Photoetching aberration calibration method and device, storage medium and electronic equipment

Abstract

The invention discloses a photoetching aberration calibration method and device, a storage medium and electronic equipment, and the method comprises the steps: obtaining an isolated mask image; generating an initial simulation image training set of photoetching imaging by adopting simulation software based on the isolated mask image; performing Fourier transform and frequency domain truncation on simulation images in the initial simulation image training set to obtain a target simulation image training set; constructing a linear regression matrix of the target simulation image training set and the Zernike coefficient; and calculating the Zernike coefficient of the actually measured photoetching image based on the linear regression matrix and the least square method so as to calibrate the photoetching aberration. According to the scheme, the photoetching aberration calibration efficiency can be improved.

Description

Technical Field

[0001] The embodiments of the present application relate to the field of lithography technology, and specifically to a lithography aberration calibration method, device, storage medium and electronic device. Background Art

[0002] Photolithography is one of the core processes for achieving nanoscale feature pattern transfer in semiconductor manufacturing, and its accuracy directly affects the performance and yield of the chip. In the photolithography process, the aberration of the optical system is one of the main causes of imaging errors. Aberrations mainly include spherical aberration, coma, astigmatism, field curvature, etc., which will cause deviations between the pattern projected on the silicon wafer and the desired pattern, thereby affecting the final manufacturing accuracy.

[0003] Currently, optical lens optimization or online wave aberration calibration is usually used to reduce the impact of aberrations on imaging quality. However, due to the extremely high accuracy requirements for aberration calibration in advanced nodes (such as 7nm and 5nm processes), high-order residual aberrations cannot be completely eliminated during the optical lens manufacturing process. The online wave aberration calibration method requires multiple adjustments and measurements, which is time-consuming and lacks accuracy in high-order aberration detection. Summary of the invention

[0004] The embodiments of the present application provide a lithography aberration calibration method, device, storage medium and electronic device, which can improve the efficiency of lithography aberration calibration.

[0005] In a first aspect, an embodiment of the present application provides a lithography aberration calibration method, comprising: Obtaining an isolated mask image; Based on the isolated mask image, using simulation software to generate an initial simulation image training set for lithography imaging; Performing Fourier transform and frequency domain truncation on the simulated images in the initial simulated image training set to obtain a target simulated image training set; Constructing a linear regression matrix of the target simulation image training set and Zernike coefficients; The Zernike coefficients of the measured lithography image are calculated based on the linear regression matrix and the least square method to calibrate the lithography aberration.

[0006] In the lithography aberration calibration method provided in the embodiment of the present application, the initial simulation image training set of lithography imaging is generated by using simulation software based on the isolated mask image, including: Setting photolithography conditions and a Zernike coefficient group, wherein the Zernike coefficient group includes several groups of Zernike coefficients; Calculating, by simulation software, a planar light intensity distribution diagram of each group of the Zernike coefficients of the isolated mask image under the photolithography conditions; A number of the plane light intensity distribution maps are used as an initial simulation image training set.

[0007] In the lithography aberration calibration method provided in the embodiment of the present application, the Fourier transform and frequency domain truncation are performed on the simulated images in the initial simulated image training set to obtain the target simulated image training set, including: Using Fourier transform, converting each of the plane light intensity distribution diagrams in the initial simulation image training set from a spatial domain image to a frequency domain image; Frequency domain truncation is performed on a number of the frequency domain images to obtain a target simulation image training set.

[0008] In the lithography aberration calibration method provided in the embodiment of the present application, the frequency domain truncation of the plurality of frequency domain images to obtain a target simulation image training set includes: According to the effective frequency range of the optical system, each of the frequency domain images is truncated; Based on inverse Fourier transform, converting the truncated frequency domain image into a spatial domain image; A number of the spatial domain images are used as target simulation image training sets.

[0009] In the lithography aberration calibration method provided in the embodiment of the present application, the step of constructing a linear regression matrix of the target simulation image training set and the Zernike coefficients includes: The principal component analysis method is used to extract the eigenvalues ​​and eigenvectors of the target simulation image training set; Based on the order of the eigenvalues, feature extraction is performed on the eigenvectors to obtain a target feature vector; A linear regression matrix of the target feature vector and the Zernike coefficients is constructed.

[0010] In the lithography aberration calibration method provided in the embodiment of the present application, the principal component analysis method is used to extract the eigenvalues ​​and eigenvectors of the target simulation image training set, including: Representing the target simulation image training set as a data matrix; Calculating a covariance matrix of the data matrix; Perform eigenvalue decomposition on the covariance matrix to obtain eigenvalues ​​and eigenvectors.

[0011] In the lithography aberration calibration method provided in the embodiment of the present application, the step of constructing a linear regression matrix of the target feature vector and the Zernike coefficient includes: Representing a plurality of said target feature vectors as feature matrices; Projecting the data matrix onto the feature matrix to form a principal component matrix; The linear regression matrix is ​​calculated based on the Zernike coefficients and the principal component matrix.

[0012] In a second aspect, an embodiment of the present application provides a lithography aberration calibration device, comprising: An acquisition unit, used for acquiring an isolated mask image; A simulation unit, configured to generate an initial simulation image training set for lithography imaging using simulation software based on the isolated mask image; A conversion unit, used for performing Fourier transform and frequency domain truncation on the simulated images in the initial simulated image training set to obtain a target simulated image training set; A construction unit, used to construct a linear regression matrix of the target simulation image training set and Zernike coefficients; The measuring unit is used to calculate the Zernike coefficients of the measured lithography image based on the linear regression matrix and the least square method to calibrate the lithography aberration.

[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 above-mentioned lithography aberration calibration methods.

[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-mentioned lithography aberration calibration methods when executing the computer program.

[0015] In summary, the lithography aberration calibration method provided by the embodiment of the present application includes acquiring an isolated mask image; based on the isolated mask image, using simulation software to generate an initial simulation image training set of lithography imaging; performing Fourier transform and frequency domain truncation on the simulation images in the initial simulation image training set to obtain a target simulation image training set; constructing a linear regression matrix of the target simulation image training set and the Zernike coefficient; based on the linear regression matrix and the least squares method, calculating the Zernike coefficient of the measured lithography image to calibrate the lithography aberration. This solution can reduce the amount of data analysis on the basis of retaining actual valid data through frequency domain truncation, thereby improving the efficiency of lithography aberration calibration. 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 schematic diagram of an application scenario of the lithography aberration calibration method provided in an embodiment of the present application.

[0018] Figure 2It is a flow chart of the lithography aberration calibration method provided in an embodiment of the present application.

[0019] Figure 3 It is a schematic diagram of the structure of the lithography aberration calibration device provided in an embodiment of the present application.

[0020] Figure 4 It is a schematic diagram of the structure of an electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0021] 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.

[0022] 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.

[0023] 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.

[0024] 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.

[0025] 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.

[0026] Currently, optical lens optimization or online wave aberration calibration is usually used to reduce the impact of aberrations on imaging quality. However, due to the extremely high accuracy requirements for aberration calibration in advanced nodes (such as 7nm and 5nm processes), high-order residual aberrations cannot be completely eliminated during the optical lens manufacturing process. The online wave aberration calibration method requires multiple adjustments and measurements, which is time-consuming and lacks accuracy in high-order aberration detection.

[0027] Based on this, the embodiments of the present application provide a lithography aberration calibration method, device, storage medium and electronic device. Specifically, the lithography aberration calibration 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, Figure 1 As shown, the electronic device can obtain an isolated mask image; based on the isolated mask image, an initial simulation image training set of lithography imaging is generated by using simulation software; the simulation images in the initial simulation image training set are subjected to Fourier transformation and frequency domain truncation to obtain a target simulation image training set; a linear regression matrix of the target simulation image training set and the Zernike coefficients is constructed; the Zernike coefficients of the measured lithography image are calculated based on the linear regression matrix and the least squares method to calibrate the lithography aberration.

[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 2 , Figure 2 : is a schematic diagram of the process of the photolithography aberration calibration method provided in an embodiment of the present application. The specific process of the photolithography aberration calibration method can be as follows: 101. Obtain an isolated mask image.

[0031] The aberrations of the optical system (such as spherical aberration, coma, astigmatism, etc.) will affect the quality of the lithography image. By acquiring a series of isolated mask patterns, the impact of different aberrations on the imaging results can be maximized, thereby obtaining higher accuracy in simulation and frequency domain analysis. This helps to optimize the design of the lithography system and improve the imaging quality.

[0032] In some embodiments, by selecting an isolated mask image with a specific spatial frequency, diffraction order, and directional distribution, it can help simulate the response of the optical system under different conditions to adapt to different optical aberrations and simulation requirements.

[0033] Specifically, a complete mask image may be obtained first, and then a condition is selected to select a portion of the image in the complete mask image as an isolated mask image. The number of complete mask images may be set according to actual conditions, and the embodiment of the present application does not limit it.

[0034] In some embodiments, the selection condition may be a sampling range, a period (Pitch), a critical dimension (CD), etc. For isolated mask images of different pitches, the representation in the frequency domain corresponds to different diffraction orders, and isolated mask images of different CDs correspond to amplitude changes in the diffraction orders.

[0035] For example, a suitable sampling range is selected on the X-axis and Y-axis of the complete mask image. Then, based on the sampling range, isolated mask images of different periods and sizes are selected on the X-axis and Y-axis, respectively. It should be noted that the sampling range, period and size can be set according to actual conditions, and the embodiments of the present application do not limit them.

[0036] 102. Based on the isolated mask image, an initial simulation image training set of lithography imaging is generated using simulation software.

[0037] Specifically, the lithography conditions and the Zernike coefficient group can be set first, and the Zernike coefficient group includes several groups of Zernike coefficients; then, the plane light intensity distribution map of each group of Zernike coefficients of the isolated mask image under the lithography conditions is calculated by simulation software; and the several plane light intensity distribution maps are used as the initial simulation image training set.

[0038] Among them, the photolithography conditions may include illumination conditions, optical parameters, and imaging film parameters. For example, light source polarization, partial coherence factor , numerical aperture NA, wavelength, photoresist refractive index absorption rate, etc.

[0039] Zernike coefficients are used to describe different optical aberrations (such as spherical aberration, astigmatism, etc.). Common Zernike coefficients include Z4, Z7, Z8, Z9, and Z10. Among them, Z4 is spherical aberration, which affects the focus position. Z7 and Z8 are coma, which affect the trail and uniformity of the imaging. Z9 and Z10 are astigmatism, which affect the symmetry of the imaging.

[0040] In order to fully simulate various aberrations in optical systems, it is necessary to calculate Zernike coefficients of different orders and combinations. Taking the 37th-order Zernike coefficients as an example, about 700 different sets of Zernike coefficients can be formed. Each set of Zernike coefficients will affect the imaging effect, and each combination corresponds to a different aberration mode. These Zernike coefficients can be used to generate a series of different optical system states, thereby obtaining a variety of imaging images.

[0041] 103. Perform Fourier transform and frequency domain truncation on the simulated images in the initial simulated image training set to obtain a target simulated image training set.

[0042] Specifically, the simulated image is a spatial domain image. Specifically, Fourier transform can be used to convert each plane light intensity distribution map in the initial simulated image training set from a spatial domain image to a frequency domain image; and frequency domain truncation is performed on several frequency domain images to obtain a target simulated image training set.

[0043] In some embodiments, frequency domain truncation is performed on several frequency domain images to obtain a target simulation image training set, which can be specifically as follows: each frequency domain image is truncated according to an effective frequency range of the optical system; based on an inverse Fourier transform, the truncated frequency domain image is converted into a spatial domain image; and several spatial domain images are used as a target simulation image training set.

[0044] The effective frequency range can be . is the coherence factor, which is used to describe the coherence of the light source.

[0045] In some embodiments, converting the planar light intensity distribution map from a spatial domain image to a frequency domain image may be performed as follows:

[0046] In one embodiment, converting the truncated frequency domain image into a spatial domain image may be performed as follows:

[0047] In the above formula, It is the plane light intensity distribution diagram. is a frequency domain image. D is the sampling range, is the effective frequency range. j is the imaginary number in the Euler formula, which represents the phase change. f and g are the frequency values ​​of the Fourier transform in the x-axis direction and the y-axis direction, respectively.

[0048] From the above, it can be seen that since the frequency domain image is truncated, the data volume of the spatial domain image is also reduced accordingly, thereby effectively reducing the amount of data calculation and storage.

[0049] In one embodiment, converting the truncated frequency domain image into a spatial domain image may be specifically performed as follows:

[0050] In the above formula, is the frequency domain coordinate, is the pupil function, is the mask function, for coefficient, for Equation. m represents the number of frequency domain images, and n represents The number of coefficients, .

[0051] 104. Construct a linear regression matrix of the target simulation image training set and the Zernike coefficients.

[0052] In some embodiments, step 104 is specifically as follows: S1. Principal Component Analysis (PCA) is used to extract the eigenvalues ​​and eigenvectors of the target simulation image training set.

[0053] Specifically, the target simulation image training set can be represented as a data matrix first, then the covariance matrix of the data matrix is ​​calculated, and finally the covariance matrix is ​​subjected to eigenvalue decomposition to obtain eigenvalues ​​and eigenvectors.

[0054] S2. Based on the order of the sizes of several eigenvalues, feature extraction is performed on several eigenvectors to obtain a target feature vector.

[0055] For example, eigenvectors corresponding to the first several eigenvalues ​​may be selected in descending order of eigenvalues ​​as target eigenvectors.

[0056] S3. Construct a linear regression matrix of the target feature vector and the Zernike coefficient.

[0057] It can be understood that the linear regression matrix of the target feature vector and the Zernike coefficient is the linear regression matrix of the spatial domain image and the Zernike coefficient.

[0058] Specifically, several target feature vectors can be represented as feature matrices; the data matrix is ​​projected onto the feature matrix to form a principal component matrix; and the linear regression matrix is ​​calculated based on the Zernike coefficients and the principal component matrix.

[0059] It should be noted that when calculating the linear regression matrix, the least square method can be used to fit the Zernike coefficients and the principal component matrix to obtain the linear regression matrix.

[0060] After PCA, the features of each spatial domain image are simplified into a number of principal components (eigenvalues), which greatly reduces the dimension and complexity of the data. Among them, the Zernike coefficients set in step 102 in this embodiment are Zernike coefficients.

[0061] 105. The Zernike coefficients of the measured lithography image are calculated based on the linear regression matrix and the least square method to calibrate the lithography aberration.

[0062] Specifically, the measured lithography image can be first subjected to Fourier transformation and frequency domain truncation to obtain a measured spatial domain image, and then the measured spatial domain image and a linear regression matrix are fitted using the least squares method to obtain the Zernike coefficients of the measured lithography image.

[0063] After obtaining the Zernike coefficients of the measured lithography image, the optical elements (such as lens groups) or light source parameters (such as numerical aperture NA, lighting conditions) of the lithography machine can be adjusted according to the different components of the Zernike coefficients. For specific aberration types (such as spherical aberration and coma), the corresponding compensation device can be adjusted automatically or manually. The measured Zernike coefficients can also be feedback controlled to adjust the state of the optical system to ensure the best imaging quality under different process conditions.

[0064] In summary, the lithography aberration calibration method provided by the embodiment of the present application includes acquiring an isolated mask image; based on the isolated mask image, using simulation software to generate an initial simulation image training set of lithography imaging; performing Fourier transform and frequency domain truncation on the simulation images in the initial simulation image training set to obtain a target simulation image training set; constructing a linear regression matrix of the target simulation image training set and the Zernike coefficient; calculating the Zernike coefficient of the measured lithography image based on the linear regression matrix and the least squares method to calibrate the lithography aberration. This scheme can reduce the amount of data analysis on the basis of retaining actual valid data through frequency domain truncation, thereby improving the efficiency of lithography aberration calibration.

[0065] In order to better implement the lithography aberration calibration method provided in the embodiment of the present application, the embodiment of the present application also provides a lithography aberration calibration device, wherein the meanings of the terms are the same as those in the above-mentioned lithography aberration calibration method, and the specific implementation details can refer to the description in the method embodiment.

[0066] See also Figure 3 , Figure 32 is a schematic diagram of the structure of the lithography aberration calibration device provided in an embodiment of the present application. The lithography aberration calibration device may include an acquisition unit 201, a simulation unit 202, a conversion unit 203, a construction unit 204 and a measurement unit 205. An acquisition unit 201 is used to acquire an isolated mask image; A simulation unit 202, configured to generate an initial simulation image training set of lithography imaging using simulation software based on the isolated mask image; The conversion unit 203 is used to perform Fourier transformation and frequency domain truncation on the simulated images in the initial simulated image training set to obtain a target simulated image training set; A construction unit 204 is used to construct a linear regression matrix of a target simulation image training set and Zernike coefficients; The measuring unit 205 is used to calculate the Zernike coefficients of the measured lithography image based on the linear regression matrix and the least square method to calibrate the lithography aberration.

[0067] The specific implementation of each of the above units can refer to the above-mentioned embodiment of the photolithography aberration calibration method, which will not be described in detail here.

[0068] In summary, the lithography aberration calibration device provided by the embodiment of the present application can acquire an isolated mask image through the acquisition unit 201; the simulation unit 202 generates an initial simulation image training set of lithography imaging using simulation software based on the isolated mask image; the conversion unit 203 performs Fourier transform and frequency domain truncation on the simulation image in the initial simulation image training set to obtain a target simulation image training set; the construction unit 204 constructs a linear regression matrix of the target simulation image training set and the Zernike coefficient; the actual measurement unit 205 calculates the Zernike coefficient of the actual lithography image based on the linear regression matrix and the least squares method to calibrate the lithography aberration. This solution can reduce the amount of data analysis on the basis of retaining actual valid data through frequency domain truncation, thereby improving the efficiency of lithography aberration calibration.

[0069] The present application also provides an electronic device, in which the photolithography aberration calibration device of the present application can be integrated, such as Figure 4 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 4 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.

[0070] 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.

[0071] 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: Obtaining an isolated mask image; Based on the isolated mask image, an initial simulation image training set of lithography imaging is generated by using simulation software; Performing Fourier transformation and frequency domain truncation on the simulated images in the initial simulated image training set to obtain a target simulated image training set; Construct a linear regression matrix of the target simulation image training set and the Zernike coefficients; The Zernike coefficients of the measured lithography images are calculated based on the linear regression matrix and the least square method to calibrate the lithography aberrations.

[0072] A person of ordinary skill in the art will appreciate that all or part of the steps in the various methods of the above embodiments may be completed by instructions, or by controlling related hardware through instructions. The instructions may be stored in a computer-readable storage medium and loaded and executed by a processor.

[0073] 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 method provided in the embodiment of the present application. For example, the instructions can execute the following steps: Obtaining an isolated mask image; Based on the isolated mask image, an initial simulation image training set of lithography imaging is generated by using simulation software; Performing Fourier transformation and frequency domain truncation on the simulated images in the initial simulated image training set to obtain a target simulated image training set; Construct a linear regression matrix of the target simulation image training set and the Zernike coefficients; The Zernike coefficients of the measured lithography images are calculated based on the linear regression matrix and the least square method to calibrate the lithography aberrations.

[0074] The specific implementation of the above operations can be found in the previous embodiments, which will not be described in detail here.

[0075] The storage medium may include: a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk, etc.

[0076] 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.

[0077] The above respectively introduces in detail the lithography aberration calibration method, device, storage medium and electronic device provided by the present application. 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 methods and application scope. In summary, the content of this specification should not be understood as a limitation on the present application.

Claims

1. A method for calibrating photolithography aberrations, characterized in that: include: Obtaining an isolated mask image; Based on the isolated mask image, using simulation software to generate an initial simulation image training set for lithography imaging; Performing Fourier transform and frequency domain truncation on the simulated images in the initial simulated image training set to obtain a target simulated image training set; Constructing a linear regression matrix of the target simulation image training set and Zernike coefficients; The Zernike coefficients of the measured lithography image are calculated based on the linear regression matrix and the least square method to calibrate the lithography aberration.

2. The lithography aberration calibration method according to claim 1, characterized in that: The step of generating an initial simulation image training set of lithography imaging using simulation software based on the isolated mask image comprises: Setting photolithography conditions and a Zernike coefficient group, wherein the Zernike coefficient group includes several groups of Zernike coefficients; Calculating, by simulation software, a planar light intensity distribution diagram of each group of the Zernike coefficients of the isolated mask image under the photolithography conditions; A number of the plane light intensity distribution maps are used as an initial simulation image training set.

3. The photolithography aberration calibration method according to claim 2, characterized in that: The performing Fourier transform and frequency domain truncation on the simulated images in the initial simulated image training set to obtain a target simulated image training set includes: Using Fourier transform, converting each of the plane light intensity distribution diagrams in the initial simulation image training set from a spatial domain image to a frequency domain image; Frequency domain truncation is performed on a number of the frequency domain images to obtain a target simulation image training set.

4. The photolithography aberration calibration method according to claim 3, characterized in that: The step of performing frequency domain truncation on the plurality of frequency domain images to obtain a target simulation image training set includes: According to the effective frequency range of the optical system, each of the frequency domain images is truncated; Based on inverse Fourier transform, converting the truncated frequency domain image into a spatial domain image; A number of the spatial domain images are used as target simulation image training sets.

5. The photolithography aberration calibration method according to claim 4, characterized in that: The step of constructing a linear regression matrix of the target simulation image training set and the Zernike coefficients includes: The principal component analysis method is used to extract the eigenvalues ​​and eigenvectors of the target simulation image training set; Based on the order of the eigenvalues, feature extraction is performed on the eigenvectors to obtain a target feature vector; A linear regression matrix of the target feature vector and the Zernike coefficients is constructed.

6. The photolithography aberration calibration method according to claim 5, characterized in that: The method of extracting the eigenvalues ​​and eigenvectors of the target simulation image training set by using the principal component analysis method includes: Representing the target simulation image training set as a data matrix; Calculating a covariance matrix of the data matrix; Perform eigenvalue decomposition on the covariance matrix to obtain eigenvalues ​​and eigenvectors.

7. The photolithography aberration calibration method according to claim 6, characterized in that: The step of constructing a linear regression matrix of the target feature vector and the Zernike coefficient comprises: Representing a plurality of said target feature vectors as feature matrices; Projecting the data matrix onto the feature matrix to form a principal component matrix; The linear regression matrix is ​​calculated based on the Zernike coefficients and the principal component matrix.

8. A photolithography aberration calibration device, characterized in that: include: An acquisition unit, used for acquiring an isolated mask image; A simulation unit, configured to generate an initial simulation image training set of lithography imaging using simulation software based on the isolated mask image; A conversion unit, used for performing Fourier transform and frequency domain truncation on the simulated images in the initial simulated image training set to obtain a target simulated image training set; A construction unit, used to construct a linear regression matrix of the target simulation image training set and Zernike coefficients; The measuring unit is used to calculate the Zernike coefficients of the measured lithography image based on the linear regression matrix and the least square method to calibrate the lithography aberration.

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 lithography aberration calibration 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 the processor implements the lithography aberration calibration method according to any one of claims 1 to 7 when executing the computer program.

Images