Optical Proximity Correction Optimization Method, Device, Storage Medium and Electronic Device

Abstract

The present application discloses an optical proximity correction optimization method, apparatus, storage medium and electronic device. Among them, the optical proximity correction optimization method includes analyzing an original layout to determine an area to be optimized in the original layout; defining the distance between a correction layer and a target layer in the area to be optimized as a correction variable; defining the root mean square error of the edge position errors of all correction variables as a target evaluation function; based on the target evaluation function, using an annealing algorithm to optimize all correction variables to obtain a target correction variable combination; and using the target correction variable combination to correct the original layout to obtain a target layout. This solution avoids defective patterns caused by the mutual influence of correction variables.

Description

Technical Field

[0001] Embodiments of the present application relate to the field of semiconductor technology, and in particular to an optical proximity correction optimization method, apparatus, storage medium, and electronic device. Background Art

[0002] With the continuous progress of semiconductor manufacturing technology, the lithography process has become a key step in manufacturing microelectronic components. However, at the micron and nanometer scales, optical proximity effects (OPE) often occur during the lithography process, resulting in pattern distortion of the layout and affecting the manufacturing accuracy of the chip. To solve this problem, optical proximity correction (OPC) is usually required for the original layout.

[0003] Current optical proximity correction methods usually rely on model feedback and optimize by gradually adjusting the pattern position. When facing complex patterns, this method often fails to accurately reach the target position due to the mutual influence between correction variables, resulting in defective patterns. Summary of the Invention

[0004] Embodiments of the present application provide an optical proximity correction optimization method, apparatus, storage medium, and electronic device, which can avoid defective patterns caused by the mutual influence of correction variables.

[0005] In a first aspect, embodiments of the present application provide an optical proximity correction optimization method, including:

[0006] Analyze the original layout to determine the area to be optimized in the original layout;

[0007] Define the distance between the correction layer and the target layer in the area to be optimized as a correction variable;

[0008] Define the root mean square error of the edge position errors of all the correction variables as the target evaluation function;

[0009] Based on the target evaluation function, use the annealing algorithm to optimize all the correction variables to obtain a target correction variable combination;

[0010] Use the target correction variable combination to correct the original layout to obtain a target layout.

[0011] In the optical proximity correction optimization method provided by the embodiments of the present application, the step of using the annealing algorithm to optimize all the correction variables based on the evaluation function to obtain a target correction variable combination includes:

[0012] Set the initial values of all the correction variables to 0;

[0013] Randomly generate the current combination of correction variables within the preset value range of the correction variables, and calculate the current evaluation function of the current combination of correction variables;

[0014] Compare the current evaluation function with the target evaluation function, and determine whether to update the target evaluation function according to the comparison result;

[0015] Return to execute the step of randomly generating the current combination of correction variables within the preset value range of the correction variables until the edge position errors of all the correction variables are less than the preset threshold, and use the current combination of correction variables as the target combination of correction variables.

[0016] In the optical proximity correction optimization method provided in the embodiments of the present application, the determining whether to update the target evaluation function according to the comparison result includes:

[0017] If the current evaluation function is less than the target evaluation function, use the current evaluation function as the target evaluation function;

[0018] If the current evaluation function is greater than or equal to the target evaluation function, determine whether to use the current evaluation function as the target evaluation function according to the acceptance probability.

[0019] In the optical proximity correction optimization method provided in the embodiments of the present application, the acceptance probability is:

[0020] P = exp(−ΔRMS / RMS new )

[0021] In the above formula, P is the acceptance probability, ΔRMS is the difference between the current evaluation function and the target evaluation function, and RMS new is the current evaluation function.

[0022] In the optical proximity correction optimization method provided in the embodiments of the present application, the calculating the current evaluation function of the current combination of correction variables includes:

[0023] Calculate the edge position error of each correction variable in the current combination of correction variables;

[0024] Calculate the root mean square error of all the edge position errors.

[0025] In the optical proximity correction optimization method provided in the embodiments of the present application, the analyzing the original layout to determine the area to be optimized in the original layout includes:

[0026] Perform optical simulation on the original layout to identify the target area with optical proximity effect;

[0027] Calculate the error of the target area, and determine the area to be optimized from multiple target areas according to the error calculation result.

[0028] In the optical proximity correction optimization method provided in the embodiments of the present application, the preset threshold is 1 nanometer.

[0029] In a second aspect, an optical proximity correction optimization device provided in the embodiments of the present application includes:

[0030] A layout analysis unit for analyzing the original layout to determine the area to be optimized in the original layout;

[0031] A variable definition unit for defining the distance between the correction layer and the target layer in the area to be optimized as a correction variable;

[0032] A function definition unit for defining the root mean square error of the edge position errors of all the correction variables as a target evaluation function;

[0033] A variable optimization unit for optimizing all the correction variables based on the target evaluation function by using an annealing algorithm to obtain a target correction variable combination;

[0034] A layout correction unit for correcting the original layout by using the target correction variable combination to obtain a target layout.

[0035] In a third aspect, the present application provides a storage medium storing multiple instructions suitable for being loaded by a processor to execute the optical proximity correction optimization method described in any one of the above.

[0036] In a fourth aspect, the present application provides an electronic device including a memory, a processor, and a computer program stored on the memory and executable on the processor. When the processor executes the computer program, the optical proximity correction optimization method described in any one of the above is implemented.

[0037] In summary, the optical proximity correction optimization method provided by the embodiments of the present application includes analyzing the original layout to determine the area to be optimized in the original layout; defining the distance between the correction layer and the target layer in the area to be optimized as a correction variable; defining the root mean square error of the edge position errors of all the correction variables as a target evaluation function; optimizing all the correction variables based on the target evaluation function by using an annealing algorithm to obtain a target correction variable combination; and correcting the original layout by using the target correction variable combination to obtain a target layout. This solution uses an annealing algorithm to optimize the optical proximity correction process, optimizes the layout by precisely adjusting the correction variables, and can effectively avoid defective patterns caused by the mutual influence of correction variables, thereby improving the accuracy and efficiency of optical proximity correction. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] To more clearly illustrate the technical solutions in the embodiments of the present application, the following briefly introduces the accompanying drawings required for the description of the embodiments. Obviously, the accompanying drawings in the following description are only some embodiments of the present application. For those skilled in the art, other drawings can be obtained based on these drawings without creative efforts.

[0039] Figure 1 FIG. is a flowchart of the optical proximity correction optimization method provided by the embodiments of the present application.

[0040] Figure 2 FIG. is a layer diagram provided by the embodiments of the present application.

[0041] Figure 3 FIG. is a diagram of correction variables provided by the embodiments of the present application.

[0042] Figure 4 FIG. is a structural diagram of the optical proximity correction optimization device provided by the embodiments of the present application.

[0043] Figure 5 FIG. is a structural diagram of an electronic device provided by the embodiments of the present application. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0044] Here, the exemplary embodiments will be described in detail, and the examples are shown in the accompanying drawings. When the following description refers to the accompanying drawings, unless otherwise indicated, the same numbers in different drawings represent the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the present application. On the contrary, they are only examples of devices and methods consistent with some aspects of the present application as detailed in the appended claims.

[0045] It should be noted that in this text, the term "including", "comprising" or any other variant thereof is intended to cover non-exclusive inclusion, such that a process, method, article or device comprising a series of elements not only includes those elements but also includes other elements not expressly listed, or further includes elements inherent to such process, method, article or device. Without further limitation, an element defined by the phrase "comprising one..." does not exclude the presence of additional identical elements in the process, method, article or device comprising such element. In addition, components, features, and elements with the same name in different embodiments of the present application may have the same meaning or different meanings, and their specific meanings need to be determined based on their explanations in the specific embodiments or further in combination with the context of the specific embodiments.

[0046] It should be understood that the specific embodiments described herein are merely for explaining the present application and are not used to limit the present application.

[0047] In the subsequent descriptions, the use of suffixes such as "module", "component" or "unit" for indicating elements is only for the convenience of explaining the present application and has no specific meaning in itself. Therefore, "module", "component" or "unit" can be used interchangeably.

[0048] In the description of the present application, it should be noted that the orientation or positional relationship indicated by terms such as "upper", "lower", "left", "right", "inner", "outer", etc. is based on the orientation or positional relationship shown in the drawings, and is only for the convenience of describing the present application and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore should not be construed as a limitation to the present application. In addition, terms such as "first", "second", etc. are only used for descriptive purposes and should not be construed as indicating or implying relative importance.

[0049] Based on this, the embodiments of the present application provide an optical proximity correction optimization method, device, storage medium and electronic device. Specifically, the optical proximity correction optimization device can be integrated in an electronic device, and the electronic device can be a server or a terminal device, etc.; among them, the terminal can include a mobile phone, a wearable smart device, a tablet computer, a laptop computer, and a personal computer (PC), etc.; the server can be a single server or a server cluster composed of multiple servers, and can be a physical server or a virtual server.

[0050] For example, the electronic device can first analyze the original layout to determine the area to be optimized in the original layout; then define the distance between the correction layer and the target layer in the area to be optimized as the correction variable; then define the root mean square error of the edge position errors of all correction variables as the target evaluation function; then optimize all correction variables based on the target evaluation function using the annealing algorithm to obtain a combination of target correction variables; finally, correct the original layout using the combination of target correction variables to obtain the target layout.

[0051] The technical solutions shown in the present application will be described in detail below through specific embodiments. It should be noted that the description order of the following embodiments does not limit the priority order of the embodiments.

[0052] Please refer to Figure 1 , Figure 1 which is a schematic flowchart of the optical proximity correction optimization method provided by an embodiment of the present application. The specific process of the optical proximity correction optimization method can be as follows:

[0053] 101. Analyze the original layout to determine the area to be optimized in the original layout.

[0054] The original layout Figure 1 is generally created through chip design software (such as Cadence, Mentor Graphics, Synopsys, etc.). In the semiconductor manufacturing industry, in order to ensure the standardization and compatibility of design data, specific file format standards, such as GDS (Graphic Data System) or OASIS (Open Artwork System Interchange Standard), are usually used to save these original layouts.

[0055] In some embodiments, after obtaining the original layout, optical simulation can be performed on the original layout to identify target areas with optical proximity effects; then error calculation is performed on the target areas, and the area to be optimized is determined from multiple target areas according to the error calculation results.

[0056] In the embodiments of the present application, error calculation can be performed on the target areas based on the Edge Placement Error (EPE). EPE is an index used to measure the distance between the Contour layer and the Target layer in OPC. Specifically, an edge position error threshold can be preset first, then the distance between the contour layer and the target layer in each target area is calculated, and this distance is compared with the edge position error threshold. When this distance is greater than or equal to the edge position error threshold, the corresponding target area can be determined as the area to be optimized.

[0057] 102. Define the distance between the correction layer and the target layer in the area to be optimized as the correction variable.

[0058] Among them, as Figure 2 shown, the correction layer (OPC Layer) refers to the pattern after optical proximity correction. The target pattern refers to the ideally designed pattern, representing the ultimate requirements of the chip function and circuit. The contour layer is the actual imaging pattern simulated after lithography simulation of the correction layer.

[0059] For example, when the area to be optimized includes the first area to be optimized, the second area to be optimized, and the third area to be optimized, the correction variables in the first area to be optimized can be as Figure 3 shown, the distance between each side of the correction layer and the corresponding side in the target layer, that is, X1, X2, X3, and X4.

[0060] Similarly, the correction variables in the second area to be optimized can be X5, X6, X7, and X8. The correction variables in the third area to be optimized can be X9, X10, X11, and X12.

[0061] 103. Define the root mean square error of the edge position errors of all correction variables as the target evaluation function.

[0062] Specifically, the distance between the contour layer and the target layer can be calculated first to obtain the edge position error corresponding to each correction variable. Then calculate the root mean square error (Root Mean Square, RSM) of all edge position errors, and define this root mean square error as the target evaluation function.

[0063] For example, the edge position errors corresponding to X1, X2, X3, X4, X5, X6, X7, X8, X9, X10, X11, and X12 can be calculated separately first to obtain RSM1, RSM2, RSM3, RSM4, RSM5, RSM6, RSM7, RSM8, RSM9, RSM10, RSM11, and RSM12. Then, calculate the root mean square error of RSM1, RSM2, RSM3, RSM4, RSM5, RSM6, RSM7, RSM8, RSM9, RSM10, RSM11, and RSM12.

[0064] 104. Based on the target evaluation function, use the annealing algorithm to optimize all correction variables to obtain the target correction variable combination.

[0065] Specifically, the initial values of all correction variables can be set to 0; randomly generate the current combination of correction variables within the preset value range of the correction variables, and calculate the current evaluation function of the current combination of correction variables; compare the current evaluation function with the target evaluation function, and determine whether to update the target evaluation function according to the comparison result; return to the step of randomly generating the current combination of correction variables within the preset value range of the correction variables until the edge position error of all correction variables is less than the preset threshold, and use the current combination of correction variables as the target combination of correction variables.

[0066] For example, when the preset value range is from -10 to 10, the value ranges of X1, X2, X3, X4, X5, X6, X7, X8, X9, X10, X11, and X12 can be as follows:

[0067] X1 = -10, -9, -8, …, 0, … 8, 9, 10;

[0068] X2 = -10, -9, -8, …, 0, … 8, 9, 10;

[0069] ……

[0070] X12 = -10, -9, -8, …, 0, … 8, 9, 10.

[0071] In the embodiment of the present application, the above preset threshold is 1 nanometer.

[0072] In some embodiments, the current combination of correction variables can be generated within the preset value range of the correction variables by using the Monte Carlo method, ensuring that the values of each correction variable are evenly distributed, thereby ensuring the comprehensiveness and randomness of the calculation of the target evaluation function. In this way, it is possible to effectively avoid falling into a local optimal solution and improve the probability of finding the global optimal solution.

[0073] Among them, calculating the current evaluation function of the current combination of correction variables can specifically be: calculating the edge position error of each correction variable in the current combination of correction variables; calculating the root mean square error of all edge position errors. The specific process of calculating the edge position error of each correction variable in the current combination of correction variables can refer to step 103, and this embodiment will not elaborate on it.

[0074] In the embodiment of the present application, it is possible to determine whether to update the target evaluation function based on the Metropolis criterion according to the comparison result.

[0075] Specifically, if the current evaluation function is less than the target evaluation function, then use the current evaluation function as the target evaluation function; if the current evaluation function is greater than or equal to the target evaluation function, then determine whether to use the current evaluation function as the target evaluation function according to the acceptance probability.

[0076] Among them, the acceptance probability can be: P = exp(−ΔRMS / RMS new )

[0077] In the above formula, P is the acceptance probability, ΔRMS is the difference between the current evaluation function and the target evaluation function, and RMS new is the current evaluation function. The value range of P is [0, 1].

[0078] In the specific implementation process, a random value r between 0 and 1 can be randomly generated. If r ≤ P, the new solution is accepted (i.e., the current evaluation function is used as the target evaluation function); otherwise, the new solution is rejected (i.e., the target evaluation function is not updated).

[0079] The Metropolis criterion realizes the dynamic balance between global search and local convergence through the judgment of ΔRMS and the acceptance mechanism of random probability. For the application of optimizing optical proximity correction, it can effectively avoid falling into local optimum in complex layout correction and improve the final optimization accuracy at the same time.

[0080] 105. Use the target correction variable combination to correct the original layout to obtain the target layout.

[0081] Specifically, each target correction variable in the target correction variable combination can be used to correct the area to be optimized in the original layout, so as to obtain a target layout without defective patterns.

[0082] In summary, the optical proximity correction optimization method provided by the embodiments of the present application includes analyzing the original layout to determine the area to be optimized in the original layout; defining the distance between the correction layer and the target layer in the area to be optimized as the correction variable; defining the root mean square error of the edge position errors of all correction variables as the target evaluation function; based on the target evaluation function, using the annealing algorithm to optimize all correction variables to obtain the target correction variable combination; using the target correction variable combination to correct the original layout to obtain the target layout. This solution uses the annealing algorithm to optimize the optical proximity correction process. By precisely adjusting the correction variables and optimizing the layout, it can effectively avoid defective patterns caused by the mutual influence of correction variables, thereby improving the accuracy and efficiency of optical proximity correction. In addition, the global search ability of the annealing algorithm can better find the optimal solution, ensuring that the optical proximity correction process can meet the high-precision manufacturing requirements.

[0083] To facilitate better implementation of the optical proximity correction optimization method provided by the embodiments of the present application, the embodiments of the present application also provide an optical proximity correction optimization device. The meanings of the terms are the same as those in the above optical proximity correction optimization method, and the specific implementation details can refer to the description in the method embodiments.

[0084] Please refer toFigure 4 , Figure 4 is a schematic structural diagram of an optical proximity correction optimization device provided by an embodiment of the present application. The optical proximity correction optimization device may include a layout analysis unit 201, a variable definition unit 202, a function definition unit 203, a variable optimization unit 204, and a layout correction unit 205. Among them,

[0085] The layout analysis unit 201 is configured to analyze the original layout to determine the area to be optimized in the original layout;

[0086] The variable definition unit 202 is configured to define the distance between the correction layer and the target layer in the area to be optimized as a correction variable;

[0087] The function definition unit 203 is configured to define the root mean square error of the edge position errors of all correction variables as a target evaluation function;

[0088] The variable optimization unit 204 is configured to optimize all correction variables based on the target evaluation function by using an annealing algorithm to obtain a target correction variable combination;

[0089] The layout correction unit 205 is configured to correct the original layout by using the target correction variable combination to obtain a target layout.

[0090] For the specific implementation manners of the above units, reference may be made to the embodiments of the above optical proximity correction optimization method, which will not be elaborated herein one by one.

[0091] In summary, the optical proximity correction optimization device provided by the embodiment of the present application can be analyzed by the layout analysis unit 201 to analyze the original layout to determine the area to be optimized in the original layout; the variable definition unit 202 defines the distance between the correction layer and the target layer in the area to be optimized as a correction variable; the function definition unit 203 defines the root mean square error of the edge position errors of all correction variables as a target evaluation function; the variable optimization unit 204 optimizes all correction variables based on the target evaluation function by using an annealing algorithm to obtain a target correction variable combination; the layout correction unit 205 corrects the original layout by using the target correction variable combination to obtain a target layout. This solution uses an annealing algorithm to optimize the optical proximity correction process, optimizes the layout by precisely adjusting the correction variables, and can effectively avoid defective patterns caused by the mutual influence of correction variables, thereby improving the accuracy and efficiency of optical proximity correction. In addition, the global search ability of the annealing algorithm can better find the optimal solution to ensure that the optical proximity correction process can meet the high-precision manufacturing requirements.

[0092] The embodiment of the present application further provides an electronic device, which may integrate the optical proximity correction optimization device of the embodiment of the present application, such as Figure 5As shown, it shows a schematic structural diagram of an electronic device involved in an embodiment of the present application. Specifically:

[0093] The electronic device may include components such as a processor 301 with one or more processing cores and a memory 302 of one or more computer-readable storage media. Those skilled in the art can understand that Figure 5 the structure of the electronic device shown in does not constitute a limitation on the electronic device, and it may include more or fewer components than shown, or combine certain components, or have different component arrangements. Among them:

[0094] The processor 301 is the control center of the electronic device, connecting various parts of the entire electronic device through various interfaces and lines. By running or executing software programs and / or the present application stored in the memory 302, and calling the data stored in the memory 302, it executes various functions of the electronic device and processes data, thereby monitoring the electronic device as a whole. Optionally, the processor 301 may include one or more processing cores; preferably, the processor 301 may integrate an application processor and a modem processor. Among them, the application processor mainly processes operating storage media, user interfaces, application programs, etc., and the modem processor mainly processes wireless communication. It can be understood that the above modem processor may not be integrated into the processor 301.

[0095] The memory 302 can be used to store software programs and the present application. The processor 301 executes various functional applications and data processing by running the software programs and the present application stored in the memory 302. The memory 302 may mainly include a program storage area and a data storage area. Among them, the program storage area can store operating storage media, application programs required for at least one function, etc.; the data storage area can store data created according to the use of the electronic device. In addition, the memory 302 may include high-speed random access memory, and may also include non-volatile memory, such as at least one magnetic disk storage device, a flash memory device, or other volatile solid-state storage devices. Correspondingly, the memory 302 may also include a memory controller to provide the processor 301 with access to the memory 302.

[0096] Although not shown, the electronic device may also include a display unit, an input unit, a power supply, etc., which will not be elaborated here. Specifically in this embodiment, the processor 301 in the electronic device will, according to the following instructions, load the executable files corresponding to the processes of one or more application programs into the memory 302, and the processor 301 will run the application programs stored in the memory 302 to implement various functions as follows:

[0097] Analyze the original layout to determine the area to be optimized in the original layout;

[0098] Define the distance between the correction layer and the target layer in the area to be optimized as the correction variable;

[0099] Define the root mean square error of the edge position errors of all correction variables as the target evaluation function;

[0100] Based on the target evaluation function, use the annealing algorithm to optimize all correction variables to obtain the target correction variable combination;

[0101] Use the target correction variable combination to correct the original layout to obtain the target layout. Those of ordinary skill in the art can understand that all or part of the steps in the various methods of the above embodiments can be completed by instructions, or by controlling related hardware through instructions. The instructions can be stored in a computer-readable storage medium and loaded and executed by a processor.

[0102] For this reason, an embodiment of the present application provides a storage medium, which stores multiple instructions that can be loaded by a processor to execute the steps in any one of the generation methods provided by the embodiments of the present application. For example, the instructions can perform the following steps:

[0103] Analyze the original layout to determine the area to be optimized in the original layout;

[0104] Define the distance between the correction layer and the target layer in the area to be optimized as the correction variable;

[0105] Define the root mean square error of the edge position errors of all correction variables as the target evaluation function;

[0106] Based on the target evaluation function, use the annealing algorithm to optimize all correction variables to obtain the target correction variable combination;

[0107] Use the target correction variable combination to correct the original layout to obtain the target layout.

[0108] For the specific implementation of each of the above operations, reference can be made to the previous embodiments and will not be elaborated here.

[0109] Among them, the storage medium may include: read-only memory (ROM, Read Only Memory), random access memory (RAM, Random Access Memory), magnetic disk or optical disc, etc.

[0110] Since the instructions stored in the storage medium can execute the steps in any one of the methods provided by the embodiments of the present application, the beneficial effects that can be achieved by any one of the methods provided by the embodiments of the present application can be realized. For details, reference can be made to the previous embodiments and will not be elaborated here.

[0111] The above has introduced in detail the optical proximity correction optimization method, device, storage medium and electronic device provided by the present application. Specific examples are used in this article to elaborate on the principle and implementation manner of the present application. The description of the above embodiments is only used to help understand the core idea of the present application; at the same time, for those skilled in the art, according to the idea of the present application, there will be changes in the specific implementation manner and application scope. In summary, the content of this specification should not be construed as a limitation to the present application.

Claims

1. An optical proximity correction optimization method, characterized in that: include: Analyzing the original layout to determine the area to be optimized in the original layout; The distance between the correction layer and the target layer in the area to be optimized is defined as a correction variable; The root mean square error of the edge position errors of all the correction variables is defined as the target evaluation function; Based on the target evaluation function, all the correction variables are optimized by using an annealing algorithm to obtain a target correction variable combination, including: setting the initial values ​​of all the correction variables to 0; randomly generating a current correction variable combination within a preset value range of the correction variables, and calculating a current evaluation function of the current correction variable combination; comparing the current evaluation function with the target evaluation function, and determining whether to update the target evaluation function according to the comparison result; returning to execute the step of randomly generating a current correction variable combination within the preset value range of the correction variables until the edge position errors of all the correction variables are less than a preset threshold, and taking the current correction variable combination as the target correction variable combination; The original layout is modified using the target correction variable combination to obtain a target layout.

2. The optical proximity correction optimization method according to claim 1, characterized in that: The step of determining whether to update the target evaluation function according to the comparison result includes: If the current evaluation function is smaller than the target evaluation function, the current evaluation function is used as the target evaluation function; If the current evaluation function is greater than or equal to the target evaluation function, it is determined whether to use the current evaluation function as the target evaluation function according to the acceptance probability.

3. The optical proximity correction optimization method according to claim 2, characterized in that: The acceptance probability is: P=exp(−ΔRMS / RMS new ) In the above formula, P is the acceptance probability, ΔRMS is the difference between the current evaluation function and the target evaluation function, and RMS new is the current evaluation function.

4. The optical proximity correction optimization method according to claim 1, characterized in that: The calculating of the current evaluation function of the current correction variable combination comprises: Calculating the edge position error of each correction variable in the current correction variable combination; The root mean square error of all the edge position errors is calculated.

5. The optical proximity correction optimization method according to claim 1, wherein: The analyzing the original layout to determine the area to be optimized in the original layout includes: Performing optical simulation on the original layout to identify a target area where an optical proximity effect exists; An error calculation is performed on the target area, and a region to be optimized is determined from the multiple target areas according to the error calculation result.

6. The optical proximity correction optimization method according to claim 1, characterized in that: The preset threshold is 1 nanometer.

7. An optical proximity correction optimization device, characterized in that: include: A layout analysis unit, used to analyze the original layout to determine the area to be optimized in the original layout; A variable definition unit, used for defining the distance between the correction layer and the target layer in the area to be optimized as a correction variable; A function definition unit, used for defining a root mean square error of edge position errors of all correction variables as a target evaluation function; A variable optimization unit is used to optimize all the correction variables based on the target evaluation function by using an annealing algorithm to obtain a target correction variable combination, including: setting the initial values ​​of all the correction variables to 0; randomly generating a current correction variable combination within a preset value range of the correction variables, and calculating a current evaluation function of the current correction variable combination; comparing the current evaluation function with the target evaluation function, and determining whether to update the target evaluation function according to the comparison result; returning to execute the step of randomly generating the current correction variable combination within the preset value range of the correction variables until the edge position errors of all the correction variables are less than a preset threshold, and taking the current correction variable combination as the target correction variable combination; The layout correction unit is used to correct the original layout using the target correction variable combination to obtain a target layout.

8. A storage medium, characterized in that: The storage medium stores a plurality of instructions, and the instructions are suitable for being loaded by a processor to execute the optical proximity correction optimization method according to any one of claims 1-6.

9. An electronic device, characterized in that: The method comprises a memory, a processor and a computer program stored in the memory and executable on the processor, wherein when the processor executes the computer program, the optical proximity correction optimization method according to any one of claims 1 to 6 is implemented.

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