compared with the physical properties of the mixed solvent produced by the mixed solvent generator by specifying the information on that 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 an acceptable range of change by obtaining the optimal solution to the combination optimization problem of the composition of the mixed solvent that asymptotically approaches the target value of the desired physical property.
[0094] As described above, this embodiment can be understood to be capable of various modifications to its form and details without departing from the spirit and scope of the claims.
[0095] Although 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. 2021-097382 filed with the Japan Patent Office on June 10, 2021, the entire contents of which are incorporated herein by reference. [Explanation of symbols]
[0096] 1. Information Processing System 10. Annealing-type computers 12 Material composition exploration device 18. Communication Networks 20 Call Reception Department 22 Optimal Solution Calculation Unit 30 Input reception section 32 Formulation part 34 Conversion Unit 36. Liaison Department 37 Post-processing 38 Output control unit 40 Solvent information storage unit 42 Formula Memory Unit 44 Allowable change range storage unit 502 Display device
Claims
1. An information processing system comprising: an annealing-type computing device using the Ising model; and a material composition search device that converts a combinatorial optimization problem of material compositions asymptotically approaching target material properties into an Ising model and has the computing device solve it; An input receiving unit that accepts input of a target value and allowable range of change for at least one physical property, A conversion unit that converts a mathematical formula that defines a combinatorial optimization problem for material compositions that asymptotically approach the target value from a mixture of materials with known physical properties into the Ising model in a data format usable by the computing device, An optimal solution calculation unit that calculates the optimal solution for a material composition that asymptotically approaches the target value using the Ising model, A post-processing unit that calculates physical property values based on the formula for the material composition after removing the material based on the calculated optimal solution, determines whether the physical property values meet the allowable range of change of the target value, identifies the material to be excluded from the materials included in the mixed material within the allowable range of change of the target value, and performs post-processing to remove the identified material, An output control unit that outputs the post-processed material composition, An information processing system characterized by having the following features.
2. The above formula is, A cost function that outputs values such that the physical properties of the mixed material become smaller as they approach the target value, A constraint condition that outputs a value that is not calculated as the optimal solution when the sum of the ratios of the materials contained in the aforementioned mixed material does not equal 100%, The problem of optimizing the combination of material compositions that asymptotically approach the target value is formulated using an energy function that includes the above. The information processing system according to claim 1, characterized by the following:
3. An information processing system comprising: an annealing-type computing device using an Ising model; and a material composition search device that converts a combinatorial optimization problem of material compositions asymptotically approaching target material properties into an Ising model and has the computing device solve it, An input receiving unit that accepts input of a target value and allowable range of change for at least one physical property, A conversion unit that converts a mathematical formula that defines a combinatorial optimization problem for material compositions that asymptotically approach the target value from a mixture of materials with known physical properties into the Ising model in a data format usable by the computing device, An optimal solution calculation unit that calculates the optimal solution for a material composition that asymptotically approaches the target value using the Ising model, A post-processing unit performs a post-processing operation to remove the material contained in the mixed material from the calculated optimal solution material composition within the allowable range of change of the target value, An output control unit that outputs the post-processed material composition, It has, The information processing system according to claim 1 or 2, wherein the aforementioned formula is the following formula (1). [Math 1] However, in formula (1) above, The aforementioned L is the number of physical properties to be optimized. The aforementioned N is the number of materials whose physical properties are known. The aforementioned D k,i This is the property value of the k-th property of material i that we want to optimize. The aforementioned r i This is the following equation (2), which expresses the mixing ratio (composition ratio) of material i using the binary method: [Math 2] The aforementioned D k,0 This is the target value for the k-th physical property of the mixed material that we want to optimize. The aforementioned n i,j This is the number "0" or "1" when the mixing ratio of material i is expressed using the binary method. Said c j This is a coefficient when the mixing ratio of material i is expressed using the binary method. The aforementioned α k β is the weighting constant.
4. The optimal solution calculation unit uses the Ising model obtained by converting equation (1) into a data format usable by the computing device to determine the n that minimizes the energy function of equation (1). i,j The combination of these elements is calculated as the optimal solution for material composition that asymptotically approaches the target value. The information processing system according to claim 3, characterized by the following:
5. The input receiving unit receives from the user the selection of a target value for at least one physical property, the selection of a material to be used as the material composition of the mixed material from a plurality of materials whose physical property values for at least one physical property are known, and the selection of an acceptable range of change for the target value. The post-processing unit performs a post-processing step from the output optimal solution material composition, removing the materials contained in the mixed material in order of increasing mixing ratio, within the allowable range of change of the target value. An information processing system according to claim 1 or 3, characterized by the above.
6. The input receiving unit receives from the user the selection of a target value for at least one physical property, the selection of a material to be used as the material composition of the mixed material from a plurality of materials whose physical property values for at least one physical property are known, and the selection of an acceptable range of change for the target value. The post-processing unit performs a post-processing step in which it removes the materials contained in the mixed material from the output optimal solution's material composition in the order selected by the user, within the allowable range of change of the target value. An information processing system according to claim 1 or 3, characterized by the above.
7. The output control unit displays information on a display device that includes 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. An information processing system according to claim 1 or 3, characterized by the above.
8. A material composition search method executed by an information processing system having an annealing-type computing device using an Ising model, and a material composition search device that converts a combinatorial optimization problem of material compositions asymptotically approaching target material properties into an Ising model and has the computing device solve it, wherein An input receiving step that accepts input for a target value and an allowable range of change for at least one physical property, A conversion step of converting a mathematical formula that formulates a combinatorial optimization problem for material compositions that asymptotically approach the target value from a mixture of materials with known physical properties into the Ising model in a data format usable by the computing device, An optimal solution calculation step, which uses the Ising model to calculate the optimal solution for a material composition that asymptotically approaches the target value, A post-processing step which involves calculating physical property values based on the formula for the material composition after removing the material based on the calculated optimal solution, determining whether the physical property values meet the allowable range of change of the target value, identifying the material to be excluded from the materials included in the mixed material within the allowable range of change of the target value, and performing a post-processing step which involves removing the identified material, An output control step that outputs the post-processed material composition, A method for exploring material compositions, characterized by having the following features.
9. A material composition search device connected via a communication network to an annealing-type computing device using the Ising model, which converts a combinatorial optimization problem of material compositions that asymptotically approaches target material properties into an Ising model and has the computing device solve it, An input receiving unit that accepts input of a target value and allowable range of change for at least one physical property, A conversion unit that converts a mathematical formula that defines a combinatorial optimization problem for material compositions that asymptotically approach the target value from a mixture of materials with known physical properties into the Ising model in a data format usable by the computing device, A coordinating unit that transmits the converted Ising model to the computing device and receives from the computing device the optimal solution for material composition that asymptotically approaches the target value calculated by the computing device, A post-processing unit calculates physical property values based on the formula for the material composition after removing the material based on the received optimal solution, determines whether the physical property values meet the allowable range of change of the target value, identifies the material to be excluded from the materials included in the mixed material within the allowable range of change of the target value, and performs post-processing to remove the identified material. An output control unit that outputs the post-processed material composition, A material composition search device characterized by having the following features.
10. A material composition search device is connected via a communication network to an annealing-type computing device using the Ising model. This device converts a combinatorial optimization problem of material compositions that asymptotically approach target material properties into an Ising model and has the computing device solve it. An input receiving unit that accepts input of a target value and an allowable range of change for at least one physical property, A conversion unit that converts a mathematical formula that defines a combination optimization problem of material compositions from a mixture of materials with known physical properties that asymptotically approach the target value into the Ising model in a data format usable by the computing device. A coordinating unit transmits the converted Ising model to the computing device and receives from the computing device the optimal solution for the material composition that asymptotically approaches the target value calculated by the computing device. A post-processing unit calculates physical property values based on the formula for the material composition after removing the material based on the received optimal solution, determines whether the physical property values meet the allowable range of change of the target value, identifies the material to be excluded from the mixed material within the allowable range of change of the target value, and performs post-processing to remove the identified material. An output control unit that outputs the post-processed material composition, A program designed to function as such.