Structure determination method and device of photonic device, equipment, medium and product
By initializing and adjusting the element values of the matrix in the photonic device design and converting them into a double-layer numerical optimization problem, the balance between performance and manufacturing constraints in traditional design is solved, and design efficiency and manufacturability are improved.
Patent Information
- Application Number
- CN202411147952.6
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2024-08-20
- Publication Date
- 2024-12-20
AI Technical Summary
In the optimization process, traditional reverse design methods are difficult to maximize the performance of photonic devices while meeting manufacturing constraints. After introducing constraints, the number of optimization iterations and simulation computing resources are increased, which limits design efficiency.
By initializing the first matrix and the second matrix, adjusting the element values of the second matrix to meet the preset requirements of the target matrix, and adjusting the first matrix when the performance is not met, converting it into a double-layer numerical optimization problem, ensuring that every iteration Meet manufacturing constraints and achieve rapid search and optimization convergence.
Maximize the performance of photonic devices while meeting constraints, reduce the computing resources and simulation time of reverse design, and improve manufacturability and yield.
Smart Images
Figure CN119167452A_ABST
Abstract
Description
Technical Field
[0001] The present application belongs to the field of photonic device design, and in particular, relates to a method, device, equipment, medium and product for determining the structure of a photonic device. Background Art
[0002] The design of integrated photonic devices usually relies on complex physical processes. In order to realize the automation of photonic device design, the gradient-based optimization method of integrated photonic device reverse design based on topology optimization technology can be used to automatically generate the topological shapes of different photonic devices through numerical optimization. Integrated photonic devices generated by topology optimization technology usually have the characteristics of low loss, large bandwidth, and compactness.
[0003] However, the topological shapes of integrated photonic devices obtained through inverse design are usually very complex. For example, the commonly used topology optimization scheme based on the variable density method introduces manufacturing constraints during the performance optimization process, which usually causes the device to converge to a structure that meets the manufacturing constraints prematurely and ignores the performance. It can be seen that traditional schemes are difficult to maximize the performance of photonic devices while satisfying the constraints. On the other hand, the introduction of constraints in the later stage of continuous optimization often increases the number of optimization iterations, simulation computing resources and time overhead, which greatly limits the efficiency of reverse design. Summary of the invention
[0004] The embodiments of the present application provide a method, device, equipment, medium and product for determining the structure of a photonic device, which can maximize the performance of the photonic device while satisfying constraint conditions.
[0005] On the one hand, an embodiment of the present application provides a method for determining the structure of a photonic device, comprising:
[0006] Initializing a first matrix and a second matrix based on a preset structural condition of the photonic device;
[0007] Adjusting the element values of the second matrix so that the target matrix meets the first preset requirement; the first preset requirement includes that the matrix similarity value between the target matrix and the first matrix meets the similarity requirement, and the constraint parameter value of the corresponding photonic device meets the manufacturing constraint condition; there is a corresponding relationship between the target matrix and the second matrix, and the element values of the target matrix correspond to the materials of the corresponding points of the photonic device;
[0008] Determining whether the photonic device corresponding to the target matrix meets the performance conditions;
[0009] In the case where the photonic device does not meet the performance condition, the element values of the first matrix are adjusted, and the step of returning to adjust the element values of the second matrix so that the corresponding target matrix meets the first preset requirement is returned;
[0010] In the case where the photonic device meets the performance condition, the structure of the photonic device is determined based on the target matrix.
[0011] On the other hand, adjusting the element values of the second matrix so that the corresponding target matrix meets the first preset requirement includes:
[0012] Based on the second matrix, determining the corresponding target matrix;
[0013] Based on the target matrix and the first matrix, obtaining a first result output by a constraint objective function; the constraint objective function includes a similarity function and a constraint function, and the first result includes the matrix similarity value and the constraint parameter value;
[0014] If the first result does not meet the first preset requirement, adjust the element values of the second matrix, and return to the step of determining the corresponding target matrix based on the second matrix; until the first result meets the first preset requirement.
[0015] On the other hand, based on the second matrix, determining the corresponding target matrix includes:
[0016] Performing convolution operation filtering on the second matrix based on a preset two-dimensional convolution kernel to obtain a third matrix;
[0017] Based on a preset projection function, the third matrix is projected to obtain the target matrix.
[0018] On the other hand, the first result is the sum of the matrix similarity value and the constraint parameter value; the first preset requirement includes that the first result is greater than a preset threshold;
[0019] Based on the target matrix and the first matrix, obtaining a first result output by the constraint objective function includes:
[0020] Input the target matrix and the first matrix into the similarity function to obtain the matrix similarity value; and input the target matrix into the constraint function to obtain the constraint parameter value;
[0021] The first result is obtained by adding the matrix similarity value and the constraint parameter value.
[0022] On the other hand, the similarity function is used to calculate any one or any combination of the following:
[0023] KL divergence, JS divergence, cosine similarity, Euclidean distance, Minkowski distance, and Chebyshev distance.
[0024] On the other hand, the constraint parameter value includes any one or any combination of the following: minimum characteristic size, minimum spacing, and minimum radius of curvature of the photonic device.
[0025] In another aspect, the performance condition includes an energy loss value of the photonic device being less than a loss threshold;
[0026] The determining whether the photonic device corresponding to the target matrix meets the performance condition includes:
[0027] Based on the target matrix, obtaining an energy loss value of the photonic device output by a performance objective function;
[0028] When the energy loss value is less than the loss threshold, determining that the photonic device meets the performance condition;
[0029] When the energy loss value is not less than the loss threshold, it is determined that the photonic device does not meet the performance condition.
[0030] On the other hand, based on the target matrix, obtaining the energy loss value of the photonic device output by the performance objective function includes:
[0031] Projecting the target matrix to obtain a scattering matrix;
[0032] Based on the scattering matrix, the energy loss value of the corresponding photonic device is determined.
[0033] On the other hand, when the photonic device does not meet the performance condition, adjusting the element value of the first matrix includes:
[0034] Calculating the derivative of the performance objective function with respect to the first matrix;
[0035] The element values of the first matrix are adjusted based on the derivative.
[0036] On the other hand, an embodiment of the present application provides a device for determining the structure of a photonic device, the device comprising:
[0037] An initialization module, used for initializing the first matrix and the second matrix based on a preset structural condition of the photonic device;
[0038] A first adjustment module is used to adjust the element values of the second matrix so that the target matrix meets a first preset requirement; the first preset requirement includes that the matrix similarity value between the target matrix and the first matrix meets the similarity requirement, and the constraint parameter value of the corresponding photonic device meets the manufacturing constraint condition; there is a corresponding relationship between the target matrix and the second matrix, and the element values of the target matrix correspond to the materials of the corresponding points of the photonic device;
[0039] A judgment module, used to judge whether the photonic device corresponding to the target matrix meets the performance condition; if the photonic device does not meet the performance condition, trigger the second adjustment module; if the photonic device meets the performance condition, trigger the determination module;
[0040] The second adjustment module is used to adjust the element values of the first matrix and return to the step of adjusting the element values of the second matrix so that the corresponding target matrix meets the first preset requirement;
[0041] The determination module is used to determine the structure of the photonic device based on the target matrix.
[0042] In another aspect, an embodiment of the present application provides a device for determining the structure of a photonic device, the device comprising: a processor and a memory storing computer program instructions;
[0043] When the processor executes the computer program instructions, the method for determining the structure of the photonic device as described above is implemented.
[0044] On the other hand, an embodiment of the present application provides a computer-readable storage medium, on which computer program instructions are stored. When the computer program instructions are executed by a processor, the structure determination method of the photonic device as described above is implemented.
[0045] On the other hand, an embodiment of the present application provides a computer program product. When instructions in the computer program product are executed by a processor of an electronic device, the electronic device executes the structure determination method of the photonic device as described above.
[0046] A method for determining the structure of a photonic device in an embodiment of the present application, first, based on the preset structural conditions of the photonic device, initialize the first matrix and the second matrix. Then, fix the first matrix first, and adjust the element values of the second matrix so that the corresponding target matrix meets the first preset requirement. That is, the matrix similarity value between the target matrix and the first matrix meets the similarity requirement, and the constraint parameter value of the corresponding photonic device meets the manufacturing constraint condition. Next, determine whether the photonic device corresponding to the target matrix meets the performance condition; if the photonic device does not meet the performance condition, adjust the element value of the first matrix, and return to the step of adjusting the element value of the second matrix so that the corresponding target matrix meets the first preset requirement; if the photonic device meets the performance condition, determine the structure of the photonic device based on the target matrix. It can be seen that the scheme proposed in the embodiment of the present application converts the inverse design problem of the photonic device into a two-layer numerical optimization problem, so that in the entire process of the inverse design optimization of the photonic device, the photonic device obtained in each performance optimization iteration can meet the given minimum manufacturing constraint condition, and achieve rapid search and optimization convergence, so that the final design can maximize the performance of the photonic device while meeting the constraint condition. This method can be simultaneously applied to micro-nano processing such as photolithography and electron beam lithography systems, reducing the required computing resources and simulation time for reverse design, and improving the manufacturability and yield of photonic devices obtained through reverse design. BRIEF DESCRIPTION OF THE DRAWINGS
[0047] In order to more clearly illustrate the technical solution of the embodiments of the present application, the following is a brief introduction to the drawings required for use in the embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.
[0048] Figure 1 A schematic diagram of a process of determining a structure of a photonic device provided by an embodiment of the present application is shown;
[0049] Figure 2 The hierarchical relationship between two numerical optimization problems provided by an embodiment of the present application is shown;
[0050] Figure 3 A schematic diagram showing the optimal solutions of the upper-level optimization problem and the lower-level optimization problem independent variables provided by one embodiment of the present application is shown;
[0051] Figure 4 The overall iterative process of the optimization algorithm provided by one embodiment of the present application is shown;
[0052] Figure 5 A schematic diagram of the structure of a device for determining the structure of a photonic device provided in an embodiment of the present application is shown;
[0053] Figure 6A schematic diagram of the hardware structure of a device for determining the structure of a photonic device provided in an embodiment of the present application is shown. DETAILED DESCRIPTION
[0054] The features and exemplary embodiments of various aspects of the present application will be described in detail below. In order to make the purpose, technical solutions and advantages of the present application clearer, the present application will be further described in detail below in conjunction with the accompanying drawings and specific embodiments. It should be understood that the specific embodiments described herein are only intended to explain the present application, rather than to limit the present application. For those skilled in the art, the present application can be implemented without the need for some of these specific details. The following description of the embodiments is only to provide a better understanding of the present application by illustrating the examples of the present application.
[0055] It should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, the elements defined by the statement "include..." do not exclude the presence of other identical elements in the process, method, article or device including the elements.
[0056] Reverse design is one of the key technologies in the development of photonic design automation. In traditional reverse design methods, the introduction of manufacturing constraints during the optimization process usually causes the device to converge to a structure that meets the manufacturing constraints too early and ignores the performance. On the other hand, manufacturing constraints can cause the performance of the device to drop rapidly in the later stages of optimization. It can be seen that traditional solutions are difficult to achieve optimal device performance while meeting the manufacturing constraint requirements.
[0057] In order to solve the problems of the traditional solution, the embodiment of the present application provides a method, device, equipment, medium and product for determining the structure of a photonic device. The method for determining the structure of a photonic device provided by the embodiment of the present application is first introduced below. Figure 1 FIG. 1 is a flow chart of a method for determining the structure of a photonic device provided by an embodiment of the present application; Figure 1 As shown, the method includes the following steps: S101 to S105.
[0058] S101: Initializing a first matrix and a second matrix based on a preset structural condition of a photonic device.
[0059] First determine the structural conditions of the photonic device to be designed, such as the size of the photonic device, the number of input and output ports, etc. Then initialize the corresponding first matrix and second matrix (such as a matrix of 300*300). In fact, the purpose of the first matrix and the second matrix is to affect the target matrix. The final photonic device design structure is one-to-one corresponding to the target matrix, and one target matrix corresponds to one device design. The first matrix is the independent variable of the function corresponding to the performance adjustment, and the second matrix is the independent variable of the function corresponding to the manufacturing constraint condition.
[0060] In actual design, the element value of the target matrix corresponds to the material of the corresponding point of the photonic device. A design is equivalent to a two-dimensional image. For example, the corresponding point of the photonic device can be set to silicon, and the element of the corresponding point of the matrix is 1; the corresponding point of the photonic device is set to silicon dioxide, and the element of the corresponding point of the matrix is 0. In actual situations, the element values in the matrix are not all 0 or 1, but numbers between 0 and 1. The closer the number is to which side, the greater the probability of the corresponding value.
[0061] S102: Adjust element values of the second matrix so that the target matrix meets the first preset requirement.
[0062] On the basis of satisfying the preset structural conditions, the element values of the target matrix are adjusted to obtain a device design that meets the manufacturing constraints and maximizes performance. Because the target matrix corresponds to the second matrix, the actual adjustment is to adjust the second matrix, and then obtain the target matrix after a series of processing (such as binarization). At this time, the target matrix represents the structure of the photonic device.
[0063] When adjusting the second matrix here, the first matrix will be fixed unchanged, and the target matrix will meet the first preset requirement. In the scheme proposed in this embodiment, the first preset requirement includes that the matrix similarity value between the target matrix and the first matrix meets the similarity requirement, and the constraint parameter value of the corresponding photonic device meets the manufacturing constraint condition.
[0064] S101 mentions that the first matrix is the independent variable of the function corresponding to the performance adjustment, and the second matrix is the independent variable of the function corresponding to the manufacturing constraint condition. After initializing the first matrix or adjusting the first matrix to optimize the performance once, the first matrix is fixed unchanged, and then the second matrix is adjusted, that is, the photonic device meets the manufacturing constraint condition under the current performance design.
[0065] Because the target matrix and the second matrix have a corresponding relationship, when the second matrix is adjusted, the target matrix will change accordingly. The first preset requirement mentioned above includes that the matrix similarity value between the target matrix and the first matrix meets the similarity requirement, that is, the first matrix determines the overall shape of the device. In addition, the first preset requirement also includes that the constraint parameter value of the corresponding photonic device meets the manufacturing constraint conditions, that is, it is achieved that the device can meet the manufacturing constraint conditions without affecting the performance of the device.
[0066] S103: Determine whether the photonic device corresponding to the target matrix meets the performance requirements.
[0067] After optimizing the second matrix, the device can meet the manufacturing constraints, and the target matrix is similar to the first matrix this time. At this time, it is determined whether the photonic device corresponding to the target matrix meets the performance conditions. The performance condition can be the energy loss value of the photonic device. A loss threshold can be set in advance. When the energy loss value is less than the loss threshold, it is determined that the photonic device meets the performance condition; when the energy loss value is not less than the loss threshold, it is determined that the photonic device does not meet the performance condition. The final photonic device design can have a smaller energy loss.
[0068] S104: When the photonic device does not meet the performance condition, adjust the element values of the first matrix, and return to the step of adjusting the element values of the second matrix so that the corresponding target matrix meets the first preset requirement.
[0069] If the photonic device corresponding to the target matrix does not meet the performance conditions, the first matrix is adjusted with the goal of optimizing the device performance, and the process returns to S102 to continue the step of optimizing the second matrix. That is, each time the performance is optimized, the second matrix is adjusted so that the final target matrix meets the manufacturing constraints. This achieves fast optimization convergence, optimizes the performance while ensuring that the device meets the manufacturing constraints, and avoids the situation where the constraints are considered again after the performance is optimized and the performance is affected again.
[0070] S105: When the photonic device meets the performance conditions, determine the structure of the photonic device based on the target matrix.
[0071] After multiple iterations, the photonic device meets the performance conditions because the manufacturing constraints have been verified before the verification conditions. Therefore, the target matrix at this time is the required target matrix, and the structure of the photonic device is determined based on the target matrix, which enables the photonic device to maximize performance while meeting the constraints.
[0072] The solution proposed in this embodiment can play a key role in photonic design automation algorithms and tools, and simulation software, including automatic design of high-performance integrated photonic devices, and improvement of the manufacturability of reverse design devices. Photonic integrated devices with excellent performance are expected to be used in data centers, optical communications, optical sensing, optical imaging, and other applications that require optical technology.
[0073] A method for determining the structure of a photonic device according to an embodiment of the present application, first, based on the preset structural conditions of the photonic device, initialize the first matrix and the second matrix. Then, fix the first matrix first, and adjust the element values of the second matrix so that the corresponding target matrix meets the first preset requirement. That is, the matrix similarity value between the target matrix and the first matrix meets the similarity requirement, and the constraint parameter value of the corresponding photonic device meets the manufacturing constraint condition. Next, determine whether the photonic device corresponding to the target matrix meets the performance condition; if the photonic device does not meet the performance condition, adjust the element value of the first matrix, and return to the step of adjusting the element value of the second matrix so that the corresponding target matrix meets the first preset requirement; if the photonic device meets the performance condition, determine the structure of the photonic device based on the target matrix.
[0074] It can be seen that the scheme proposed in the embodiment of the present application converts the reverse design problem of photonic devices into a two-layer numerical optimization problem, so that in the entire process of reverse design optimization of photonic devices, the photonic devices obtained in each performance optimization iteration can meet the given minimum manufacturing constraints, and achieve fast search and optimization convergence, so that the final design can maximize the performance of photonic devices while meeting the constraints. This method can be applied to micro-nano processing such as lithography and electron beam lithography systems at the same time, reducing the required computing resources and simulation time for reverse design, and improving the manufacturability and yield of photonic devices obtained by reverse design.
[0075] It can be seen that the scheme proposed in the embodiment of the present application converts the photonic device reverse design problem into a two-layer numerical optimization problem, so that in the entire process of photonic device reverse design optimization, the photonic device obtained in each performance optimization iteration can meet the given minimum manufacturing constraints, and achieve fast search and optimization convergence, so that the final design can maximize the performance of the photonic device while meeting the constraints. This method can be applied to micro-nano processing such as lithography and electron beam straightening at the same time to improve the manufacturability and yield of photonic devices obtained by reverse design.
[0076] Figure 2 The hierarchical relationship between two numerical optimization problems provided by an embodiment of the present application is shown; Figure 2 As shown in the figure, the inverse design method includes solving two numerical optimization problems, and the two numerical optimization problems have a hierarchical relationship, namely, the optimization performance problem (the upper optimization problem argminF(b* )) and satisfy the manufacturing constraints (the lower optimization problem b * =argminf(a,b)).
[0077] The upper optimization problem relies on a performance objective function that measures the performance of the device. In each iteration of the upper optimization problem, the lower optimization problem needs to be solved to a local optimal solution. That is, the parameters of the performance objective function are the local optimal solution of the lower optimization problem, or are functions that depend on the local optimal solution of the lower optimization problem.
[0078] The lower-level optimization problem depends on both the independent variables of the upper-level optimization problem (the first matrix) and the independent variables of the lower-level optimization problem (the second matrix). The constraint objective function of the lower-level optimization problem consists of two parts: a similarity function and a constraint function that measures the degree to which the design violates the design constraints. The parameters of the similarity function include both the first matrix and the target matrix; and the constraint function that measures the degree to which the design violates the design constraints, the corresponding manufacturing constraints include the minimum feature size, the minimum spacing, and the minimum radius of curvature.
[0079] In practical applications, the specific implementation process is related to the specific optimized photonic integrated device, including but not limited to optical couplers, optical beam splitters, optical polarization rotators, optical wavelength division multiplexers, optical mode converters, and optical active modulators, etc. This method can be optimized for any photonic integrated device or optoelectronic integrated device.
[0080] Figure 3 A schematic diagram showing the optimal solution of the upper optimization problem and the lower optimization problem independent variable provided by an embodiment of the present application is shown; Figure 3 As shown in the figure, the objective function f of the lower optimization problem consists of two parts, one of which is the device design after projection. The similarity between the target matrix and the independent variable a (first matrix) of the upper optimization problem is obtained by parameterized calculation using the variable density method commonly used in topology optimization. This process requires first obtaining the device design The process of obtaining the device design is as follows: First, the lower optimization problem independent variable b is convolved with a two-dimensional convolution kernel h to obtain the filtered design variable The process can be expressed as:
[0081]
[0082] Next, a projection function is used to obtain the projected device design The process can be expressed as:
[0083]
[0084] The similarity can be calculated using the KL divergence function, that is, calculating the upper optimization problem independent variable a and The KL divergence between In practical applications, the similarity function is used to calculate any one or any combination of the following: KL divergence, JS divergence, cosine similarity, Euclidean distance, Minkowski distance, and Chebyshev distance. In practical applications, the above similarity types can be selected according to needs, which can ensure that the obtained similarity is more accurate and further ensure that the device performance will not be affected while optimizing the constraint parameter value.
[0085] Another part of the underlying optimization problem is to measure the device design The function of the degree of violation of the design rules, as a specific implementation method, adopts the geometric constraints used in topology optimization based on the density method, and its calculation method can be expressed as:
[0086]
[0087] in:
[0088]
[0089] The constraint objective function of the lower constraint problem can be written as:
[0090]
[0091] In practical applications, the constraint parameter value may include any one or any combination of the following: minimum characteristic size, minimum spacing, and minimum radius of curvature of the photonic device. Through the above constraint parameters, the photonic device finally designed can meet the production conditions.
[0092] In each iteration of the upper optimization problem, it is necessary to solve the lower optimization problem to the local optimal solution b * At this time b * It uniquely represents a device design, which can be substituted into the upper optimization problem to evaluate the performance of the device design, and the upper optimization problem independent variable a is updated by calculating the derivative of the upper optimization problem objective function F with respect to the upper optimization problem independent variable a. It can be seen that when the photonic device does not meet the performance conditions, the derivative of the performance objective function with respect to the first matrix can be calculated, and the element value of the first matrix can be adjusted based on the derivative to optimize the performance of the photonic device. Then the iterative optimization is repeated until the device loss reflected by the objective function F meets the required requirements, and the algorithm iteration is stopped.
[0093] Figure 4 The overall iterative process of the optimization algorithm provided by one embodiment of the present application is shown; Figure 4 As shown, the following steps are included:
[0094] S401: Initialize the upper optimization problem independent variable a and the lower optimization problem independent variable b.
[0095] That is, the first matrix and the second matrix are initialized according to the preset structural conditions of the device.
[0096] S402: Solve the lower-level optimization problem to a local optimal solution.
[0097] Find the local optimal solution b * , that is, adjusting the element values of the second matrix so that the target matrix meets the first preset requirement.
[0098] S403: Substitute the local optimal solution into the upper optimization objective function and check convergence.
[0099] That is, determine whether the photonic device corresponding to the target matrix meets the performance requirements.
[0100] S404: Calculate the derivative of the upper-level problem objective function with respect to the upper-level optimization problem independent variable.
[0101] S405: Update the upper optimization problem independent variable a.
[0102] That is, when the photonic device does not meet the performance condition, the element values of the first matrix are adjusted.
[0103] First, the optimization of the lower layer problem is explained. The embodiment of the present application provides a specific optimization solution, that is, iterative optimization of the second matrix. The specific process of adjusting the second matrix so that the corresponding target matrix meets the first preset requirement is as follows: based on the second matrix, determine the corresponding target matrix; then, based on the target matrix and the first matrix, obtain the first result output by the constraint objective function. The constraint objective function includes a similarity function (such as ) and a constraint function (such as formula (3)), the first result includes a matrix similarity value and a constraint parameter value. If the first result does not meet the first preset requirement, adjust the element value of the second matrix, and return to the step of determining the corresponding target matrix based on the second matrix; until the first result meets the first preset requirement.
[0104] It should be noted that the embodiment of the present application does not limit the specific content of the first result and the first preset requirement, and can be set according to actual needs. When adjusting the element value of the second matrix, the method used is also not specifically required, and the optimization adjustment can be performed in the direction of satisfying the manufacturing constraint condition.
[0105] The embodiment of the present application can quickly solve the second matrix so that the target matrix meets the first preset requirement through iterative optimization.
[0106] In the above embodiment, before determining the matrix similarity value and the constraint parameter value, it is necessary to first determine the corresponding target matrix based on the second matrix. The embodiment of the present application provides a specific implementation scheme, which can perform convolution operation filtering on the second matrix based on a preset two-dimensional convolution kernel (such as formula (1)) to obtain a third matrix. Then, based on a preset projection function (such as formula (2)), the third matrix is projected to obtain a target matrix.
[0107] The embodiment of the present application provides a conversion process between a second matrix and a target matrix. Through this method, a target matrix that characterizes the design of a photonic device can be quickly obtained.
[0108] The above embodiment mentioned that the first result includes a matrix similarity value and a constraint parameter value, but does not limit the specific combination thereof. The embodiment of the present application provides a specific solution, in which the first result is the sum of the matrix similarity value and the constraint parameter value; the first preset requirement includes that the first result is greater than a preset threshold. Here, the preset threshold can be set according to actual conditions.
[0109] The specific process of obtaining the first result output by the constraint objective function includes: inputting the target matrix and the first matrix into the similarity function to obtain the matrix similarity value; and inputting the target matrix into the constraint function to obtain the constraint parameter value. Then, the matrix similarity value and the constraint parameter value are added to obtain the first result (such as formula (5)).
[0110] In the solution proposed in the embodiment of the present application, the constraint objective function specifically includes a similarity function and a constraint function. The first result is the sum of the two function values. By combining the two functions and iteratively optimizing the second matrix, the optimization efficiency can be accelerated.
[0111] The above embodiment does not limit the specific content of the performance conditions. This embodiment provides a specific solution, and the performance conditions include that the energy loss value of the photonic device is less than the loss threshold; that is, the output of the performance objective function F of the upper-level optimization problem is the energy loss of the device.
[0112] Correspondingly, when judging whether the photonic device corresponding to the target matrix meets the performance conditions, firstly, based on the target matrix, the energy loss value of the photonic device output by the performance objective function is obtained. When the energy loss value is less than the loss threshold, it is determined that the photonic device meets the performance conditions; when the energy loss value is not less than the loss threshold, it is determined that the photonic device does not meet the performance conditions.
[0113] In the embodiment of the present application, the performance parameter value includes the energy loss value of the photonic device, and the performance condition includes that the energy loss value of the photonic device is less than the loss threshold. By reducing the energy loss value of the photonic device, a photonic device that better meets actual usage requirements can be obtained.
[0114] Here, a specific scheme for obtaining the energy loss value of a photonic device is provided. The target matrix can be projected to obtain a scattering matrix, and then the energy loss value of the corresponding photonic device can be determined based on the scattering matrix. This scheme converts the target matrix into a scattering matrix through projection processing, so that the corresponding performance parameter value can be accurately determined.
[0115] In order to solve the above technical problems, the present application also provides a device for determining the structure of a photonic device. Figure 5 A schematic diagram of the structure of a device for determining the structure of a photonic device provided in an embodiment of the present application is shown; Figure 5 As shown, the device includes the following modules:
[0116] An initialization module 501 is used to initialize the first matrix and the second matrix based on a preset structural condition of the photonic device;
[0117] The first adjustment module 502 is used to adjust the element values of the second matrix so that the target matrix meets the first preset requirement; the first preset requirement includes that the matrix similarity value between the target matrix and the first matrix meets the similarity requirement, and the constraint parameter value of the corresponding photonic device meets the manufacturing constraint condition; there is a corresponding relationship between the target matrix and the second matrix, and the element value of the target matrix corresponds to the material of the corresponding point of the photonic device;
[0118] A judgment module 503 is used to judge whether the photonic device corresponding to the target matrix meets the performance condition; if the photonic device does not meet the performance condition, the second adjustment module 504 is triggered, and if the photonic device meets the performance condition, the determination module 505 is triggered;
[0119] A second adjustment module 504, configured to adjust the element values of the first matrix and return to the step of adjusting the element values of the second matrix so that the corresponding target matrix meets the first preset requirement;
[0120] The determination module 505 is used to determine the structure of the photonic device based on the target matrix.
[0121] In some embodiments, the first adjustment module 502 is specifically configured to:
[0122] Based on the second matrix, determining a corresponding target matrix;
[0123] Based on the target matrix and the first matrix, a first result output by the constraint objective function is obtained; the constraint objective function includes a similarity function and a constraint function, and the first result includes a matrix similarity value and a constraint parameter value;
[0124] When the first result does not meet the first preset requirement, adjust the element values of the second matrix, and return to the step of determining the corresponding target matrix based on the second matrix; until the first result meets the first preset requirement.
[0125] In some embodiments, the first adjustment module 502 is specifically configured to:
[0126] Performing convolution operation filtering on the second matrix based on a preset two-dimensional convolution kernel to obtain a third matrix;
[0127] Based on a preset projection function, the third matrix is projected to obtain a target matrix.
[0128] In some embodiments, the first adjustment module 502 is specifically configured to:
[0129] Input the target matrix and the first matrix into the similarity function to obtain the matrix similarity value; and input the target matrix into the constraint function to obtain the constraint parameter value;
[0130] The matrix similarity value and the constraint parameter value are added to obtain a first result.
[0131] In some embodiments, the determination module 503 is specifically configured to:
[0132] Based on the target matrix, the energy loss value of the photonic device output by the performance target function is obtained;
[0133] When the energy loss value is less than the loss threshold, determining that the photonic device meets the performance condition;
[0134] When the energy loss value is not less than the loss threshold, it is determined that the photonic device does not meet the performance condition.
[0135] In some embodiments, the determination module 503 is specifically configured to:
[0136] Project the target matrix to obtain the scattering matrix;
[0137] Based on the scattering matrix, the energy loss value of the corresponding photonic device is determined.
[0138] In some embodiments, the second adjustment module 504 is specifically configured to:
[0139] Calculating the derivative of the performance objective function with respect to the first matrix;
[0140] The values of elements of the first matrix are adjusted based on the derivatives.
[0141] The device provided in the embodiment of the present application is the same as the method in the above embodiment, so both have the same embodiments and beneficial effects, which will not be repeated here.
[0142] Figure 6 FIG. 1 is a schematic diagram showing the hardware structure of a device for determining the structure of a photonic device provided in an embodiment of the present application; Figure 6As shown, the device for determining the structure of a photonic device may include a processor 601 and a memory 602 storing computer program instructions.
[0143] Specifically, the processor 601 may include a central processing unit (CPU), or an application specific integrated circuit (ASIC), or may be configured to implement one or more integrated circuits of the embodiments of the present application.
[0144] The memory 602 may include a large capacity memory for data or instructions. By way of example and not limitation, the memory 602 may include a hard disk drive (HDD), a floppy disk drive, a flash memory, an optical disk, a magneto-optical disk, a magnetic tape, or a universal serial bus (USB) drive or a combination of two or more of these. In appropriate cases, the memory 602 may include a removable or non-removable (or fixed) medium. In appropriate cases, the memory 602 may be inside or outside the integrated gateway disaster recovery device. In a specific embodiment, the memory 602 is a non-volatile solid-state memory.
[0145] The memory 602 may include a read-only memory (ROM), a random access memory (RAM), a magnetic disk storage media device, an optical storage media device, a flash memory device, an electrical, optical or other physical / tangible memory storage device. Thus, in general, the memory includes one or more tangible (non-transitory) computer-readable storage media (e.g., a memory device) encoded with software including computer-executable instructions, and when the software is executed (e.g., by one or more processors), it is operable to perform the operations described with reference to the method according to an aspect of the present disclosure.
[0146] The processor 601 implements any one of the photonic device structure determination methods in the above embodiments by reading and executing computer program instructions stored in the memory 602 .
[0147] In one example, the device for determining the structure of a photonic device may further include a communication interface 603 and a bus 604. The processor 601, the memory 602, and the communication interface 603 are connected via the bus 604 and communicate with each other.
[0148] The communication interface 603 is mainly used to implement communication between various modules, devices, units and / or equipment in the embodiments of the present application.
[0149] Bus 604 includes hardware, software or both, and the parts of the structure determination equipment of photonic device are coupled to each other.For example, but not limitation, bus may include accelerated graphics port (AGP) or other graphics bus, enhanced industrial standard architecture (EISA) bus, front side bus (FSB), hypertransport (HT) interconnection, industrial standard architecture (ISA) bus, infinite bandwidth interconnection, low pin count (LPC) bus, memory bus, micro channel architecture (MCA) bus, peripheral component interconnection (PCI) bus, PCI-Express (PCI-X) bus, serial advanced technology attachment (SATA) bus, video electronics standard association local (VLB) bus or other suitable bus or two or more of these combinations. In appropriate cases, bus 604 may include one or more buses. Although the present application embodiment describes and shows a specific bus, the application considers any suitable bus or interconnection.
[0150] In addition, in combination with the structure determination method of the photonic device in the above embodiment, the embodiment of the present application can provide a computer storage medium for implementation. The computer storage medium stores computer program instructions; when the computer program instructions are executed by the processor, any one of the structure determination methods of the photonic device in the above embodiment is implemented.
[0151] An embodiment of the present application also provides a computer program product, including a computer program, which, when processed and executed, implements any one of the photonic device structure determination methods in the above embodiments.
[0152] It should be clear that the present application is not limited to the specific configuration and processing described above and shown in the figures. For the sake of simplicity, a detailed description of the known method is omitted here. In the above embodiments, several specific steps are described and shown as examples. However, the method process of the present application is not limited to the specific steps described and shown, and those skilled in the art can make various changes, modifications and additions, or change the order between the steps after understanding the spirit of the present application.
[0153] The functional blocks shown in the above-described block diagram can be implemented as hardware, software, firmware or a combination thereof. When implemented in hardware, it can be, for example, an electronic circuit, an application specific integrated circuit (ASIC), appropriate firmware, a plug-in, a function card, etc. When implemented in software, the elements of the present application are programs or code segments that are used to perform the required tasks. The program or code segment can be stored in a machine-readable medium, or transmitted on a transmission medium or a communication link by a data signal carried in a carrier wave. "Machine-readable medium" can include any medium capable of storing or transmitting information. Examples of machine-readable media include electronic circuits, semiconductor memory devices, ROM, flash memory, erasable ROM (EROM), floppy disks, CD-ROMs, optical disks, hard disks, optical fiber media, radio frequency (RF) links, etc. The code segment can be downloaded via a computer network such as the Internet, an intranet, etc.
[0154] It should also be noted that the exemplary embodiments mentioned in this application describe some methods or systems based on a series of steps or devices. However, this application is not limited to the order of the above steps, that is, the steps can be performed in the order mentioned in the embodiment, or in a different order from the embodiment, or several steps can be performed simultaneously.
[0155] The above describes various aspects of the present disclosure with reference to the flowcharts and / or block diagrams of the structure determination method, device, equipment, medium and product of a photonic device according to an embodiment of the present disclosure. It should be understood that each box in the flowchart and / or block diagram and the combination of each box in the flowchart and / or block diagram can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device to produce a machine so that these instructions executed by the processor of the computer or other programmable data processing device enable the implementation of the functions / actions specified in one or more boxes of the flowchart and / or block diagram. Such a processor can be, but is not limited to, a general-purpose processor, a special-purpose processor, a special application processor or a field programmable logic circuit. It can also be understood that each box in the block diagram and / or flowchart and the combination of boxes in the block diagram and / or flowchart can also be implemented by dedicated hardware that performs the specified function or action, or can be implemented by a combination of dedicated hardware and computer instructions.
[0156] The above is only a specific implementation of the present application. Those skilled in the art can clearly understand that for the convenience and simplicity of description, the specific working processes of the systems, modules and units described above can refer to the corresponding processes in the aforementioned method embodiments, and will not be repeated here. It should be understood that the protection scope of the present application is not limited to this. Any technician familiar with the technical field can easily think of various equivalent modifications or replacements within the technical scope disclosed in this application, and these modifications or replacements should be included in the protection scope of this application.
Claims
1. A method for determining the structure of a photonic device, It is characterized in that include: Initializing a first matrix and a second matrix based on a preset structural condition of the photonic device; Adjusting element values of the second matrix so that the target matrix meets the first preset requirement; The first preset requirement includes that the matrix similarity value between the target matrix and the first matrix meets the similarity requirement, and the constraint parameter value of the corresponding photonic device meets the manufacturing constraint condition; there is a corresponding relationship between the target matrix and the second matrix, and the element value of the target matrix corresponds to the material of the corresponding point of the photonic device; Determining whether the photonic device corresponding to the target matrix meets the performance conditions; In the case where the photonic device does not meet the performance condition, the element values of the first matrix are adjusted, and the step of returning to adjust the element values of the second matrix so that the corresponding target matrix meets the first preset requirement is returned; In the case where the photonic device meets the performance condition, the structure of the photonic device is determined based on the target matrix.
2. The method for determining the structure of a photonic device according to claim 1, It is characterized in that Adjusting the element values of the second matrix so that the corresponding target matrix meets the first preset requirement includes: Based on the second matrix, determining the corresponding target matrix; Based on the target matrix and the first matrix, obtaining a first result output by a constraint objective function; the constraint objective function includes a similarity function and a constraint function, and the first result includes the matrix similarity value and the constraint parameter value; If the first result does not meet the first preset requirement, adjust the element values of the second matrix, and return to the step of determining the corresponding target matrix based on the second matrix; until the first result meets the first preset requirement.
3. The method for determining the structure of a photonic device according to claim 2, It is characterized in that Determining the corresponding target matrix based on the second matrix includes: Performing convolution operation filtering on the second matrix based on a preset two-dimensional convolution kernel to obtain a third matrix; Based on a preset projection function, the third matrix is projected to obtain the target matrix.
4. The method for determining the structure of a photonic device according to claim 2, It is characterized in that The first result is the sum of the matrix similarity value and the constraint parameter value; the first preset requirement includes that the first result is greater than a preset threshold; Based on the target matrix and the first matrix, obtaining a first result output by the constraint objective function includes: Input the target matrix and the first matrix into the similarity function to obtain the matrix similarity value; and input the target matrix into the constraint function to obtain the constraint parameter value; The first result is obtained by adding the matrix similarity value and the constraint parameter value.
5. The method for determining the structure of a photonic device according to claim 4, It is characterized in that The similarity function is used to calculate any one or any combination of the following: KL divergence, JS divergence, cosine similarity, Euclidean distance, Minkowski distance, and Chebyshev distance.
6. The method for determining the structure of a photonic device according to claim 4, It is characterized in that The constraint parameter value includes any one or any combination of the following: minimum characteristic size, minimum spacing, and minimum radius of curvature of the photonic device.
7. The method for determining the structure of a photonic device according to claim 1, It is characterized in that The performance condition includes that the energy loss value of the photonic device is less than a loss threshold; The determining whether the photonic device corresponding to the target matrix meets the performance condition includes: Based on the target matrix, obtaining an energy loss value of the photonic device output by a performance objective function; When the energy loss value is less than the loss threshold, determining that the photonic device meets the performance condition; When the energy loss value is not less than the loss threshold, it is determined that the photonic device does not meet the performance condition.
8. The method for determining the structure of a photonic device according to claim 7, It is characterized in that Based on the target matrix, obtaining the energy loss value of the photonic device output by the performance target function includes: Projecting the target matrix to obtain a scattering matrix; Based on the scattering matrix, the energy loss value of the corresponding photonic device is determined.
9. The method for determining the structure of a photonic device according to claim 7, It is characterized in that When the photonic device does not meet the performance condition, adjusting the element value of the first matrix includes: Calculating the derivative of the performance objective function with respect to the first matrix; The element values of the first matrix are adjusted based on the derivative.
10. A device for determining the structure of a photonic device, It is characterized in that The device comprises: An initialization module, used for initializing the first matrix and the second matrix based on a preset structural condition of the photonic device; A first adjustment module is used to adjust the element values of the second matrix so that the target matrix meets a first preset requirement; the first preset requirement includes that the matrix similarity value between the target matrix and the first matrix meets the similarity requirement, and the constraint parameter value of the corresponding photonic device meets the manufacturing constraint condition; there is a corresponding relationship between the target matrix and the second matrix, and the element values of the target matrix correspond to the materials of the corresponding points of the photonic device; A judgment module, used to judge whether the photonic device corresponding to the target matrix meets the performance condition; if the photonic device does not meet the performance condition, trigger the second adjustment module; if the photonic device meets the performance condition, trigger the determination module; The second adjustment module is used to adjust the element values of the first matrix and return to the step of adjusting the element values of the second matrix so that the corresponding target matrix meets the first preset requirement; The determination module is used to determine the structure of the photonic device based on the target matrix.
11. A device for determining the structure of a photonic device, It is characterized in that The device comprises: a processor and a memory storing computer program instructions; When the processor executes the computer program instructions, the method for determining the structure of a photonic device as claimed in any one of claims 1 to 9 is implemented.
12. A computer-readable storage medium, It is characterized in that The computer-readable storage medium stores computer program instructions, and when the computer program instructions are executed by a processor, the method for determining the structure of a photonic device according to any one of claims 1 to 9 is implemented.
13. A computer program product, It is characterized in that When the instructions in the computer program product are executed by a processor of an electronic device, the electronic device executes the method for determining the structure of a photonic device as described in any one of claims 1 to 9.