CN117521421A - Dielectric composite design method, device, equipment, computing system and medium - Google Patents

Dielectric composite design method, device, equipment, computing system and medium Download PDF

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CN117521421A
CN117521421A CN202410008080.9A CN202410008080A CN117521421A CN 117521421 A CN117521421 A CN 117521421A CN 202410008080 A CN202410008080 A CN 202410008080A CN 117521421 A CN117521421 A CN 117521421A
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dielectric
qubo
dielectric composite
filling
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CN117521421B (en
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李舟
韩娟
文凯
马寅
曹崇育
李文新
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Guangdong Dawan District Aerospace Information Research Institute
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Abstract

The application relates to a dielectric composite design method, device, equipment, computing system and medium, wherein the method comprises the following steps: establishing a QUBO model according to data, design optimization targets and decision space of the dielectric composite material, wherein the QUBO model comprises the following components: a first term for approximating the dielectric constant of the dielectric composite material at each wavelength to a target value, a second term for approximating the property of the dielectric composite material to a target property, and a third term carrying a second penalty factor for satisfying a constraint term, wherein the constraint condition of the constraint term is used for selecting a unique composite scheme, and the composite scheme comprises a filling material, a filling rate of the filling material and a base material; and solving the QUBO model based on quantum computation, so as to obtain the composition and the corresponding filling proportion of the dielectric composite material with the optimal dielectric function. By implementing the embodiment of the application, the calculation efficiency of the dielectric composite material design optimization can be improved, and the accuracy of a calculation result is improved.

Description

Dielectric composite design method, device, equipment, computing system and medium
Technical Field
The application relates to a dielectric composite material design method, a device, equipment, a computing system and a medium, belonging to the field of composite material design optimization.
Background
Current computing techniques are based on optimization algorithms of conventional computers, including precision solution algorithms (branch-and-bound algorithms, etc.) based on integer programming and mixed integer programming mathematical models, heuristic algorithms, etc.
Currently, large-scale calculations are performed on classical supercomputers, the speed of which is determined by moore's law for logic large-scale integrated circuits. In the future, as large data volumes increase dramatically, conventional computers will not be able to handle these large-scale calculations, as the scaling of gate lengths for logic large-scale integrated circuits will almost reach manufacturing limits.
Therefore, the prior art is difficult to calculate a large-scale dielectric composite material design, and as the scale of the problem increases (the types of materials increase and the filling rate precision increases), the calculation complexity increases exponentially, the solving difficulty increases sharply, and the prior solving technology is difficult to finish solving in a short time.
Disclosure of Invention
In view of the foregoing, embodiments of the present application provide a dielectric composite design method, apparatus, quantum computer device, computing system, and readable storage medium. The method can solve the technical problem that the design optimization of the complex dielectric material is difficult to calculate in the prior art.
The first aspect of the embodiment of the application discloses a dielectric composite material design method, which comprises the following steps:
establishing a QUBO model according to data, design optimization targets and decision space of the dielectric composite material, wherein the QUBO model comprises the following components:
a first term for approximating the dielectric constants of the dielectric composite materials at respective wavelengths to target values,
a second item for approximating a property of the dielectric composite to a target property,
the third item carries a second punishment coefficient and is used for meeting a constraint item, wherein the constraint condition of the constraint item is used for selecting a unique composite scheme, and the composite scheme comprises a filling material, the filling rate of the filling material and a base material;
and solving the QUBO model based on quantum computation, so as to obtain the composition and the corresponding filling proportion of the dielectric composite material with the optimal dielectric function.
Optionally, the second term carries a first penalty coefficient.
Optionally, the QUBO model specifically includes:
；
wherein,indicating wavelength +.>A target dielectric constant below; />Indicating the filling material at a wavelength +.>A lower dielectric constant; />Indicating the wavelength of the base material +.>A lower dielectric constant;xrepresenting decision variables to be optimized;Krepresenting a set of all materials combined with mixing ratios; />Indicating that the first is selectedkSeed material combination and corresponding proportion; />Representing a set of wavelengths;representing the filling proportion of the filling material; />Representing a first penalty factor; />Representing a second penalty factor; ->And->Respectively representing the relevant material properties of the filling material and the base material to be considered in the optimization process;>representing an optimization objective for the material properties.
Optionally, the solving the QUBO model based on quantum computation, to obtain the composition and the corresponding filling ratio of the dielectric composite material with the optimal dielectric function, includes:
converting the QUBO model into an Ising model;
and solving a variable value corresponding to the global optimal solution according to the Ising model so that the service node recovers the composition and the corresponding filling proportion of the dielectric composite material with the optimal dielectric function according to the variable value.
Further, the solving the variable value corresponding to the global optimal solution according to the Ising model includes:
and receiving the matrix coefficient of the Ising model in the form of light pulse to obtain the variable value.
Optionally, the solving the QUBO model based on quantum computation, to obtain the composition and the corresponding filling ratio of the dielectric composite material with the optimal dielectric function, includes:
operating a QAOA quantum circuit, and executing multiple transformations on the QUBO model to obtain a quantum state;
calculating expected values of the QUBO model using the quantum states in a classical computer;
and calculating an approximate solution of the target problem according to the expected value, wherein the approximate solution is the composition and the corresponding filling proportion of the dielectric composite material with the optimal dielectric function.
A second aspect of an embodiment of the present application discloses a dielectric composite design apparatus, the apparatus comprising:
an establishing module for establishing a QUBO model according to data, design optimization targets and decision space of the dielectric composite material, wherein the QUBO model comprises:
a first term for approximating the dielectric constants of the dielectric composite materials at respective wavelengths to target values,
a second item for approximating a property of the dielectric composite to a target property,
the third item carries a second punishment coefficient and is used for meeting a constraint item, wherein the constraint condition of the constraint item is used for selecting a unique composite scheme, and the composite scheme comprises a filling material, the filling rate of the filling material and a base material;
and the solving module is used for solving the QUBO model based on quantum computation so as to obtain the composition and the corresponding filling proportion of the dielectric composite material with the optimal dielectric function.
A third aspect of the embodiments of the present application discloses a quantum computer device, including a quantum memory and a quantum processor, where the quantum memory stores a computer program, and when executed by the quantum processor, implements any one of the dielectric composite design methods disclosed in the embodiments of the present application.
The fourth aspect of the embodiment of the application discloses a computing system, which comprises a processor and a memory for storing a program executable by the processor, wherein when the processor executes the program stored by the memory, any one of the dielectric composite material design methods disclosed in the embodiment of the application is realized.
A fifth aspect of the embodiments of the present application discloses a readable storage medium storing a program that, when executed by a processor, implements any of the dielectric composite design methods disclosed in the embodiments of the present application.
Compared with the related art, the embodiment of the application has the following beneficial effects:
based on the characteristics of the dielectric composite material, the embodiment of the application is used for carrying out acceleration solving on the problem by designing a combination optimization algorithm suitable for quantum computing, so that the computing efficiency of the dielectric composite material design optimization is improved, and the accuracy of a computing result is improved.
Drawings
In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the following description will briefly explain the drawings used in the embodiments or the description of the prior art, and it is obvious that the drawings in the following description are only some embodiments of the present application, and other drawings can be obtained according to the structures shown in these drawings without inventive effort for a person skilled in the art.
Fig. 1 is a flowchart illustrating a method for designing a dielectric composite material according to an embodiment of the present application.
FIG. 2 is a graph showing a wavelength comparison of the optimized dielectric and the target dielectric provided in the embodiments of the present application.
Fig. 3 is a schematic diagram of a dielectric composite design device according to an embodiment of the present application.
Fig. 4 is a structural example diagram of a quantum computer device according to an embodiment of the present application.
Fig. 5 is a structural example diagram of a computing system according to an embodiment of the present application.
Detailed Description
For the purpose of making the objects, technical solutions and advantages of the embodiments of the present application more apparent, the technical solutions of the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present application, and it is apparent that the described embodiments are some embodiments of the present application, but not all embodiments, and all other embodiments obtained by a person of ordinary skill in the art without making any inventive effort based on the embodiments in the present application are all within the scope of protection of the present application.
In the description and claims of this application, the terms "first," "second," and the like are used for distinguishing between similar objects and not for describing a specified sequence or order. It is to be understood that the data so used may be interchanged, as appropriate, such that embodiments of the present application may be implemented in sequences other than those illustrated or described herein, and that the "first" and "second" distinguished objects generally are of the same type and not limited to the number of objects, such as the first object may be one or more.
It should be noted that, in the embodiments of the present application, words such as "exemplary" or "such as" are used to mean serving as an example, instance, or illustration. Any embodiment or design described herein as "exemplary" or "such as" is not necessarily to be construed as preferred or advantageous over other embodiments or designs. Rather, the use of words such as "exemplary" or "such as" is intended to present related concepts in a concrete fashion.
Some of the terms or terminology that appear in describing the embodiments of the present application are applicable to the following explanation:
1. the dielectric material (dielectric material) is an electrically insulating material that can be used to fabricate capacitors.
2. Dielectric composite materials refer to materials formed by compounding two or more dielectric materials, and the dielectric function of the materials meets specific property requirements.
3. The design optimization of the dielectric composite material refers to selecting the optimal material composition and mixing ratio so that the property of the dielectric composite material meets the specific property requirement as far as possible, namely, the corresponding dielectric function reaches the optimal, thereby realizing the reverse design of the dielectric composite material.
4. The combined optimization is a mathematical optimization technology, and consists of discrete decision variables, objective functions and constraint conditions, and aims to solve the optimal values of the objective functions and the corresponding optimal solutions. If the objective function is quadratic and without constraints and the decision variables can only take 0 or 1, then this combined optimization is called a quadratic unconstrained binary optimization model (Quadratic Unconstrained Binary Optimization, QUBO). The QUBO model form can be solved by a quantum annealing machine or a special quantum computer such as coherent i Xin Ji.
The composite materials that can be formed by the combination of the various dielectric materials are various. At present, the human is skilled to grasp that the materials of the preparation process only occupy a very small part, and a very large number of unknown materials wait for the human to find. The new materials need longer period from the concept of proposal to the final formation of the mature preparation scheme through continuous trial and error, and the rapid optimization of the dielectric composite materials is expected to realize the efficient discovery and development of the new materials. Based on the above, the embodiment of the application provides a dielectric composite material design method, a device, a quantum computer device, a computing system and a readable storage medium, which use a special quantum computer to accelerate solving of a dielectric composite material design problem, thereby improving computing efficiency and realizing accurate and rapid optimization of a dielectric composite material. The specific implementation scheme is as follows:
as shown in fig. 1, fig. 1 is a flowchart of a method for designing a dielectric composite material according to an embodiment of the present application. The method for designing the dielectric composite material can comprise the following steps:
s101, establishing a QUBO model according to data of the dielectric composite material, a design optimization target and a decision space.
In this embodiment, first, the set and data used for the dielectric composite design optimization problem are defined as follows:
a set of candidate dielectric materials I is defined, such as i= { material 1, material 2, … }.
A set of wavelengths Λ is defined, such as Λ= {1000nm, 2000nm, … }.
A set F of fill factors is defined, such as f= {0.01, 0.02, … }.
Definition of the definitionFor the dielectric constant of material I e I at wavelength lambda e lambda.
Definition of the definitionThe target dielectric constants for the composite dielectric materials are as close as possible at the wavelength lambda epsilon lambda.
Pi is defined as a property of the material i that is relevant, such as ductility, quality, etc.
Ptar is defined as the target value to which the properties of the composite dielectric material are as close as possible.
Then, setting decision space and targets of dielectric composite material design optimization problems, specifically comprising:
1. the decision space for the dielectric composite design optimization problem is to select a specific material combination and corresponding fill ratio from the candidate materials.
2. The goal of the dielectric composite design optimization problem is to have the dielectric constants of the dielectric composite at each wavelength as close as possible to the target dielectric constant while meeting the properties of the dielectric composite close to the target value.
Finally, establishing a QUBO model according to the set and the data and the decision space and the target, wherein the method specifically comprises the following steps:
optionally, the QUBO model includes:
the first term is used to bring the dielectric constant of the dielectric composite material at each wavelength close to a target value.
A second term for approximating a property of the dielectric composite to a target property.
And thirdly, carrying a second penalty coefficient, wherein the second penalty coefficient is used for meeting a constraint term, and the constraint condition of the constraint term is used for selecting a unique composite scheme, and the composite scheme comprises a filling material, the filling rate of the filling material and a base material.
Optionally, the QUBO model includes:
the first term is used to bring the dielectric constant of the dielectric composite material at each wavelength close to a target value.
The second term carries a first penalty factor for approximating the properties of the dielectric composite to target properties.
And thirdly, carrying a second penalty coefficient, wherein the second penalty coefficient is used for meeting a constraint term, and the constraint condition of the constraint term is used for selecting a unique composite scheme, and the composite scheme comprises a filling material, the filling rate of the filling material and a base material.
It should be noted that the second penalty factor is necessary, and has a large value and a strong constraint to determine an optimal material combination and corresponding filling ratio.
Specifically, to meet the design optimization requirements of the dielectric composite material, a binary variable x is defined k Any value of index k represents a particular material design scheme, i.e., choice of filler material, filler rate of filler material, and choice of base material, x if the scheme is implemented k Taking 1, otherwise taking 0. Because only one composite scheme can be selected, the following constraints exist:
；
the objective function of the QUBO model is:
；
wherein,indicating wavelength +.>A lower target dielectric constant (including real and imaginary parts); />Indicating the filling material at a wavelength +.>Lower dielectric constant (including real and imaginary parts); />Indicating the wavelength of the base material +.>Lower dielectric constant (including real and imaginary parts);xrepresenting decision variables to be optimized;Krepresenting a set of all materials combined with mixing ratios; />Indicating that the first is selectedkSeed material combination and corresponding proportion; />Representing a set of wavelengths; />Representing the filling proportion of the filling material;representing the first penalty factor, ">Representing a second penalty factor for introducing a constraint, the larger the value, the better the constraint>And->Respectively representing the relevant material properties of the filling material and the base material to be considered in the optimization process, in order ∈ ->To optimize the objective.
The purpose of step S101 is to correspond the optimization objective to a particular QUBO form suitable for application-specific quantum computing solutions.
S102, solving the QUBO model based on quantum computation, and further obtaining the composition and the corresponding filling proportion of the dielectric composite material with the optimal dielectric function.
The QUBO model of this embodiment is suitable for use in a quantum annealing machine, a special quantum computer such as coherent i Xin Ji (Coherent Ising Machine, CIM), and the like. The physical machine is implemented by taking CIM based on a degenerate optical parametric oscillator (DegenerateOptical Parametric Oscillator, DOPO) as an example, which is a mixed quantum computing system consisting of an optical part and an electrical part. The optical portion comprises a laser, an amplifier, a periodically poled lithium niobate crystal (Periodically Poled Lithium Niobate, PPLN) and a fiber loop. The laser uses a femtosecond pulse fiber laser and is matched with an amplifier system. The amplified laser is first frequency doubled by using PPLN crystal. The frequency-doubled laser is used as a pumping source to synchronously pump a PPLN crystal in an optical fiber loop, so as to form degenerate optical parametric oscillation, and hundreds of oscillation pulses can exist in the optical fiber loop at the same time. The electrical part includes FPGA (FieldProgrammable Gate Array), AD/DA (digital analog/digital conversion) and a phase detecting part. The laser output in the optical fiber loop and the laser with the fundamental frequency are measured by a phase detector, so that the phase of the output light can be tested. And the FPGA is matched with the high-speed AD/DA to measure and feedback control the optical pulse.
Unlike classical computers running on semiconductor integrated circuits, CIM uses laser pulses in an optical fiber as qubits for computation. In DOPO, the pump light is incident on the nonlinear optical crystal to split two beams of light, the polarization direction of the two beams of light is the same, the frequency is half of that of the pump light, and the pump light is in a compressed state and can be used as a qubit. When the power of the pumping light is increased gradually and exceeds the oscillation threshold, the generated light becomes a coherent state, the phase of the light is divided into two states (phase 0 state and pi state), and the phase can be correspondingly set to be +/-1 of spin at the moment so as to solve the optimization problem.
Example (1), a material design was obtained as follows:
and S11, the user side transmits data such as dielectric constants to the server side, and the server side establishes a QUBO model based on the received data.
S12, the server drives the converted Ising matrix coefficient into a coherent Italian Xin Ji in a light pulse mode.
S13, the coherent iferous Xin Ji rapidly obtains the variable value corresponding to the function in the global optimal solution.
And S14, the coherent Yi Xin Ji transmits the variable value back to the server.
S15, the server receives the data and restores the corresponding material design scheme.
In other embodiments, the model may also be solved by a quantum approximation optimization algorithm (Quantum Approximate Optimization Algorithm, QAOA). QAOA is a hybrid algorithm of classical and quantum that can solve the combinatorial optimization problem on gate-based quantum computers. Based on the QUBO form, it can be converted into an Ising model and corresponding biggest cut problem. The objective function may be expressed as maximization. Defining two rotating unitary matrices>And. After repeating the operation P times, the following new state can be obtained:
；
example (2), a material design was obtained as follows:
and S21, the user side transmits data such as dielectric constants to the server side, and the server side establishes a QUBO model based on the received data.
S22, constructing a QAOA quantum circuit, wherein the circuit comprises trainable parameters.
S23, initializing parameters in the circuit, and obtaining an initial quantum state in the quantum computer.
S24, operating the quantum circuit, and executing P times of transformation on an objective function, namely a QUBO model to obtain a quantum state。
S25, utilizing quantum states in classical computersThe expected value of the objective function is calculated.
S26, repeating the steps S23-S25 for a plurality of times, namely measuring the same group of parameters gamma and beta for a plurality of times, so as to obtain quantum state distribution.
S27, optimizing parameters in the line by using grid search. And repeating the steps S23-S26 for a group of new parameters gamma and beta, and selecting the target value with the largest value after quantum state distribution is obtained.
S28, calculating an approximate solution of the target problem according to the result of the step S25, wherein the approximate solution is the composition of the dielectric composite material with the optimal dielectric function and the corresponding filling proportion, namely the material design scheme.
As shown in fig. 2, the real part wavelength of the dielectric is close to the real part wavelength of the target dielectric, and the imaginary part wavelength is not coincident, but the error is still in an acceptable range, and the optimization accuracy of the filling rate can be improved by adjusting the filling rate.
Those skilled in the art will appreciate that all or part of the steps in a method implementing the above embodiments may be implemented by a program to instruct related hardware, and the corresponding program may be stored in a computer readable storage medium.
It should be noted that although the method operations of the above embodiments are depicted in the drawings in a particular order, this does not require or imply that the operations must be performed in that particular order or that all illustrated operations be performed in order to achieve desirable results. Rather, the depicted steps may change the order of execution. Additionally or alternatively, certain steps may be omitted, multiple steps combined into one step to perform, and/or one step decomposed into multiple steps to perform.
As shown in fig. 3, fig. 3 is a schematic diagram of a dielectric composite design apparatus according to an embodiment of the present application. The dielectric composite design device is applied to quantum computer equipment or a computing system and can comprise the following modules:
an establishing module 301 for establishing a QUBO model based on data of the dielectric composite material, design optimization objectives and decision space, the QUBO model comprising:
a first term for approximating the dielectric constants of the dielectric composite materials at respective wavelengths to target values,
a second item for approximating a property of the dielectric composite to a target property,
the third item carries a second punishment coefficient and is used for meeting a constraint item, wherein the constraint condition of the constraint item is used for selecting a unique composite scheme, and the composite scheme comprises a filling material, the filling rate of the filling material and a base material;
the solution module 302 is configured to solve the QUBO model based on quantum computation, thereby obtaining a composition and a corresponding filling ratio of the dielectric composite material with the optimal dielectric function.
As shown in fig. 4, fig. 4 is a structural diagram of a quantum computer device provided in an embodiment of the present application. The quantum computer device may include a quantum processor 402 and a quantum memory 403 connected by a system bus 401. The quantum memory stores a computer program that when executed by the quantum processor implements any of the dielectric composite design methods disclosed in the embodiments of the present application.
As shown in fig. 5, fig. 5 is a block diagram of a computing system according to an embodiment of the present application. The computing system may include a processor 502, memory, input devices 503, display devices 504, and a network interface 505 connected by a system bus 501. The processor 502 is configured to provide computing and control capabilities, and the memory includes a nonvolatile storage medium 506 and an internal memory 507, where the nonvolatile storage medium 506 stores an operating system, a computer program and a database, and the internal memory 507 provides an environment for the operating system and the computer program in the nonvolatile storage medium 506 to run, and when the computer program is executed by the processor 502, any of the dielectric composite material design methods disclosed in the embodiments of the present application are implemented.
The embodiment of the application discloses a storage medium. The storage medium is a computer readable storage medium storing a computer program which, when executed by a processor, implements any of the dielectric composite design methods disclosed in the embodiments of the present application.
The computer readable storage medium of the present embodiment may be a computer readable signal medium or a computer readable storage medium, or any combination of the two. The computer readable storage medium can be, for example but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the foregoing. More specific examples of the computer-readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.
In this embodiment, a computer-readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. In the present embodiment, however, the computer-readable signal medium may include a data signal propagated in baseband or as part of a carrier wave, with a computer-readable program embodied therein. Such a propagated data signal may take any of a variety of forms, including, but not limited to, electro-magnetic, optical, or any suitable combination of the foregoing. A computer readable signal medium may also be any computer readable storage medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device. A computer program embodied on a computer readable storage medium may be transmitted using any appropriate medium, including but not limited to: electrical wires, fiber optic cables, RF (radio frequency), and the like, or any suitable combination of the foregoing.
The computer readable storage medium may be written in one or more programming languages, including an object oriented programming language such as Java, python, C ++ and conventional procedural programming languages, such as the C-language or similar programming languages, or combinations thereof for performing the present embodiments. The program may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any kind of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or may be connected to an external computer (for example, through the Internet using an Internet service provider).
In summary, the embodiment of the application is based on the characteristics of the dielectric composite material, and the combination optimization algorithm suitable for quantum computing is designed, so that the problem is solved in an accelerating way by using the quantum computer, the computing efficiency of the dielectric composite material design optimization is improved, and the accuracy of the computing result is improved.
The above-mentioned embodiments are only preferred embodiments of the present invention, but the protection scope of the present invention is not limited thereto, and any person skilled in the art can make equivalent substitutions or modifications according to the technical solution and the inventive concept of the present invention within the scope of the present invention disclosed in the present invention patent, and all those skilled in the art belong to the protection scope of the present invention.

Claims (10)

1. A method of designing a dielectric composite, the method comprising:
establishing a QUBO model according to data, design optimization targets and decision space of the dielectric composite material, wherein the QUBO model comprises the following components:
a first term for approximating the dielectric constants of the dielectric composite materials at respective wavelengths to target values,
a second item for approximating a property of the dielectric composite to a target property,
the third item carries a second punishment coefficient and is used for meeting a constraint item, wherein the constraint condition of the constraint item is used for selecting a unique composite scheme, and the composite scheme comprises a filling material, the filling rate of the filling material and a base material;
and solving the QUBO model based on quantum computation, so as to obtain the composition and the corresponding filling proportion of the dielectric composite material with the optimal dielectric function.
2. The method of claim 1, wherein the second term carries a first penalty coefficient.
3. Method according to claim 2, characterized in that said QUBO model comprises in particular:
；
wherein,indicating wavelength +.>A target dielectric constant below; />Indicating the filling material at a wavelength +.>A lower dielectric constant; />Indicating the wavelength of the base material +.>A lower dielectric constant;xrepresenting decision variables to be optimized;Krepresenting a set of all materials combined with mixing ratios; />Indicating that the first is selectedkSeed material combination and corresponding proportion; />Representing a set of wavelengths;representing the filling proportion of the filling material; />Representing a first penalty factor; />Representing a second penalty factor; ->And->Respectively representing the relevant material properties of the filling material and the base material to be considered in the optimization process;>representing an optimization objective for the material properties.
4. A method according to any one of claims 1 to 3, wherein said solving said QUBO model based on quantum computation, thereby obtaining the composition and corresponding filling ratio of a dielectric composite material having an optimal dielectric function, comprises:
converting the QUBO model into an Ising model;
and solving a variable value corresponding to the global optimal solution according to the Ising model so that the service node recovers the composition and the corresponding filling proportion of the dielectric composite material with the optimal dielectric function according to the variable value.
5. The method of claim 4, wherein the solving the variable value corresponding to the global optimal solution according to the Ising model includes:
and receiving the matrix coefficient of the Ising model in the form of light pulse to obtain the variable value.
6. A method according to any one of claims 1 to 3, wherein said solving said QUBO model based on quantum computation, thereby obtaining the composition and corresponding filling ratio of a dielectric composite material having an optimal dielectric function, comprises:
operating a QAOA quantum circuit, and executing multiple transformations on the QUBO model to obtain a quantum state;
calculating expected values of the QUBO model using the quantum states in a classical computer;
and calculating an approximate solution of the target problem according to the expected value, wherein the approximate solution is the composition and the corresponding filling proportion of the dielectric composite material with the optimal dielectric function.
7. A dielectric composite design apparatus, the apparatus comprising:
an establishing module for establishing a QUBO model according to data, design optimization targets and decision space of the dielectric composite material, wherein the QUBO model comprises:
a first term for approximating the dielectric constants of the dielectric composite materials at respective wavelengths to target values,
a second item for approximating a property of the dielectric composite to a target property,
the third item carries a second punishment coefficient and is used for meeting a constraint item, wherein the constraint condition of the constraint item is used for selecting a unique composite scheme, and the composite scheme comprises a filling material, the filling rate of the filling material and a base material;
and the solving module is used for solving the QUBO model based on quantum computation so as to obtain the composition and the corresponding filling proportion of the dielectric composite material with the optimal dielectric function.
8. A quantum computer device comprising a quantum memory and a quantum processor, the quantum memory storing a computer program which when executed by the quantum processor implements the method of any one of claims 1 to 5.
9. A computing system comprising a processor and a memory for storing a program executable by the processor, the processor implementing the method of any one of claims 1 to 6 when executing the program stored in the memory.
10. A readable storage medium storing a program, wherein the program, when executed by a processor, implements the method of any one of claims 1 to 6.
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