A method for computing holographic detection optical element processing error global inversion

Abstract

The present application relates to the technical field of optical detection, and particularly relates to a kind of holographic detection optical element processing error global inversion method, comprising: constructing the function relationship of etching depth error about local grating period reciprocal and radial coordinate, as initial etching depth error physical parameterization model;The function relationship of duty cycle error about local grating period reciprocal and radial coordinate is constructed, as initial duty cycle error physical parameterization model;Obtain multiple groups of measured parameters;Multiple groups of measured parameters are substituted into initial etching depth error physical parameterization model and initial duty cycle error physical parameterization model, and etching depth error physical parameterization model and duty cycle error physical parameterization model are obtained;Full aperture design data is brought into etching depth error physical parameterization model and duty cycle error physical parameterization model to obtain etching depth error global distribution and duty cycle error global distribution.The present application is at least beneficial to realize low-cost, high-precision error reconstruction.

Description

Technical Field

[0001] This invention belongs to the field of optical detection technology, and in particular relates to a method for calculating the full-domain inversion of the processing error of holographic detection optical elements. Background Technology

[0002] As modern optical systems develop towards larger apertures and higher steepness, the requirements for the detection accuracy of aspherical optical elements are increasing. As the core compensation element in aspherical null interferometry, the manufacturing accuracy of computational holographic detection optical elements (CGH) directly determines the final detection result. Computational holographic detection optical elements are usually composed of hundreds of millions of micro-nano grating structures, and even small deviations in their etching depth and duty cycle will introduce wavefront errors.

[0003] To assess and correct these errors, researchers both domestically and internationally have conducted extensive work. Some related technologies have proposed a parameterized modeling method based on scalar diffraction theory, attempting to establish a physical relationship between processing parameters and wavefront errors, and using sparse measurement data to invert and estimate the overall error. Other related technologies have proposed an error assessment method that combines microstructure sampling and sub-aperture stitching, using a white light interferometer to conduct on-site measurements of key areas to quantify the specific contribution of processing errors to detection uncertainty.

[0004] However, the existing methods for measuring and evaluating manufacturing errors of computational holographic detection optical elements still have two main problems in practical engineering applications: First, while error assessment methods combining microstructure sampling and sub-aperture stitching can obtain high-resolution data through stitching, using a white light interferometer or atomic force microscope to perform full-field coverage scanning of large-aperture computational holographic detection optical elements (typically with a diameter > 100 mm) often requires stitching thousands of sub-apertures. This method is extremely time-consuming and generates a huge amount of data, making it difficult to achieve rapid, full-domain error detection in engineering. Second, parametric models or conventional interpolation fitting methods often rely only on low-frequency data from a few measurement points, using Zernike polynomials or spline interpolation to fit the full-domain error. This method implicitly assumes that the error changes smoothly in space, ignoring the "micro-load effect" and "proximity effect" commonly found in micro- and nano-fabrication etching. In reality, in the high-frequency, small-period regions at the edges of computational holographic detection optical elements, the error often exhibits drastic nonlinear changes. Traditional interpolation methods cannot capture these high-frequency characteristics, leading to severe distortion in error prediction for critical edge regions.

[0005] Therefore, there is an urgent need for a method that can significantly reduce measurement costs and accurately predict structural errors of the entire aperture, especially in the high-frequency region, based on the physical structure. Summary of the Invention

[0006] In view of this, the present invention aims to provide a method for calculating the global inversion of the processing error of holographic detection optical elements, which is at least beneficial for achieving low-cost and high-precision error reconstruction.

[0007] To achieve the above objectives, the technical solution created by this invention is implemented as follows:

[0008] This invention provides a method for global inversion of the processing error of a holographic detection optical element, comprising: Step 1, based on the micro-load effect, constructing a functional relationship between the etching depth error and the local grating period inverse and radial coordinate as independent variables, as an initial physical parameterization model for the etching depth error; Step 2, based on the proximity effect, constructing a functional relationship between the duty cycle error and the local grating period inverse and radial coordinate as independent variables, as an initial physical parameterization model for the duty cycle error; Step 3, measuring the actual etching depth and actual duty cycle corresponding to multiple measurement points on the surface of the holographic detection optical element, and then... Step 4: Obtain multiple sets of measured parameters based on the measured etching depth and measured duty cycle. Substitute these measured parameters into the physical parameterization models of the initial etching depth error and the initial duty cycle error, and solve for the corresponding coefficients and biases of the physical parameterization model of the initial etching depth error to obtain the physical parameterization model of the etching depth error. Similarly, solve for the corresponding coefficients and biases of the physical parameterization model of the initial duty cycle error to obtain the physical parameterization model of the duty cycle error. Step 5: Substitute the full-aperture design data of the optical element to be tested for holographic detection into the physical parameterization models of the etching depth error and the duty cycle error to obtain the global distribution of the etching depth error and the global distribution of the duty cycle error.

[0009] Furthermore, in step three, each set of measured parameters includes the radial coordinates of the corresponding measurement point, the reciprocal of the grating period, the measured etching depth error, and the measured duty cycle error.

[0010] Furthermore, the expression for the physical parameterization model of the initial etching depth error is as follows: ; Indicates the etching depth error. This represents the reciprocal of the local grating period. Represents radial coordinates, For micro load factor, The radial non-uniformity coefficient is... The first bias constant is used as the first bias constant. In step four, the corresponding coefficients of the physical parameterization model of the initial etching depth error include the micro-load coefficient and the radial non-uniformity coefficient. The bias corresponding to the physical parameterization model of the initial etching depth error is the first bias constant.

[0011] Furthermore, the expression for the physical parameterization model of the initial duty cycle error is as follows: ; Indicates duty cycle error. This represents the reciprocal of the local grating period. Represents radial coordinates, This is the proximity effect coefficient. This is the non-uniformity coefficient of development. The second bias constant is used as the second bias constant. In step four, the corresponding coefficients of the physical parameterization model of the initial duty cycle error include the proximity effect coefficient and the development non-uniformity coefficient. The bias corresponding to the physical parameterization model of the initial duty cycle error is the second bias constant.

[0012] Furthermore, in step five, the full-aperture design data of the optical element to be tested for computational holographic detection includes: the grating period and radial coordinates corresponding to each coordinate point of the optical element to be tested for computational holographic detection.

[0013] Furthermore, in step four, multiple sets of measured parameters are substituted into the physical parameterization model of the initial etching depth error and the physical parameterization model of the initial duty cycle error to form an overdetermined set of equations; the corresponding coefficients and biases of the physical parameterization model of the initial etching depth error are solved using the least squares method or regression algorithm, as well as the corresponding coefficients and biases of the physical parameterization model of the initial duty cycle error.

[0014] Furthermore, the number of measurement points ranges from 8 to 50.

[0015] Furthermore, the micro-load effect in step one indicates that the etching depth error is negatively correlated with the inverse of the local grating period.

[0016] Furthermore, the proximity effect in step two indicates that the duty cycle error is positively correlated with the inverse of the local grating period.

[0017] Furthermore, in step three, the measured etching depth and measured duty cycle corresponding to each measurement point are measured using a profilometer, white light interferometer, or atomic force microscope. The measured etching depth error is obtained based on the measured etching depth and the designed etching depth, and the measured duty cycle error is obtained based on the measured duty cycle and the designed duty cycle.

[0018] Compared with existing technologies, the present invention achieves the following beneficial effects: The full-domain inversion method for processing errors of computational holographic detection optical elements provided by the present invention does not require full-field high-resolution scanning of the computational holographic detection optical elements. It only requires measuring dozens of sparse measurement points to complete the full-domain calibration, reducing the measurement time from several days to tens of minutes, and greatly improving the detection efficiency; The present invention introduces a physical parameterization model based on micro-nano processing mechanisms (basic micro-load effect and proximity effect), which can accurately describe the high-frequency edge errors that traditional interpolation methods cannot fit, significantly improving the error reconstruction capability for high-steep regions of computational holographic detection optical elements, which is conducive to improving prediction accuracy; In addition, the physical parameterization models for etching depth error and duty cycle error provided by the present invention reflect the inherent characteristics of the process equipment. They are not only applicable to current computational holographic detection optical elements, but also have reference value for other optical elements processed in the same batch, and have strong universality. Attached Figure Description

[0019] The accompanying drawings, which form part of this invention, are used to provide a further understanding of the invention. The illustrative embodiments and descriptions of the invention are used to explain the invention and do not constitute an undue limitation of the invention. In the drawings:

[0020] Figure 1 A flowchart illustrating the implementation of the method for calculating the full-domain inversion of the processing error of a holographic detection optical element as described in an embodiment of the present invention;

[0021] Figure 2 The design drawing of the test grating device described in the embodiment of the present invention;

[0022] Figure 3 (a) is a schematic diagram illustrating the linear relationship between etching depth error and local frequency as described in the embodiment of the present invention;

[0023] Figure 3 (b) is a schematic diagram illustrating the linear relationship between duty cycle error and local frequency as described in the embodiment of the present invention.

[0024] Figure 4 (a) is a schematic diagram illustrating the linear relationship between etching depth error and grating period as described in the embodiment of the present invention;

[0025] Figure 4 (b) is a schematic diagram illustrating the linear relationship between the duty cycle error and the grating period as described in the embodiment of the present invention. Detailed Implementation

[0026] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and specific embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and do not constitute a limitation thereof.

[0027] It should be noted that, unless otherwise specified, the embodiments and features described in the present invention can be combined with each other.

[0028] In the description of this invention, it should be understood that the terms "center," "longitudinal," "lateral," "length," "width," "thickness," "upper," "lower," "front," "rear," "left," "right," "vertical," "horizontal," "top," "bottom," "inner," "outer," "clockwise," and "counterclockwise," etc., indicating orientations or positional relationships based on the orientations or positional relationships shown in the accompanying drawings, are only for the convenience of describing this invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation, and therefore should not be construed as a limitation on this invention. Furthermore, the terms "first," "second," etc., are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of indicated technical features. Thus, features defined with "first," "second," etc., may explicitly or implicitly include one or more of that feature. In the description of this invention, unless otherwise stated, "a plurality of" means two or more.

[0029] In the description of this invention, it should be noted that, unless otherwise explicitly specified and limited, the terms "installation," "connection," and "linking" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral connection; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; and they can refer to the internal connection of two components. Those skilled in the art will understand the specific meaning of the above terms in this invention based on the specific circumstances.

[0030] The invention will now be described in detail with reference to the accompanying drawings and embodiments.

[0031] refer to Figure 1This invention provides a method for calculating the full-domain inversion of processing errors in holographic detection optical elements, comprising: Step 1, based on the micro-load effect, constructing a functional relationship between the etching depth error and the local grating period reciprocal and radial coordinates as independent variables, as an initial physical parameterization model for the etching depth error; Step 2, based on the proximity effect, constructing a functional relationship between the duty cycle error and the local grating period reciprocal and radial coordinates as independent variables, as an initial physical parameterization model for the duty cycle error; Step 3, measuring the measured etching depth and measured duty cycle corresponding to multiple measurement points on the surface of the holographic detection optical element, and obtaining the... Step 4: Substitute multiple sets of measured parameters into the initial etching depth error physical parameterization model, solve the corresponding coefficients and biases of the initial etching depth error physical parameterization model, and then obtain the etching depth error physical parameterization model. Substitute multiple sets of measured parameters into the initial duty cycle error physical parameterization model, solve the corresponding coefficients and biases of the initial duty cycle error physical parameterization model, and then obtain the duty cycle error physical parameterization model. Step 5: Substitute the full-aperture design data of the optical element to be tested for computational holographic detection into the etching depth error physical parameterization model to obtain the global distribution of etching depth error. Substitute the full-aperture design data of the optical element to be tested for computational holographic detection into the duty cycle error physical parameterization model to obtain the global distribution of duty cycle error.

[0032] The radial coordinate r exists in the physical parameterization model of etching depth error and the physical parameterization model of air ratio error in the form of r. 2 r 2 Characterizing development nonuniformity. In the micro / nano fabrication (such as spin coating and development processes) of optical elements for computational holographic detection, the substrate is usually rotated at high speed. The centrifugal force of the developer, concentration diffusion, and rinsing process all produce macroscopically centrosymmetric gradient changes. Therefore, the macroscopic error distribution caused by development nonuniformity is usually strongly correlated with the distance of the corresponding position from the center (i.e., the radial coordinate r). In physical parameterization modeling, development nonuniformity can be represented by a polynomial r of the radial coordinate r. 2 To perform mathematical representation.

[0033] Furthermore, in step three, each set of measured parameters includes the radial coordinates of the corresponding measurement point, the reciprocal of the grating period, the measured etching depth error, and the measured duty cycle error.

[0034] Furthermore, the expression for the physical parameterization model of the initial etching depth error is as follows:

[0035] ;

[0036] Indicates the etching depth error. It represents the reciprocal of the local grating period (i.e., spatial frequency or pattern density). Represents radial coordinates, Characterizing development non-uniformity, For micro-load factor, micro-load factor Characterizing local microscopic effects, Radial non-uniformity coefficient, radial non-uniformity coefficient Characterizes the macroscopic etching non-uniformity of the machine tool. The first bias constant, the first bias constant Characterize the inherent bias of the system; in step four, the corresponding coefficients of the physical parameterization model of the initial etching depth error include the micro-load coefficient and the radial non-uniformity coefficient, and the bias corresponding to the physical parameterization model of the initial etching depth error is the first bias constant.

[0037] Furthermore, the expression for the physical parameterization model of the initial duty cycle error is as follows:

[0038] ;

[0039] Indicates duty cycle error. This represents the reciprocal of the local grating period. Represents radial coordinates, Characterizing development non-uniformity, This is the proximity effect coefficient. This is the non-uniformity coefficient of development. The second bias constant is used as the second bias constant. In step four, the corresponding coefficients of the physical parameterization model of the initial duty cycle error include the proximity effect coefficient and the development non-uniformity coefficient. The bias corresponding to the physical parameterization model of the initial duty cycle error is the second bias constant.

[0040] Furthermore, in step five, the full-aperture design data of the optical element to be tested for computational holographic detection includes: the grating period and radial coordinates corresponding to each coordinate point of the optical element to be tested for computational holographic detection.

[0041] Furthermore, in step four, multiple sets of measured parameters are substituted into the physical parameterization model of the initial etching depth error and the physical parameterization model of the initial duty cycle error, respectively, to form an overdetermined set of equations; the corresponding coefficients and biases of the physical parameterization model of the initial etching depth error are solved using the least squares method or regression algorithm, as well as the corresponding coefficients and biases of the physical parameterization model of the initial duty cycle error.

[0042] Furthermore, the number of measurement points is in the range of 8 to 50. From a mathematical solution perspective, each physical parameterization model has 3 unknown coefficients, so at least 4 measurement points are needed to construct an overdetermined system of equations. The number of measurement points in the range of 8 to 50 can ensure both sparse sampling and solution accuracy.

[0043] Among them, the optical element to be tested in computational holographic detection can be a computational holographic detection optical element used for aspherical zero-position detection, the micro-load effect is the micro-load effect in inductively coupled plasma etching, and the proximity effect is the electron scattering proximity effect in electron beam lithography.

[0044] Furthermore, the micro-load effect in step one indicates that the etching depth error is negatively correlated with the inverse of the local grating period.

[0045] Furthermore, the proximity effect in step two indicates that the duty cycle error is positively correlated with the inverse of the local grating period.

[0046] Furthermore, in step three, the measured etching depth and duty cycle corresponding to each measurement point are measured using a profilometer, white light interferometer, or atomic force microscope. Based on the measured etching depth and the designed etching depth, the measured etching depth error is obtained: Measured etching depth error = Measured etching depth - Designed etching depth. Similarly, based on the measured duty cycle and the designed duty cycle, the measured duty cycle error is obtained: Measured duty cycle = Measured duty cycle - Designed duty cycle. In other words, several discrete feature positions are selected on the surface of the optical element to be tested in the computational holographic detection as measurement points. Using detection equipment such as a profilometer, white light interferometer, or atomic force microscope, the actual processing data of the etching depth and duty cycle at these measurement points are obtained. It is important to note that the selection of measurement points should cover the entire range of changes in grating period from large to small and local pattern density from low to high, ensuring that the measurement points can fully reflect the changing laws of etching micro-load effects and electron beam proximity effects, and guaranteeing the stability and solution accuracy of the physical model parameters.

[0047] The present invention provides a method for full-domain inversion of the processing error of optical components for computational holographic detection. It establishes a parameterized model using the principle of micro-nano processing dynamics, identifies physical process parameters through a small number of sparse sampling points, and then reconstructs the full-aperture structural error distribution by combining design data, thereby achieving low-cost and high-precision error calibration.

[0048] To verify the effectiveness and accuracy of the full-domain inversion method for computational holographic detection optical element fabrication error provided by this invention, a physical effect verification experiment based on real micro-nano fabrication technology was conducted, specifically as follows: A test grating with variable period (local pattern density changing from sparse to dense) was designed and fabricated, such as... Figure 2As shown, the test grating device comprises several regions with different periods. The grating line density is designed to gradually transition from low to high density, meaning the grating period gradually decreases. The fabrication process employs reactive ion etching (RIE), which is completely consistent with the manufacturing of actual large-aperture computational holographic detection optical elements. Several discrete feature locations are selected on the surface of the grating device under test as measurement points. A white light interferometer is used to measure the etching depth and duty cycle of the aforementioned regions with different densities, obtaining the actual processing data of the etching depth and duty cycle at these locations. The processing error value for each region is then extracted, where the processing error value = measured value - design target value. The detection results are shown below. Figure 3 and Figure 4 As shown, according to Figure 3 As shown in (a) and (b), as the grating lines become denser, the etching depth error exhibits a clear monotonically decreasing trend. Furthermore, the etching depth shows the largest negative deviation in the region with the densest grating lines. This result is consistent with the theoretical prediction of the micro-loading effect, namely, that during etching, the diffusion of the reactive gas within the narrow trench is hindered, resulting in a lower etching rate in the dense grating line region compared to the sparse grating line region, thus producing a shallower etching depth (negative error). According to... Figure 4 As shown in (a) and (b), the duty cycle error increases with the increase of pattern density. The duty cycle error reaches its maximum value in the densest region. This is consistent with the proximity effect in electron beam exposure, that is, the dense region accumulates more backscattered electron energy, which leads to the lines becoming wider or the duty cycle shifting after development.

[0049] The accuracy of the full-domain inversion method for calculating the processing error of optical elements for holographic detection provided by this invention is verified by comparing the "set true value" with the "inversion calculation value". The specific steps are as follows:

[0050] The first step is to construct an ideal computational holographic detection optical element model and a known periodic distribution, as follows: A standard Fresnel zone plate is defined as the optical element model for the computational holographic detection under test, with the following parameters: aperture D = 50 mm, operating wavelength λ = 632.8 nm, focal length f = 100 mm. According to the zone plate formula, the local periodicity at any radius r on its surface is... It is known that the local period decreases with increasing radius; therefore, it is possible to have arbitrary coordinates of the full aperture of this computational holographic detection optical element. Ideal design cycle ;

[0051] The second step is to customize the etching depth error, as follows: In order to simulate real manufacturing defects, based on the micro-load effect law verified by the aforementioned experiments, a real etching depth error distribution for the entire aperture is artificially defined. Using this as the verification standard, we assume the actual etching depth error. Mainly due to micro-load effect (and period) (related) and the macroscopic distribution of the machine (with radial radius) (Related) Composition, the etching depth error function is set as: ;in, To set the micro-load factor, you can Set as a known constant, To set the etching non-uniformity coefficient, one can... Set as a known constant, To generate the error distribution of the set etching depth for all pixels across the entire aperture, which is random high-frequency noise, this function is used. ;

[0052] The third step involves using the full-domain inversion method for fabrication error of computational holographic detection optical elements provided by this invention. Specifically, only eight discrete measurement points can be selected on the surface of the computational holographic detection optical element, and the coordinates of these eight points can be recorded. Corresponding design cycle and the measured etching depth error In the simulation experiment, the etching depth error distribution generated in the second step was used. The values ​​at the corresponding coordinate points are used as the measured etching depth error. Where i represents the sequence number of the 8 data sets, i = 1, 2...8, the 8 data sets are... Substituting the initial etching depth error physical parameterization model provided by this invention, the undetermined coefficients are solved using the least squares method to obtain the etching depth error physical parameterization model, combined with the ideal design period known in the first step. Calculate the error distribution of the predicted etching depth for the entire aperture. The obtained predicted etching depth error distribution Error distribution with the etching depth set in the second step Point-to-point subtraction is performed to obtain the residual map. In the fourth step, the comparison results show that the predicted etching depth error distribution accurately restores the error trend of high center and low edge caused by micro-load effect. The PV value (peak-valley value) of etching depth error is set to 150nm. After reconstruction by the computational holographic detection optical element processing error global inversion method provided by this invention, the PV value of the residual is only 8nm (mainly the preset random noise). Therefore, the computational holographic detection optical element processing error global inversion method provided by this invention has high accuracy.

[0053] It should be understood that the various forms of processes shown above can be used to reorder, add, or delete steps. For example, the steps described in this invention disclosure can be executed in parallel, sequentially, or in different orders, as long as the desired result of the technical solution disclosed in this invention can be achieved, and this is not limited herein.

[0054] The specific embodiments described above do not constitute a limitation on the scope of protection of this invention. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this invention should be included within the scope of protection of this invention.

Claims

1. A method for calculating the full-domain inversion of fabrication errors of holographic detection optical elements, characterized in that, include: Step 1: Based on the micro-load effect, using the reciprocal of the local grating period and the radial coordinate as independent variables, construct a functional relationship between the etching depth error and the reciprocal of the local grating period and the radial coordinate, as the initial physical parameterization model for the etching depth error; Step 2: Based on the proximity effect, using the reciprocal of the local grating period and the radial coordinate as independent variables, construct a functional relationship between the duty cycle error and the reciprocal of the local grating period and the radial coordinate, as the initial physical parameterization model of the duty cycle error; Step 3: Measure the actual etching depth and actual duty cycle corresponding to multiple measurement points on the surface of the holographic detection optical element, and obtain multiple sets of measured parameters based on the actual etching depth and actual duty cycle; Step 4: Substitute multiple sets of measured parameters into the physical parameterization model of the initial etching depth error and the physical parameterization model of the initial duty cycle error, solve the corresponding coefficients and biases of the physical parameterization model of the initial etching depth error, and thus obtain the physical parameterization model of the etching depth error, and solve the corresponding coefficients and biases of the physical parameterization model of the initial duty cycle error, and thus obtain the physical parameterization model of the duty cycle error. Step 5: Input the full-aperture design data of the optical element to be tested for computational holographic detection into the physical parameterization model of etching depth error and the physical parameterization model of duty cycle error to obtain the global distribution of etching depth error and duty cycle error.

2. The method for calculating the full-domain inversion of fabrication errors of holographic detection optical elements according to claim 1, characterized in that, In step three, each set of measured parameters includes the radial coordinates of the corresponding measurement point, the reciprocal of the grating period, the measured etching depth error, and the measured duty cycle error.

3. The method for calculating the full-domain inversion of fabrication errors of holographic detection optical elements according to claim 1, characterized in that, The expression for the physical parameterization model of the initial etching depth error is as follows: ; Indicates the etching depth error. This represents the reciprocal of the local grating period. Represents radial coordinates, For micro load factor, The radial non-uniformity coefficient is... The first bias constant is used as the first bias constant. In step four, the corresponding coefficients of the physical parameterization model of the initial etching depth error include the micro-load coefficient and the radial non-uniformity coefficient. The bias corresponding to the physical parameterization model of the initial etching depth error is the first bias constant.

4. The method for calculating the full-domain inversion of fabrication errors of holographic detection optical elements according to claim 1, characterized in that, The expression for the physical parameterization model of the initial duty cycle error is as follows: ; Indicates duty cycle error. This represents the reciprocal of the local grating period. Represents radial coordinates, This is the proximity effect coefficient. This is the non-uniformity coefficient of development. The second bias constant is used as the second bias constant. In step four, the corresponding coefficients of the physical parameterization model of the initial duty cycle error include the proximity effect coefficient and the development non-uniformity coefficient. The bias corresponding to the physical parameterization model of the initial duty cycle error is the second bias constant.

5. The method for calculating the full-domain inversion of fabrication errors of holographic detection optical elements according to claim 1, characterized in that, In step five, the full-aperture design data of the optical element to be tested for computational holographic detection includes: the grating period and radial coordinates corresponding to each coordinate point of the optical element to be tested for computational holographic detection.

6. The method for calculating the full-domain inversion of fabrication errors of holographic detection optical elements according to claim 1, characterized in that, In step four, multiple sets of measured parameters are substituted into the physical parameterization model of the initial etching depth error and the physical parameterization model of the initial duty cycle error to form an overdetermined set of equations. The corresponding coefficients and biases of the physical parameterization model of the initial etching depth error are solved using the least squares method or regression algorithm, as well as the corresponding coefficients and biases of the physical parameterization model of the initial duty cycle error.

7. The method for calculating the full-domain inversion of fabrication errors of holographic detection optical elements according to claim 1, characterized in that, The number of measurement points ranges from 8 to 50.

8. The method for calculating the full-domain inversion of fabrication errors of holographic detection optical elements according to claim 1, characterized in that, The micro-load effect in step one indicates that the etching depth error is negatively correlated with the inverse of the local grating period.

9. The method for calculating the full-domain inversion of fabrication errors of holographic detection optical elements according to claim 1, characterized in that, The proximity effect in step two indicates that the duty cycle error is positively correlated with the inverse of the local grating period.

10. The method for calculating the full-domain inversion of processing errors of holographic detection optical elements according to claim 1, characterized in that, In step three, the measured etching depth and measured duty cycle corresponding to each measurement point are measured using a profilometer, white light interferometer, or atomic force microscope. The measured etching depth error is obtained based on the measured etching depth and the designed etching depth, and the measured duty cycle error is obtained based on the measured duty cycle and the designed duty cycle.

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