Optical proximity correction optimization method and device, storage medium and electronic equipment

Abstract

The invention discloses an optical proximity correction optimization method and device, a storage medium and electronic device.The optical proximity correction optimization method comprises the steps that an original layout is analyzed to determine a to-be-optimized area in the original layout; defining the distance between the correction layer and the target layer in the to-be-optimized region as a correction variable; defining the root mean square error of the edge position error of all the correction variables as a target evaluation function; based on the target evaluation function, adopting an annealing algorithm to optimize all the correction variables so as to obtain a target correction variable combination; and correcting the original layout by using the target correction variable combination to obtain a target layout. According to the scheme, defect patterns generated due to mutual influence of correction variables are avoided.

Description

Technical Field

[0001] The embodiments of the present application relate to the field of semiconductor technology, and specifically to an optical proximity correction optimization method, device, storage medium, and electronic device. Background Art

[0002] With the continuous advancement of semiconductor manufacturing technology, photolithography has become a key step in manufacturing microelectronic components. However, at the micrometer and nanometer scale, the optical proximity effect (OPE) often occurs during the photolithography process, causing the pattern of the layout to be distorted, affecting the manufacturing accuracy of the chip. In order to solve this problem, it is usually necessary to perform optical proximity correction (OPC) on the original layout.

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

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

[0005] In a first aspect, an embodiment of the present application provides an optical proximity correction optimization method, comprising: 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; The original layout is modified using the target correction variable combination to obtain a target layout.

[0006] In the optical proximity correction optimization method provided in the embodiment of the present application, based on the evaluation function, an annealing algorithm is used to optimize all the correction variables to obtain a target correction variable combination, including: Setting the initial values ​​of all the correction variables to 0; Randomly generate a current correction variable combination within a preset value range of the correction variable, and calculate a current evaluation function of the current correction variable combination; 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 a current correction variable combination within the preset value range of the correction variable until the edge position errors of all the correction variables are less than a preset threshold, and use the current correction variable combination as the target correction variable combination.

[0007] In the optical proximity correction optimization method provided in the embodiment of the present application, 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.

[0008] In the optical proximity correction optimization method provided in the embodiment of the present application, 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.

[0009] In the optical proximity correction optimization method provided in the embodiment of the present application, the current evaluation function of the current correction variable combination is calculated, including: 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.

[0010] In the optical proximity correction optimization method provided in the embodiment of the present application, the analyzing of 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.

[0011] In the optical proximity correction optimization method provided in the embodiment of the present application, the preset threshold is 1 nanometer.

[0012] In a second aspect, an embodiment of the present application provides an optical proximity correction optimization device, comprising: 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, configured to optimize all the correction variables by using an annealing algorithm based on the target evaluation function to obtain a 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.

[0013] In a third aspect, the present application provides a storage medium storing a plurality of instructions, wherein the instructions are suitable for loading by a processor to execute any of the optical proximity correction optimization methods described above.

[0014] In a fourth aspect, the present application provides an electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements any of the above-described optical proximity correction optimization methods when executing the computer program.

[0015] In summary, the optical proximity correction optimization method provided in the embodiment 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; based on the target evaluation function, using an annealing algorithm to optimize all the correction variables to obtain a target correction variable combination; using the target correction variable combination to correct the original layout to obtain a target layout. This solution uses an annealing algorithm to optimize the optical proximity correction process, and by accurately adjusting the correction variables and optimizing the layout, it can effectively avoid defective graphics caused by the mutual influence of the correction variables, thereby improving the accuracy and efficiency of the optical proximity correction. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below 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 work.

[0017] Figure 1 It is a flow chart of the optical proximity correction optimization method provided in the embodiment of the present application.

[0018] Figure 2It is a schematic diagram of layers provided in an embodiment of the present application.

[0019] Figure 3 It is a schematic diagram of the correction variables provided in the embodiment of the present application.

[0020] Figure 4 It is a schematic diagram of the structure of the optical proximity correction optimization device provided in an embodiment of the present application.

[0021] Figure 5 It is a schematic diagram of the structure of an electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0022] Exemplary embodiments will be described in detail herein, examples of which are shown in the accompanying drawings. When the following description refers to the drawings, the same numbers in different drawings represent the same or similar elements unless otherwise indicated. The implementations described in the following exemplary embodiments do not represent all implementations consistent with the present application. Instead, they are merely examples of devices and methods consistent with some aspects of the present application as detailed in the appended claims.

[0023] It should be noted that, in this article, the terms "include", "comprises" 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 includes other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, an element defined by the sentence "includes a ..." does not exclude the existence of other identical elements in the process, method, article or device including the 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 by their explanation in the specific embodiment or further combined with the context of the specific embodiment.

[0024] It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0025] In the subsequent description, the suffixes such as "module", "component" or "unit" used to represent elements are only used to facilitate the description of the present application, and have no specific meanings. Therefore, "module", "component" or "unit" can be used in a mixed manner.

[0026] In the description of the present application, it should be noted that the terms "upper", "lower", "left", "right", "inner", "outer", etc., indicating the orientation or positional relationship, are based on the orientation or positional relationship shown in the drawings, and are 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 cannot be understood as limiting the present application. In addition, terms such as "first" and "second" are only used for descriptive purposes and cannot be understood as indicating or implying relative importance.

[0027] 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. 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.

[0028] 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 a correction variable; then define the root mean square error of the edge position error of all correction variables as a target evaluation function; then based on the target evaluation function, use an annealing algorithm to optimize all correction variables to obtain a target correction variable combination; finally, use the target correction variable combination to correct the original layout to obtain a target layout.

[0029] 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 is not intended to limit the priority order of the embodiments.

[0030] See also Figure 1 , Figure 1 : is a schematic diagram of the process of the optical proximity correction optimization method provided in the embodiment of the present application. The specific process of the optical proximity correction optimization method can be as follows: 101. Analyze the original layout to determine the area to be optimized in the original layout.

[0031] Original version Figure 1It is usually created by 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.

[0032] In some embodiments, after acquiring the original layout, optical simulation can be performed on the original layout to identify the target area where the optical proximity effect exists; then, error calculation is performed on the target area, and the area to be optimized is determined from multiple target areas based on the error calculation results.

[0033] In an embodiment of the present application, the error calculation of the target area can be performed based on the edge position error (Edge Placement Error, EPE). EPE is an indicator used to measure the distance between the contour layer (Contour layer) and the target layer (Target layer) in OPC. Specifically, an edge position error threshold can be preset first, and then the distance between the contour layer and the target layer in each target area is calculated, and the distance is compared with the edge position error threshold. When the 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.

[0034] 102. Define the distance between the correction layer and the target layer in the area to be optimized as a correction variable.

[0035] Among them, Figure 2 As shown in the figure, the correction layer (OPC Layer) refers to the pattern corrected by optical proximity. The target pattern refers to the ideal design pattern, which represents the final requirements of chip functions and circuits. The outline layer is the actual imaging pattern simulated by the correction layer through lithography simulation.

[0036] For example, when the area to be optimized includes a first area to be optimized, a second area to be optimized, and a third area to be optimized, the correction variable in the first area to be optimized can be as follows: Figure 3 As shown, it is the distance between each edge of the correction layer and the corresponding edge in the target layer, that is, X1, X2, X3 and X4.

[0037] Similarly, the correction variables of the second area to be optimized may be X5, X6, X7 and X8. The correction variables of the third area to be optimized may be X9, X10, X11 and X12.

[0038] 103. The root mean square error of the edge position errors of all correction variables is defined as the objective evaluation function.

[0039] 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 the root mean square error (RSM) of all edge position errors is calculated and defined as the target evaluation function.

[0040] For example, the edge position errors corresponding to X1, X2, X3, X4, X5, X6, X7, X8, X9, X10, X11 and X12 can be calculated respectively to obtain RSM1, RSM2, RSM3, RSM4, RSM5, RSM6, RSM7, RSM8, RSM9, RSM10, RSM11 and RSM12. Then, the root mean square errors of RSM1, RSM2, RSM3, RSM4, RSM5, RSM6, RSM7, RSM8, RSM9, RSM10, RSM11 and RSM12 can be calculated.

[0041] 104. Based on the target evaluation function, the annealing algorithm is used to optimize all correction variables to obtain the target correction variable combination.

[0042] Specifically, the initial values ​​of all correction variables can be set to 0; the current correction variable combination is randomly generated within the preset value range of the correction variables, and the current evaluation function of the current correction variable combination is calculated; the current evaluation function is compared with the target evaluation function, and it is determined whether to update the target evaluation function based on the comparison result; return 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 error of all correction variables is less than the preset threshold, and the current correction variable combination is used as the target correction variable combination.

[0043] For example, when the preset value range is -10 to 10, the value ranges of X1, X2, X3, X4, X5, X6, X7, X8, X9, X10, X11, and X12 can be as follows: X1=-10,-9,-8,…,0,…8,9,10; X2=-10,-9,-8,…,0,…8,9,10; … X12=-10,-9,-8,…,0,…8,9,10.

[0044] In the embodiment of the present application, the preset threshold is 1 nanometer.

[0045] In some embodiments, the current correction variable combination can be generated within the preset value range of the correction variable using the Monte Carlo method to ensure that the value of each correction variable is evenly distributed, thereby ensuring the comprehensiveness and randomness of the target evaluation function calculation. In this way, it is possible to effectively avoid falling into a local optimal solution and increase the probability of finding a global optimal solution.

[0046] The current evaluation function for calculating the current correction variable combination may specifically be: calculating the edge position error of each correction variable in the current correction variable combination; and 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 correction variable combination may refer to step 103, which will not be described in detail in this embodiment.

[0047] In the embodiment of the present application, it can be determined whether to update the target evaluation function based on the Metropolis criterion and according to the comparison result.

[0048] Specifically, if the current evaluation function is less 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, whether to use the current evaluation function as the target evaluation function is determined according to the acceptance probability.

[0049] Among them, the acceptance probability can be: 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. The value range of P is [0,1].

[0050] 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 (that is, the current evaluation function is used as the target evaluation function); otherwise, the new solution is rejected (that is, the target evaluation function is not updated).

[0051] The Metropolis criterion achieves a dynamic balance between global search and local convergence by judging ΔRMS and combining it with a random probability acceptance mechanism. For applications that optimize optical proximity correction, it can effectively avoid falling into local optimality in complex layout corrections while improving the final optimization accuracy.

[0052] 105. The original layout is modified using the target correction variable combination to obtain the target layout.

[0053] Specifically, each target correction variable in the target correction variable combination can be used to correct the region to be optimized in the original layout, thereby obtaining a target layout without defective patterns.

[0054] In summary, the optical proximity correction optimization method provided in the embodiment 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 error 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; using the target correction variable combination to correct the original layout to obtain a target layout. This scheme uses an annealing algorithm to optimize the optical proximity correction process. By accurately adjusting the correction variables and optimizing the layout, it can effectively avoid defective graphics caused by the mutual influence of the correction variables, thereby improving the accuracy and efficiency of the optical proximity correction. In addition, the global search capability of the annealing algorithm can better find the optimal solution, ensuring that the optical proximity correction process can meet high-precision manufacturing requirements.

[0055] In order to better implement the optical proximity correction optimization method provided in the embodiment of the present application, the embodiment of the present application also provides an optical proximity correction optimization device, wherein 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 embodiment.

[0056] See also Figure 4 , Figure 4 : is a schematic diagram of the structure of the optical proximity correction optimization device provided in the 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, A layout analysis unit 201 is used to analyze the original layout to determine the area to be optimized in the original layout; A variable definition unit 202, used to define the distance between the correction layer and the target layer in the area to be optimized as a correction variable; A function definition unit 203, used to define the root mean square error of the edge position errors of all correction variables as a target evaluation function; The variable optimization unit 204 is used to optimize 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 is used to correct the original layout using the target correction variable combination to obtain the target layout.

[0057] The specific implementation of each of the above units can refer to the above-mentioned embodiment of the optical proximity correction optimization method, which will not be described one by one here.

[0058] In summary, the optical proximity correction optimization device provided in the embodiment of the present application can be used to analyze the original layout through the layout analysis unit 201 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 the correction variable; the function definition unit 203 defines the root mean square error of the edge position error of all correction variables as the target evaluation function; the variable optimization unit 204 optimizes all correction variables based on the target evaluation function using the annealing algorithm to obtain the target correction variable combination; the layout correction unit 205 corrects the original layout using the target correction variable combination to obtain the target layout. This scheme uses the annealing algorithm to optimize the optical proximity correction process. By accurately adjusting the correction variables and optimizing the layout, the defective graphics caused by the mutual influence of the correction variables can be effectively avoided, thereby improving the accuracy and efficiency of the optical proximity correction. In addition, the global search capability 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.

[0059] The present application also provides an electronic device, in which the optical proximity correction optimization device of the present application can be integrated, such as Figure 5 As shown, it shows a schematic diagram of the structure of the electronic device involved in the embodiment of the present application, specifically: The electronic device may include one or more processors 301 of processing cores and one or more computer-readable storage media memories 302 and other components. Those skilled in the art will appreciate that Figure 5 The electronic device structure shown in the figure does not constitute a limitation on the electronic device, and may include more or fewer components than shown in the figure, or combine certain components, or arrange the components differently. The processor 301 is the control center of the electronic device, which uses various interfaces and lines to connect various parts of the entire electronic device, and executes various functions of the electronic device and processes data by running or executing the software program and / or the present application stored in the memory 302, and calling the data stored in the memory 302, so as to monitor 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, wherein the application processor mainly processes the operation storage medium, user interface and application program, etc., and the modem processor mainly processes wireless communication. It is understandable that the above-mentioned modem processor may not be integrated into the processor 301.

[0060] 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, wherein the program storage area may store an operating storage medium, an application required for at least one function, etc.; the data storage area may store data created according to the use of the electronic device, etc. In addition, the memory 302 may include a high-speed random access memory, and may also include a non-volatile memory, such as at least one disk storage device, a flash memory device, or other volatile solid-state storage devices. Accordingly, the memory 302 may also include a memory controller to provide the processor 301 with access to the memory 302.

[0061] Although not shown, the electronic device may further include a display unit, an input unit, a power supply, etc., which will not be described in detail herein. Specifically in this embodiment, the processor 301 in the electronic device will load the executable files corresponding to the processes of one or more application programs into the memory 302 according to the following instructions, and the processor 301 will run the application programs stored in the memory 302, thereby realizing various functions, as follows: Analyze 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 correction variables is defined as the objective evaluation function; Based on the target evaluation function, the annealing algorithm is used to optimize all correction variables to obtain the target correction variable combination; The target correction variable combination is used to correct the original layout to obtain the target layout. A person skilled 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, and the instructions can be stored in a computer-readable storage medium and loaded and executed by a processor.

[0062] To this end, an embodiment of the present application provides a storage medium in which a plurality of instructions are stored, and the instructions can be loaded by a processor to execute the steps in any one of the generation methods provided in the embodiment of the present application. For example, the instructions can execute the following steps: Analyze 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 correction variables is defined as the objective evaluation function; Based on the target evaluation function, the annealing algorithm is used to optimize all correction variables to obtain the target correction variable combination; The target correction variable combination is used to correct the original layout to obtain the target layout.

[0063] The specific implementation of the above operations can be found in the previous embodiments, which will not be described in detail here.

[0064] The storage medium may include: a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk, etc.

[0065] Since the instructions stored in the storage medium can execute the steps in any method provided in the embodiments of the present application, the beneficial effects that can be achieved by any method provided in the embodiments of the present application can be achieved. Please refer to the previous embodiments for details and will not be repeated here.

[0066] The optical proximity correction optimization method, device, storage medium and electronic device provided by the present application are respectively introduced in detail above. Specific examples are used in this article to illustrate the principles and implementation methods 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 technical personnel in this field, according to the idea of ​​the present application, there will be changes in the specific implementation method and application scope. In summary, the content of this specification should not be understood as a limitation on 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; 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: Based on the 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 generate a current correction variable combination within a preset value range of the correction variable, and calculate a current evaluation function of the current correction variable combination; 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 a current correction variable combination within the preset value range of the correction variable until the edge position errors of all the correction variables are less than a preset threshold, and use the current correction variable combination as the target correction variable combination.

3. The optical proximity correction optimization method according to claim 2, 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.

4. The optical proximity correction optimization method according to claim 3, 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.

5. The optical proximity correction optimization method according to claim 2, 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.

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

7. The optical proximity correction optimization method according to claim 2, characterized in that: The preset threshold is 1 nanometer.

8. 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, configured to optimize all the correction variables by using an annealing algorithm based on the target evaluation function to obtain a 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.

9. 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 to 7.

10. 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 7 is implemented.

Images