Electro-optical modulator traveling wave electrode design method and device and storage medium

Abstract

The invention discloses an electrooptical modulator traveling wave electrode design method and device and a storage medium, and the method comprises the steps: determining to-be-optimized process parameters, performance indexes, key process parameters and primary selection performance indexes of a traveling wave electrode, and setting constraint conditions; acquiring initial values of a plurality of groups of to-be-optimized process parameters and primary selection performance index evaluation results, and selecting the initial values of the plurality of groups of to-be-optimized process parameters as initial conditions; secondly, establishing a target function, and converting the optimization problem of the constrained traveling wave electrode design target function into an unconstrained optimization problem by adopting an external penalty function method; and finally, carrying out iterative solution by adopting an AdaGrad algorithm in combination with initial conditions to obtain traveling wave electrode process parameter values meeting design requirements. The equipment and the storage medium are used for implementing the method. The method has high efficiency, robustness and usability, and non-professionals can quickly generate a feasible scheme through preset performance indexes based on the method.

Description

Technical Field

[0001] The invention relates to the field of traveling wave electrode design methods, in particular to a traveling wave electrode design method, device and storage medium for an electro-optic modulator. Background Art

[0002] With the rapid development of artificial intelligence technology, optical computing has become an important direction to break through the bottleneck of traditional electronic computing due to its high parallelism and low energy consumption. As the core component of optical communication and optical computing systems, the performance of electro-optic modulators determines the efficiency and accuracy of optical signal modulation. With the increasing demand for electro-optic modulators, higher requirements are placed on the design of electro-optic modulators: on the one hand, it is necessary to meet high performance indicators under complex multi-physical field coupling, and on the other hand, it is necessary to adapt to the rapid iteration development cycle to cope with market changes.

[0003] Traditional electro-optic modulator traveling wave electrode optimization methods rely heavily on the experience and adjustments of designers, resulting in long development cycles and high trial-and-error costs. On the one hand, it is difficult to meet the demand for rapid iteration of devices in optical computing systems, and on the other hand, it severely limits the possibility for non-professionals to enter this field. Therefore, there is an urgent need for an electro-optic modulator design method that is both efficient, robust, and easy to use. It can not only reduce the learning and operation thresholds of non-professionals who have never designed in this field through automated processes, but also provide high-precision optimization tools for professionals in this field, thereby promoting the large-scale application of optical computing technology. Summary of the invention

[0004] The present invention provides a design method, device and storage medium for an electro-optic modulator traveling wave electrode, so as to solve the problem that the electro-optic modulator traveling wave electrode in the prior art relies on manual experience and it is difficult for non-professionals to participate in the design.

[0005] In order to achieve the above object, the technical solution adopted by the present invention is: A method for designing a traveling wave electrode of an electro-optic modulator, the process is as follows: Determine the process parameters to be optimized and the key process parameters therein, determine the performance indicators and select the initial performance indicators therefrom, and set the constraints of the key process parameters and performance indicators; Based on the preliminary performance index evaluation results corresponding to each of the multiple groups of initial values ​​of the process parameters to be optimized, several groups of initial values ​​of the process parameters to be optimized are selected as initial conditions; The objective function of the traveling wave electrode design is established with the performance index as a variable, and the constraints of the key process parameters and performance indexes are used as constraints of the objective function; Convert the constrained objective function optimization problem into an unconstrained optimization problem; The AdaGrad algorithm is used to iterate the unconstrained optimization problem with the process parameters to be optimized as variables. In each iteration, a set of initial values ​​of the process parameters to be optimized in the initial conditions are used as the initial points of the variables to obtain the optimal solution of the variables and the corresponding iterative results of the unconstrained optimization problem. In multiple iterations, different groups of initial values ​​are used as the initial points of the variables to obtain the optimal solution of the variables and the corresponding iterative results of each iteration. The optimal solution of the variables corresponding to the iterative results that meet the requirements is selected as the traveling wave electrode process parameter value that meets the design requirements.

[0006] Furthermore, the structural types of the traveling wave electrode include ordinary traveling wave electrode and capacitive load type traveling wave electrode.

[0007] Furthermore, the process parameters to be optimized include signal electrode width, electrode spacing, ground electrode width, signal electrode thickness, and ground electrode thickness, wherein the key process parameters are signal electrode width and electrode spacing.

[0008] Furthermore, the performance indicators include microwave refractive index, characteristic impedance, insertion loss, and half-wave voltage, and the microwave refractive index and characteristic impedance are selected as the primary performance indicators.

[0009] Further, a preliminary selected performance indicator evaluation result calculation function is constructed using the preliminary selected performance indicator as a variable, and the preliminary selected performance indicator evaluation result calculation function includes a preliminary selected performance indicator objective function and a preliminary selected performance indicator penalty item; Based on the preliminary performance index evaluation result calculation function, the preliminary performance index evaluation results and the preliminary performance index penalty items of each group of initial values ​​of the process parameters to be optimized are calculated; When selecting, the initial values ​​of several groups of process parameters to be optimized whose initial performance index evaluation results are less than the preset threshold are taken as initial conditions, or the initial values ​​of several groups of process parameters to be optimized whose penalty items are 0 are taken as initial conditions.

[0010] Furthermore, the iterative results of the unconstrained optimization problem corresponding to the optimal solutions of the variables obtained in each iteration are sorted by size, and the optimal solution of the variables corresponding to the smallest iterative result is taken as the traveling wave electrode process parameter value that meets the design requirements.

[0011] Furthermore, the Adagrad algorithm projects the parameters to the nearest discrete point after each gradient update.

[0012] An electronic device comprises a processor and a memory. When the processor reads and runs the program instructions in the memory, the above-mentioned method for designing traveling wave electrodes of an electro-optic modulator is executed.

[0013] A storage medium stores program instructions, and when the program instructions are read and run, the above-mentioned method for designing traveling wave electrodes of electro-optic modulators is executed.

[0014] The present invention discloses a traveling wave electrode design method for an electro-optic modulator based on the coordinated optimization of an external penalty function method and an AdaGrad algorithm, and is particularly suitable for the structural parameter optimization design of traveling wave electrodes in lithium niobate (LiNbO3) electro-optic modulators.

[0015] The method of the present invention solves the problems of low optimization efficiency and slow convergence speed caused by multi-parameter coupling, nonlinear constraints and discrete process limitations in traditional design by integrating the constraint processing capability of the external penalty function method with the adaptive gradient optimization characteristics of the AdaGrad algorithm. It is suitable for the development of high-performance electro-optic modulators in the fields of high-speed optical communication, microwave photonics and integrated photonic chips. The method has high efficiency, robustness and ease of use, and can realize the automated optimization of traveling wave electrodes of electro-optic modulators.

[0016] In the present invention, the constraints are processed by the external penalty function method, and the adaptive step size of the Adagrad algorithm is combined to significantly improve the optimization speed while ensuring accuracy. Through simulation experiments, it is found that even when the optimization range is large, excellent performance can still be guaranteed. The following technical advantages are specifically achieved: (1) Efficient optimization and fast convergence: The adaptive gradient adjustment mechanism based on the AdaGrad algorithm can dynamically allocate the parameter update step size, significantly improving the optimization efficiency under multi-parameter coupling problems. Compared with the traditional gradient descent method, the convergence speed is increased by more than 40%, and it can effectively avoid falling into the local optimal solution, which is especially suitable for searching in large-scale parameter space.

[0017] (2) Low threshold and high applicability: The automated optimization process greatly reduces the reliance on the professional experience of designers. Non-professionals who have never been involved in this field can quickly generate feasible solutions through preset performance indicators. At the same time, professionals in this field can flexibly adjust the penalty factor (σ), tolerance parameters (Δn, ΔZ), constraint range (n2-n1, Z2-Z1) and weight coefficient (α, β, a, b, c, d) to adapt to different process platforms (such as lithium niobate film, lithium niobate body material, silicon-based material), electrode types (such as ordinary traveling wave electrode, capacitor-loaded traveling wave electrode) and different process requirements (such as hollow bottom, SiO2 covering).

[0018] (3) Strong engineering practicality: Through parameter projection technology, the continuous optimization results are mapped to discrete process nodes (such as electrode width step 0.1μm), and the manufacturable layout parameters are directly output, avoiding the iterative links of "design-simulation-process adaptation" in traditional methods and reducing trial production costs. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] Figure 1 It is a flow chart of a method according to an embodiment of the present invention.

[0020] Figure 2 It is a schematic diagram of the traveling wave electrode structure of the electro-optic modulator involved in the embodiment of the present invention.

[0021] Figure 3 It is a cross-sectional view of the traveling wave electrode structure of the electro-optic modulator involved in an embodiment of the present invention.

[0022] Figure 4 It is a schematic diagram of iterative convergence of the Adagrad algorithm in an embodiment of the present invention.

[0023] Figure 5 This is a page effect diagram of an embodiment of the present invention. DETAILED DESCRIPTION

[0024] In order to enable those skilled in the art to better understand the solutions of the present invention, the following will describe the implementation methods of the present invention in detail in conjunction with the accompanying drawings and embodiments, so that the implementation process of how the present invention applies technical means to solve technical problems and achieve corresponding technical effects can be fully understood and implemented accordingly. The embodiments of the present invention and the various features in the embodiments can be combined with each other without conflict, and the technical solutions formed are all within the protection scope of the present invention.

[0025] Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present invention.

[0026] It should be noted that the terms "include" and "have" in the specification and claims of the present invention and the above drawings and any modifications thereof are intended to cover non-exclusive inclusions.

[0027] like Figure 1 As shown, this embodiment aims at the problem of low optimization efficiency caused by multi-parameter coupling, nonlinear constraints and discrete process limitations in traditional designs, and discloses a design method for traveling wave electrodes of electro-optic modulators combining an external penalty function method and an Adagrad algorithm. The process is as follows: Step 1: Determine the structural type of the traveling wave electrode of the electro-optic modulator according to the actual process design requirements. Determine the process parameters to be optimized for the traveling wave electrode according to the structural type of the traveling wave electrode of the electro-optic modulator, and identify the key process parameters among the process parameters to be optimized.

[0028] Furthermore, based on the electro-optic effect and optical waveguide characteristics of the traveling wave electrode material of the electro-optic modulator, a physical model of the traveling wave electrode of the electro-optic modulator is established, thereby clarifying the performance indicators of the traveling wave electrode and the key performance indicators among the performance indicators.

[0029] At the same time, set constraints on key process parameters and constraints on all performance indicators.

[0030] In this embodiment, two typical traveling wave electrode structures of electro-optic modulator are used as examples for description. The two typical traveling wave electrode structures are ordinary traveling wave electrode and capacitive load traveling wave electrode. The two typical traveling wave electrode structures are the same. Figure 2 , Figure 3 As shown, a signal electrode 2, a ground electrode 3, and a component 4 are arranged on a substrate 1, wherein there are two ground electrodes 3, which are respectively located outside two symmetrical sides of the signal electrode 2, and an optical waveguide 4 is arranged between the ground electrode 3 and the signal electrode 2 on each side.

[0031] In the above two typical traveling wave electrode structure types, the process parameters to be optimized include the width w of the signal electrode 2, the electrode spacing g (i.e., the spacing between the signal electrode 2 and each ground electrode 3 is g), the width wg of the ground electrode 3, the thickness h1 of the signal electrode 2, and the thickness h2 of the ground electrode 3. Among them, the width w of the signal electrode 2 and the electrode spacing g are key process parameters.

[0032] When each process parameter to be optimized is determined, the traveling wave electrode of the electro-optic modulator has certain physical properties. In this embodiment, physical models are established for the two typical traveling wave electrode structure types mentioned above, and the performance indicators determined thereby include microwave refractive index n, characteristic impedance Z, insertion loss S21, and half-wave voltage V, and the microwave refractive index n and characteristic impedance Z are selected as the primary performance indicators.

[0033] Moreover, in this embodiment, constraint conditions for key process parameters and performance indicators that are of great significance for evaluating the performance of the electro-optic modulator are also established. Among the key process parameters, the constraint condition for the width w of the signal electrode is: w1 < w < w2, where w1 is the minimum constraint of the signal electrode width and w2 is the maximum constraint of the signal electrode width. Among the key process parameters, the constraint condition for the electrode spacing g is: g1 < g < g2, where g1 is the minimum constraint of the electrode spacing and g2 is the maximum constraint of the electrode spacing. Among the performance indicators, the constraint condition for the microwave refractive index n is: n1 < n < n2, where n1 is the minimum constraint of the microwave refractive index and n2 is the maximum constraint of the microwave refractive index. Among the performance indicators, the constraint condition for the characteristic impedance Z is: Z1 < Z < Z2, where Z1 is the minimum constraint of the characteristic impedance and Z2 is the maximum constraint of the characteristic impedance. Among the performance indicators, the constraint condition for the half-wave voltage V is V < V0, where V0 is the maximum constraint of the half-wave voltage. Among the performance indicators, since the insertion loss S21 has little significance for evaluating the performance of the above two typical traveling-wave electrode electro-optic modulators, the constraint for the insertion loss S21 is not established.

[0034] Step 2: Obtain the initial values of multiple groups of process parameters to be optimized for the traveling-wave electrode.

[0035] Construct a calculation function for the evaluation result of the initially selected performance indicators of the traveling-wave electrode with the initially selected performance indicators as variables. The calculation function for the evaluation result of the initially selected performance indicators includes an initially selected performance indicator objective function and an initially selected performance indicator penalty term.

[0036] Based on the calculation function for the evaluation result of the initially selected performance indicators, calculate the evaluation results of the initially selected performance indicators of the traveling-wave electrode corresponding to the initial values of each group of process parameters to be optimized, as well as the initially selected performance indicator penalty term.

[0037] Then, based on the evaluation results of the initially selected performance indicators of the traveling-wave electrode corresponding to the initial values of each group of process parameters to be optimized, take the initial values of several groups of process parameters to be optimized with the evaluation results of the initially selected performance indicators less than the preset threshold as the initial conditions, where the preset threshold is determined based on the design experience of experts for different types of electro-optic modulators; or take the initial values of several groups of process parameters to be optimized with the penalty term being 0 as the initial conditions.

[0038] In this embodiment, the approximate position of the feasible solution of the process parameters to be optimized is determined by performing preliminary linear scans at equal intervals at larger intervals on the process parameters to be optimized, thereby obtaining multiple groups of initial values ​​of the process parameters to be optimized. For the above two typical types of traveling wave electrode structures, in this embodiment, the initial values ​​of each group of process parameters to be optimized refer to the initial values ​​of the signal electrode width w, the electrode spacing g, the ground electrode width wg, the signal electrode thickness h1, and the ground electrode thickness h2. The initial values ​​of multiple groups of signal electrode width w, electrode spacing g, ground electrode width wg, signal electrode thickness h1, and ground electrode thickness h2 are obtained through preliminary linear scans.

[0039] For the above two typical traveling wave electrode structure types, the preliminary performance index evaluation result calculation function constructed in this embodiment is P(n, Z), and the calculation formula of P(n, Z) is as follows: P(n,Z)=f(n,Z)+σp(n,Z) Where: P(n,Z) is defined as the calculation function of the preliminary performance index evaluation result, which is constructed with the preliminary performance index microwave refractive index n and characteristic impedance Z as variables. The smaller the value of P(n,Z), the better the matching result. f(n,Z) is the objective function, which is constructed with the initial performance indicators microwave refractive index n and characteristic impedance Z as variables.

[0040] p(n,Z) is a penalty term, which is constructed using the initial performance indicators microwave refractive index n and characteristic impedance Z as variables.

[0041] σ is a sufficiently large number, called the penalty factor.

[0042] In this embodiment, for the above two typical traveling wave electrode structure types, the constructed objective function f(n, Z) is shown in the following formula: min f(n,Z)=α*|n-no|+β*|Z-Zo| The constructed penalty term p(n,Z) is shown as follows: Where: α, β are constants. no is the refractive index of the optical waveguide group. Zo is the port characteristic impedance. η≥1, usually η=2 can be taken. Δn is the microwave refractive index tolerance caused by the scanning interval in the preliminary linear scan, ranging from 0.1<Δn<0.3. ΔZ is the characteristic impedance tolerance caused by the scanning interval in the preliminary linear scan, ranging from 10Ω<ΔZ<15Ω.

[0043] In this embodiment, based on the preliminary performance indicator evaluation result calculation function P(n,Z), the preliminary performance indicator (n, Z) evaluation results of the traveling wave electrode corresponding to the initial values ​​of each group of process parameters to be optimized and the preliminary performance indicator penalty term p(n,Z) are calculated.

[0044] Finally, take the initial values of several groups of process parameters to be optimized whose performance index evaluation results are less than the preset threshold as the initial conditions, or take the initial values of several groups of process parameters to be optimized with a penalty term of 0 as the initial conditions.

[0045] Step 3: Take all the performance indexes of the traveling-wave electrode as variables, establish the objective function for the design of the traveling-wave electrode, and take the constraint conditions of the key process parameters and the constraint conditions of the performance indexes that are of great significance to the performance evaluation of the electro-optic modulator as the constraints of the objective function for the design of the traveling-wave electrode.

[0046] In this embodiment, for the above two typical types of traveling-wave electrode structures, the established objective function g(n, Z, V, S21) for the design of the traveling-wave electrode takes the four performance indexes of the microwave refractive index n, characteristic impedance Z, insertion loss S21, and half-wave voltage V as variables. The constraints of the objective function for the design of the traveling-wave electrode include the constraint conditions of the performance indexes n1 < n < n2, Z1 < Z < Z2, V < V0, and the constraint conditions of the key process parameters w1 < w < w2, g1 < g < g2.

[0047] Step 4: Adopt the external penalty function method to transform the optimization problem of the objective function for the design of the traveling-wave electrode with constraints established in Step 3 into an unconstrained optimization problem.

[0048] In this embodiment, for the above two typical types of traveling-wave electrode structures, the transformed unconstrained optimization problem is shown as the following formula: Q(n, Z, V, S21, w, g) = g(n, Z, V, S21) + σq(n, Z, V, w, g) Where: Q(n, Z, V, S21, w, g) represents the function of the transformed unconstrained optimization problem. g(n, Z, V, S21) represents the objective function for the design of the traveling-wave electrode constructed in Step 3. q(n, Z, V, w, g) represents the penalty function of the constraints of the objective function for the design of the traveling-wave electrode. σ is a sufficiently large number, called the penalty factor.

[0049] Specifically, the objective function g(n, Z, V, S21) for the design of the traveling-wave electrode is shown as the following formula: g(n, Z, V, S21) = a * |n - no| + b * |Z - Zo| + c * |V| + d * |S21| In the formula: a, b, c, d are constants; n is the microwave refractive index; no is the group refractive index of the optical waveguide; Z is the characteristic impedance; Zo is the port characteristic impedance; V is the half-wave voltage; S21 is the insertion loss.

[0050] The penalty function q(n, Z, V, w, g) of the constraints of the objective function for the design of the traveling-wave electrode is shown as the following formula: q(n,Z,V,w,g)=s(n,Z,V)+t(w,g) Where: s(n, Z, V) represents the constraints of performance indicators that are important for the performance evaluation of electro-optic modulators; t(w, g) represents the constraints of key process parameters.

[0051] The performance index constraints s(n, Z, V) and key process parameter constraints t(w, g) are shown in the following formulas: s(n,Z,V)=|min{n-n1,0}| η +|min{n2-n,0}| η +|min{Z-Z1,0}| η +|min{Z2-Z,0}| η +|min{V0-V,0}| η t(w,g)=|min{w-w1,0}| η +|min{w2-w,0}| η +|min{g-g1,0}| η +|min{g2-g,0}| η .

[0052] Step 5, using the AdaGrad algorithm, with the process parameters to be optimized as variables, to perform gradient iterative calculations on the unconstrained optimization problem; in each iteration, the initial values ​​of one group of process parameters to be optimized in the initial conditions are used as the initial points of the variables for calculation, thereby solving the optimal solution of the variables and the iterative results of the unconstrained optimization problem corresponding to the optimal solutions of the variables in the current iteration; in multiple iterations, the initial values ​​of different groups of process parameters to be optimized in the initial conditions are used as the initial points of the variables, thereby obtaining the iterative results of the unconstrained optimization problem corresponding to the optimal solutions of the variables in each iteration through multiple iterations; then, based on the iterative results, the optimal solutions of the variables corresponding to the iterative results that meet the requirements are selected as the traveling wave electrode process parameter values ​​that meet the design requirements.

[0053] In this embodiment, the AdaGrad algorithm is used to perform gradient iteration on the function of the unconstrained optimization problem established in step 4, such as Figure 4 As shown, the process is as follows: (S1) Determine an initial search step length according to the determined search interval range.

[0054] (S2) According to the determined search interval and search step size, the process parameters to be optimized are used as variables, and the unconstrained optimization problem is solved iteratively through the AdaGrad algorithm. In each iteration, the initial values ​​of one set of process parameters to be optimized in the initial conditions obtained in step 2 are taken as the initial points of the variables for calculation to obtain the optimal solution of the variables and the corresponding iterative results of the unconstrained optimization problem. In multiple iterations, the initial values ​​of different sets of process parameters to be optimized in the initial conditions obtained in step 2 are taken as the initial points of the variables for calculation, thereby obtaining the optimal solutions of the variables corresponding to each iteration and the corresponding iterative results of the unconstrained optimization problem through multiple iterations. The solution for each iteration is shown as follows:

[0055] Where: Represents the function value of the unconstrained optimization problem under the k-th iteration, that is, the k-th iteration result.

[0056] represents the variable at the kth iteration, the variable The initial point is the initial value of a set of process parameters to be optimized in the initial conditions. Each iteration process uses x as a variable to solve and obtain the optimal solution of the variable x of the iteration.

[0057] represents the penalty factor for the kth iteration.

[0058] .

[0059] It represents a function with x as the independent variable and the value of the traveling wave electrode design objective function g(n,Z,V,S21) as the dependent variable.

[0060] For penalty items.

[0061] Through Use the Adagrad algorithm to iteratively solve and get the penalty factor as The optimal solution in the case The variable obtained by the kth external penalty iteration is Optimal solution ,in represents the optimal solution for the kth iteration It is related to the penalty factor, so it is expressed as the penalty factor Function of a variable ,Right now .

[0062] (S3) When , then the algorithm terminates, point is the approximate optimal solution to the constrained optimization problem, where represents the initial point of the kth iteration, represents the initial point of the kth iteration Corresponding penalty item; otherwise, update the penalty factor And repeat the iteration. Among them, is the magnification factor, in this embodiment, =10; In order to allow for error, in this embodiment =0.05.

[0063] In this embodiment, each iteration actually includes two layers of iterations, namely, the optimization iteration of the Adagrad algorithm in step S2 and the iteration of the external penalty (ie, the penalty factor) in step S3.

[0064] After each gradient update, the Adagrad algorithm projects the parameters to the nearest discrete point to meet the discrete characteristics of engineering optimization problems.

[0065] (S4) The iterative results corresponding to the optimal solutions of the variables obtained in each iteration Sort and get the iteration results The optimal solution of the variable corresponding to the smallest one is taken as the process parameter value of the traveling wave electrode that meets the design requirements, that is, the process parameter values ​​of the signal electrode width w, electrode spacing g, ground electrode width wg, signal electrode thickness h1, and ground electrode thickness h2 that meet the design requirements, thereby completing the design of the traveling wave electrode of the electro-optical modulator.

[0066] This embodiment also discloses an electronic device, including a processor and a memory, wherein a storage medium of the memory stores program instructions, and when the processor reads and runs the program instructions in the memory, the above-mentioned method for designing traveling wave electrodes of an electro-optic modulator is executed.

[0067] This embodiment also discloses a storage medium. When the program instructions in the storage medium are read and run by any device, the above-mentioned method for designing traveling wave electrodes of electro-optic modulator is executed.

[0068] The method of this embodiment has been verified in practice, and a physical electro-optic modulator that meets the performance indicators has been successfully designed and manufactured. It can realize the full process of automated design from model establishment to parameter optimization. For specific page effects, see Figure 5 shown.

[0069] The preferred embodiments of the present invention are described in detail above in conjunction with the accompanying drawings. The embodiments described in the present invention are merely descriptions of the preferred embodiments of the present invention, and do not limit the concept and scope of the present invention. The various specific technical features described in the above specific embodiments can be combined in any suitable manner without contradiction, and such combinations should also be regarded as the contents disclosed in the present disclosure as long as they do not violate the concept of the present invention. In order to avoid unnecessary repetition, the present invention will not further describe various possible combinations.

[0070] The present invention is not limited to the specific details of the above-mentioned embodiments. Within the technical concept of the present invention and without departing from the design concept of the present invention, various modifications and improvements made to the technical solution of the present invention by technical personnel in this field should fall within the protection scope of the present invention. The technical contents for which protection is sought in the present invention have been fully recorded in the claims.

Claims

1. A method for designing a traveling wave electrode of an electro-optic modulator, characterized in that: The process is as follows: Determine the process parameters to be optimized and the key process parameters therein, determine the performance indicators and select the initial performance indicators therefrom, and set the constraints of the key process parameters and performance indicators; Based on the preliminary performance index evaluation results corresponding to each of the multiple groups of initial values ​​of the process parameters to be optimized, several groups of initial values ​​of the process parameters to be optimized are selected as initial conditions; The objective function of the traveling wave electrode design is established with the performance index as a variable, and the constraints of the key process parameters and performance indexes are used as constraints of the objective function; Convert the constrained objective function optimization problem into an unconstrained optimization problem; The AdaGrad algorithm is used to iterate the unconstrained optimization problem with the process parameters to be optimized as variables; In each iteration, a set of initial values ​​of the process parameters to be optimized in the initial conditions are used as the initial points of the variables, and the optimal solutions of the variables and the corresponding iterative results of the unconstrained optimization problem are solved; in multiple iterations, different groups of initial values ​​are used as the initial points of the variables, and the optimal solutions of the variables and the corresponding iterative results of each iteration are obtained; the optimal solutions of the variables corresponding to the iterative results that meet the requirements are selected as the traveling wave electrode process parameter values ​​that meet the design requirements.

2. The method for designing a traveling wave electrode of an electro-optic modulator according to claim 1, characterized in that: The structural types of the traveling wave electrode include ordinary traveling wave electrode and capacitive load type traveling wave electrode.

3. The method for designing a traveling wave electrode of an electro-optic modulator according to claim 2, characterized in that: The process parameters to be optimized include signal electrode width, electrode spacing, ground electrode width, signal electrode thickness, and ground electrode thickness, among which the key process parameters are signal electrode width and electrode spacing.

4. The method for designing a traveling wave electrode of an electro-optic modulator according to claim 2, characterized in that: The performance indicators include microwave refractive index, characteristic impedance, insertion loss, and half-wave voltage, and the microwave refractive index and characteristic impedance are selected as the primary performance indicators.

5. The method for designing a traveling wave electrode of an electro-optic modulator according to claim 1, characterized in that: Using the preliminary selected performance indicator as a variable to construct a preliminary selected performance indicator evaluation result calculation function, the preliminary selected performance indicator evaluation result calculation function includes a preliminary selected performance indicator objective function and a preliminary selected performance indicator penalty item; Based on the preliminary performance index evaluation result calculation function, the preliminary performance index evaluation results and the preliminary performance index penalty items of each group of initial values ​​of the process parameters to be optimized are calculated; When selecting, the initial values ​​of several groups of process parameters to be optimized whose initial performance index evaluation results are less than the preset threshold are taken as initial conditions, or the initial values ​​of several groups of process parameters to be optimized whose penalty items are 0 are taken as initial conditions.

6. The method for designing a traveling wave electrode of an electro-optic modulator according to claim 1, characterized in that: The iterative results of the unconstrained optimization problem corresponding to the optimal solutions of the variables obtained in each iteration are sorted by size, and the optimal solution of the variables corresponding to the smallest iterative result is taken as the traveling wave electrode process parameter value that meets the design requirements.

7. A method for designing a traveling wave electrode of an electro-optic modulator according to any one of claims 1 to 6, characterized in that: The Adagrad algorithm projects the parameters to the nearest discrete point after each gradient update.

8. An electronic device comprising a processor and a memory, characterized in that: When the processor reads and runs the program instructions in the memory, it executes the method for designing a traveling wave electrode of an electro-optic modulator as claimed in any one of claims 1 to 7.

9. A storage medium storing program instructions, characterized in that: When the program instructions are read and executed, the method for designing traveling wave electrodes of an electro-optic modulator as claimed in any one of claims 1 to 7 is executed.

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