Method and apparatus for fast polarization de-rotation in forward modeling of thin film measurements

Abstract

The present application relates to a kind of forward modeling fast depolarization method in thin film measurement, its method includes: obtaining the wavelength sequence of a group of measurement spectrum, by forward modeling, the first stoke vector corresponding to each wavelength point of the wavelength sequence is obtained;According to the number of preset Gaussian nodes, node sequence and the weight value of each node are calculated;Based on the node sequence and preset depolarization parameter, each wavelength point of the wavelength sequence is depolarized, and a plurality of depolarization wavelength points are obtained;Based on the first stoke vector corresponding to each depolarization wavelength point, the stoke vector sequence corresponding to the plurality of depolarization wavelength points is calculated by interpolation method;Based on the stoke vector sequence of the plurality of depolarization wavelength points and the weight of corresponding node, the forward modeling spectrum after the wavelength point depolarization is calculated.The present application is reconstructed by Lagrange interpolation method and Gaussian function, stoke vector update and depolarization forward modeling mode, improve the calculation speed of forward modeling depolarization of thin film structure.

Description

Technical Field

[0001] This invention belongs to the field of optical and semiconductor thin film material measurement technology, specifically relating to a method and apparatus for rapid de-polarization in forward modeling during thin film measurement. Background Technology

[0002] In the semiconductor industry, extracting the critical structural parameter of semiconductor thin-film nanomaterial thickness plays a crucial role in improving product quality and yield in manufacturing. Optical scattering measurement, compared to traditional atomic microscopy, scanning electron microscopy, and transmission electron microscopy, offers advantages such as speed, low cost, non-contact, non-destructive testing, and ease of integration, thus finding widespread application in advanced process monitoring and manufacturing. However, optical scattering measurement is not a "what you see is what you get" method; it requires extracting the structural parameters from the measured spectrum, making it essentially a model-based measurement method.

[0003] In thin film measurements, the LM nonlinear regression algorithm commonly used to extract the structural parameters from the spectrum is mainly based on optical forward modeling. Currently, the commonly used thin film optical forward modeling is based on the thin film transfer matrix. Therefore, the speed of thin film structural parameter extraction largely depends on the speed of forward modeling based on the thin film transfer matrix. With wavelength depolarization, the number of wavelength points *m* in forward modeling expands to the product of the number of Gaussian nodes *a* and the number of wavelength points *n* in the band, i.e., *m* = *a* *n*. This significantly increases the time consumption of LM nonlinear regression. Therefore, proposing a fast depolarization method for forward modeling is of great significance for realizing rapid measurement of the thickness of semiconductor thin film nanomaterials. Summary of the Invention

[0004] To improve the computational speed of forward modeling depolarization in thin film structures, a first aspect of the present invention provides a method for rapid depolarization in forward modeling during thin film measurement, comprising: acquiring a wavelength sequence of a set of measured spectra; obtaining a first Stokes vector corresponding to each wavelength point of the wavelength sequence through forward modeling; calculating a node sequence according to a preset number of Gaussian nodes; calculating a weight value of each node according to the node sequence; depolarizing each wavelength point of the wavelength sequence based on the node sequence and preset depolarization parameters to obtain multiple depolarized wavelength points; calculating a Stokes vector sequence corresponding to the multiple depolarized wavelength points using an interpolation algorithm based on the first Stokes vector corresponding to each depolarized wavelength point; calculating a second Stokes vector corresponding to each wavelength point based on the Stokes vector sequence of the multiple depolarized wavelength points and the weights of the corresponding nodes; and calculating the forward modeling spectrum of the wavelength point after depolarization based on the second Stokes vector corresponding to each wavelength point.

[0005] In some embodiments of the present invention, calculating the weight value of each node based on the node sequence includes: substituting the node sequence into a Gaussian function and calculating the Gaussian function value of each node to obtain the weight value of each node.

[0006] Furthermore, the node sequence is obtained by arranging the floating-point number of Gaussian nodes at equal intervals.

[0007] In some embodiments of the present invention, the step of calculating the sequence of Stokes vectors corresponding to the plurality of depolarization wavelength points by interpolation algorithm based on the first Stokes vector corresponding to each depolarization wavelength point includes: calculating the Stokes vector corresponding to each depolarization wavelength point by Lagrange interpolation algorithm based on the correspondence between each wavelength point of the wavelength sequence and the first Stokes vector.

[0008] Furthermore, the interpolation algorithm also includes the Lagrange algorithm, spline interpolation algorithm, or linear interpolation algorithm.

[0009] In some embodiments of the present invention, the step of calculating the second Stoke vector corresponding to each wavelength point based on the Stoke vector sequence of the plurality of depolarization wavelength points and the weights of the corresponding nodes includes: multiplying each Stoke vector in the Stoke vector sequence by the corresponding node weight to obtain an updated Stoke vector sequence; and summing all the updated Stoke vector sequences to obtain the second Stoke vector corresponding to each wavelength point.

[0010] A second aspect of the present invention provides a rapid depolarization apparatus for forward modeling in thin film measurement, comprising: an acquisition module for acquiring a wavelength sequence of a set of measured spectra, and obtaining a first Stokes vector corresponding to each wavelength point of the wavelength sequence through forward modeling; a weighting module for calculating a node sequence based on a preset number of Gaussian nodes; and calculating a weight value for each node based on the node sequence; an interpolation module for depolarizing each wavelength point of the wavelength sequence based on the node sequence and preset depolarization parameters to obtain multiple depolarized wavelength points; and calculating a Stokes vector sequence corresponding to the multiple depolarized wavelength points based on the first Stokes vector corresponding to each depolarized wavelength point using an interpolation algorithm; a first calculation module for calculating a second Stokes vector corresponding to each wavelength point based on the Stokes vector sequence of the multiple depolarized wavelength points and the weights of the corresponding nodes; and a second calculation module for calculating the forward modeling spectrum of the wavelength point after depolarization based on the second Stokes vector corresponding to each wavelength point.

[0011] A third aspect of the present invention provides an electronic device comprising: one or more processors; and a storage device for storing one or more programs, wherein when the one or more programs are executed by the one or more processors, the one or more processors implement the fast depolarization method for forward modeling in thin film measurement provided in the first aspect of the present invention.

[0012] A fourth aspect of the present invention provides a computer-readable medium having a computer program stored thereon, wherein the computer program, when executed by a processor, implements the fast depolarization method for forward modeling in thin film measurement provided in the first aspect of the present invention.

[0013] The beneficial effects of this invention are:

[0014] This invention, in the case of wavelength depolarization, depolarizes a single wavelength point (wave1) into multiple wavelength points. Then, it uses Lagrange interpolation to directly interpolate the Stokes vectors corresponding to these multiple wavelength points. These Stokes vectors are then multiplied by their corresponding node weights to obtain updated Stokes vectors. Finally, these Stokes vectors are summed to obtain a single Stokes vector, which is used to calculate the spectrum corresponding to wave1. This significantly reduces the number of forward modeling steps in LM nonlinear regression, thereby greatly improving the time required for extracting structural parameters and ultimately significantly reducing the time required for thin film measurements. Attached Figure Description

[0015] Figure 1 This is a schematic diagram of the basic process of a fast depolarization method for forward modeling in thin film measurement in some embodiments of the present invention;

[0016] Figure 2 This is a schematic diagram of the specific process of the forward modeling and rapid depolarization method in thin film measurement in some embodiments of the present invention;

[0017] Figure 3 These are schematic diagrams of the thin film morphology structure in some embodiments of the present invention;

[0018] Figure 4 This is a comparison diagram of the prior art in some embodiments of the present invention and the time-consuming forward modeling debiasing method adopted in this application;

[0019] Figure 5 This is a comparison chart of the SiO2 thickness error extracted by the prior art in some embodiments of the present invention and the time-consuming forward modeling de-biasing method used in this application;

[0020] Figure 6 This is a schematic diagram of the structure of a rapid depolarization device for forward modeling in thin film measurement in some embodiments of the present invention;

[0021] Figure 7 This is a schematic diagram of the structure of an electronic device in some embodiments of the present invention. Detailed Implementation

[0022] The principles and features of the present invention are described below with reference to the accompanying drawings. The examples given are only for explaining the present invention and are not intended to limit the scope of the present invention.

[0023] In actual optical scattering measurements, when using the LM nonlinear regression algorithm to extract the parameters of the structure under test, the number of forward modeling steps increases significantly in the case of wavelength depolarization, which greatly increases the time required for LM nonlinear regression fitting and consequently the time required for the final measurement.

[0024] To enable the forward modeling process to quickly de-bias and obtain the forward spectrum during the LM nonlinear regression fitting process, a scheme for rapid de-biasing of forward modeling needs to be proposed.

[0025] refer to Figure 1 and Figure 2 In a first aspect of the present invention, a method for rapid depolarization of forward modeling in thin film measurement is provided, comprising: S100. acquiring a wavelength sequence of a set of measured spectra, and obtaining a first Stokes vector corresponding to each wavelength point of the wavelength sequence through forward modeling; S200. calculating a node sequence according to a preset number of Gaussian nodes; calculating a weight value of each node according to the node sequence; S300. depolarizing each wavelength point of the wavelength sequence based on the node sequence and a preset depolarization parameter to obtain multiple depolarized wavelength points; calculating a Stokes vector sequence corresponding to the multiple depolarized wavelength points using an interpolation algorithm based on the first Stokes vector corresponding to each depolarized wavelength point; S400. calculating a second Stokes vector corresponding to each wavelength point based on the Stokes vector sequence of the multiple depolarized wavelength points and the weights of the corresponding nodes; S500. calculating the forward modeling spectrum of the wavelength point after depolarization based on the second Stokes vector corresponding to each wavelength point.

[0026] It is understood that the spectrum described in this invention can be Mueller, NCS, psidelta, reflectance R, or transmittance T. Originally, after wavelength depolarization, a single wavelength point wave1 yielded gauss_nodes_num wavelength points, requiring forward modeling gauss_nodes_num times to calculate the final corresponding spectrum spectrum1. Now, only one forward modeling plus gauss_nodes_num-1 Lagrange interpolation is needed to calculate the final corresponding spectrum spectrum1, greatly improving the speed of forward modeling depolarization calculation.

[0027] In step S100 of some embodiments of the present invention, a wavelength sequence of a set of measured spectra is obtained, and a first Stokes vector corresponding to each wavelength point of the wavelength sequence is obtained through forward modeling.

[0028] Specifically, a set of wavelength sequences from measured spectra is given as the modeling wavelength sequence [wave1, wave2, ..., wave_n], denoted as [wavelength]. The total number of wavelengths is n. The Stokes vector corresponding to each wavelength point is modeled in a forward manner using the thin film transfer matrix calculation method, denoted as [stokes].

[0029] Understandably, there are n Stokes vectors in [stokes], which can be represented as [stokes1, stokes2, ..., stokes_n]. Each Stokes vector is a vector consisting of four elements.

[0030] In step S200 of some embodiments of the present invention, a node sequence is calculated according to a preset number of Gaussian nodes; and a weight value for each node is calculated according to the node sequence. The step of calculating the weight value for each node according to the node sequence includes: substituting the node sequence into a Gaussian function and calculating the Gaussian function value for each node to obtain the weight value for each node.

[0031] Specifically, given the number of Gaussian nodes gauss_nodes_num, the node sequence [gauss_x] is calculated based on the number of Gaussian nodes. The node sequence is then substituted into the Gaussian function y = f(x) to calculate the y value corresponding to each node, which is the node weight [gauss_y].

[0032] It should be noted that the node sequence [gauss_x] consists of floating-point numbers of gauss_nodes_num, evenly spaced from -1 to 1. The Gaussian function used here has a peak center x-coordinate of 0, meaning the Gaussian curve is symmetric about the y-axis.

[0033] In step S300 of some embodiments of the present invention, based on the node sequence and preset depolarization parameters, each wavelength point of the wavelength sequence is depolarized to obtain multiple depolarized wavelength points; based on the first Stokes vector corresponding to each depolarized wavelength point, the Stokes vector sequence corresponding to the multiple depolarized wavelength points is calculated by an interpolation algorithm.

[0034] Specifically, for a wavelength point wave1 (any wavelength point), it is first de-biased using the node sequence [gauss_x] and the wavelength de-biasing parameter wave_dep_param to obtain gauss_nodes_num wavelengths, denoted as [wave1_list]. Here, [wave1_list] = wave1 * wave_dep_param * [gauss_x], and the number of wavelength points in [wave1_list] is gauss_nodes_num.

[0035] Next, the Lagrange interpolation algorithm is used to interpolate the Stokes vector value corresponding to each wavelength point in the [wave1_list] sequence based on the correspondence between [wavelength] and [stokes], denoted as [stokes1_list]. It should be noted that each [stokes1_list] includes gauss_nodes_num Stokes vectors.

[0036] Optionally, the Lagrange interpolation algorithm described above can be replaced with a spline interpolation algorithm or a linear interpolation algorithm.

[0037] In step S400 of some embodiments of the present invention, the calculation of the second Stoke vector corresponding to each wavelength point based on the Stoke vector sequence of the plurality of depolarization wavelength points and the weights of the corresponding nodes includes: multiplying each Stoke vector in the Stoke vector sequence by the corresponding node weight to obtain an updated Stoke vector sequence; and summing all the updated Stoke vector sequences to obtain the second Stoke vector corresponding to each wavelength point.

[0038] Specifically, each vector in the [stokes1_list] sequence is multiplied by its corresponding node weight to obtain [stokes1_gauss_list]. Then, all vectors in [stokes1_gauss_list] are summed to obtain the final Stokes vector S1.

[0039] In step S400 of some embodiments of the present invention, the forward modeling spectrum after depolarization of the wavelength point is calculated based on the second Stokes vector corresponding to each wavelength point.

[0040] Specifically, the spectrum spectrum1 is calculated through S1, which is the forward modeling spectrum corresponding to wavelength point wave1 after wavelength depolarization.

[0041] refer to Figures 3 to 5 The experimental materials used Figure 3 The thin film morphology structure was used as a sample for spectral sampling. An ellipsometer developed by a certain company was used to measure the spectrum of the sample. One hundred points of the spectrum of a single thin film structure were sampled, and 100 sets of NCS spectra were extracted. With wavelength depolarization enabled, LM nonlinear regression fitting based on conventional wavelength depolarization forward modeling was first used, followed by LM nonlinear regression fitting based on forward modeling and rapid depolarization calculation in this invention, to extract the SiO2 thickness corresponding to the 100 sets of NCS spectra. Figure 4 For a comparison of the time consumption of the two methods (the second half describes the method described in this application), Figure 5 The SiO2 thickness error values ​​extracted by both methods show that the error between the measured results is within 10.－6 The results are basically identical; in terms of time consumption, the method of forward modeling and rapid debiasing of this invention was adopted, which improved the speed of extracting structural parameters by LM nonlinear regression fitting by about 3 times, thus verifying that the method achieved a very good speed-up effect.

[0042] Example 2

[0043] refer to Figure 6 In a second aspect, the present invention provides a rapid depolarization device 1 for forward modeling in thin film measurement, comprising: an acquisition module 11, configured to acquire a wavelength sequence of a set of measured spectra, and obtain a first Stokes vector corresponding to each wavelength point of the wavelength sequence through forward modeling; a weighting module 12, configured to calculate a node sequence according to a preset number of Gaussian nodes; and calculate a weight value for each node according to the node sequence; an interpolation module 13, configured to depolarize each wavelength point of the wavelength sequence based on the node sequence and a preset depolarization parameter to obtain multiple depolarized wavelength points; and calculate a Stokes vector sequence corresponding to the multiple depolarized wavelength points through an interpolation algorithm based on the first Stokes vector corresponding to each depolarized wavelength point; a first calculation module 14, configured to calculate a second Stokes vector corresponding to each wavelength point based on the Stokes vector sequence of the multiple depolarized wavelength points and the weights of the corresponding nodes; and a second calculation module 15, configured to calculate the forward modeling spectrum of the wavelength point after depolarization based on the second Stokes vector corresponding to each wavelength point.

[0044] Further, the first calculation module 14 includes: a first calculation unit, used to multiply each Stokes vector in the Stokes vector sequence by the corresponding node weight to obtain an updated Stokes vector sequence; and a second calculation unit, used to add all the updated Stokes vector sequences to obtain a second Stokes vector corresponding to each wavelength point.

[0045] Example 3

[0046] refer to Figure 7 A third aspect of the present invention provides an electronic device comprising: one or more processors; and a storage device for storing one or more programs, wherein when the one or more programs are executed by the one or more processors, the one or more processors implement the method of the first aspect of the present invention.

[0047] Electronic device 500 may include a processing unit (e.g., a central processing unit, a graphics processing unit, etc.) 501, which can perform various appropriate actions and processes according to a program stored in read-only memory (ROM) 502 or a program loaded from storage device 508 into random access memory (RAM) 503. The RAM 503 also stores various programs and data required for the operation of electronic device 500. The processing unit 501, ROM 502, and RAM 503 are interconnected via bus 504. An input / output (I / O) interface 505 is also connected to bus 504.

[0048] Typically, the following devices can be connected to I / O interface 505: input devices 506 including, for example, touchscreens, touchpads, keyboards, mice, cameras, microphones, accelerometers, gyroscopes, etc.; output devices 507 including, for example, liquid crystal displays (LCDs), speakers, vibrators, etc.; storage devices 508 including, for example, hard disks; and communication devices 509. Communication device 509 allows electronic device 500 to communicate wirelessly or wiredly with other devices to exchange data. Although Figure 7 An electronic device 500 with various devices is shown; however, it should be understood that it is not required to implement or possess all of the devices shown. More or fewer devices may be implemented or possessed alternatively. Figure 7 Each box shown can represent a device or multiple devices as needed.

[0049] Specifically, according to embodiments of this disclosure, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, embodiments of this disclosure include a computer program product comprising a computer program carried on a computer-readable medium, the computer program containing program code for performing the methods shown in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via a communication device 509, or installed from a storage device 508, or installed from a ROM 502. When the computer program is executed by a processing device 501, it performs the functions defined in the methods of embodiments of this disclosure. It should be noted that the computer-readable medium described in embodiments of this disclosure can be a computer-readable signal medium or a computer-readable storage medium, or any combination thereof. A computer-readable storage medium can be, for example,—but not limited to—an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples of computer-readable storage media may include, but are not limited to: electrical connections having one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof. In embodiments of this disclosure, a computer-readable storage medium may be any tangible medium containing or storing a program that can be used by or in connection with an instruction execution system, apparatus, or device. In embodiments of this disclosure, a computer-readable signal medium may include a data signal propagated in baseband or as part of a carrier wave, carrying computer-readable program code. Such propagated data signals may take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. A computer-readable signal medium may also be any computer-readable medium other than a computer-readable storage medium, which can send, propagate, or transmit a program for use by or in connection with an instruction execution system, apparatus, or device. Program code contained on a computer-readable medium may be transmitted using any suitable medium, including but not limited to: wires, optical fibers, RF (radio frequency), etc., or any suitable combination thereof.

[0050] The aforementioned computer-readable medium may be included in the aforementioned electronic device; or it may exist independently and not assembled into the electronic device. The aforementioned computer-readable medium carries one or more computer programs, which, when executed by the electronic device, cause the electronic device to:

[0051] Computer program code for performing the operations of embodiments of this disclosure can be written in one or more programming languages ​​or a combination thereof. Programming languages ​​include object-oriented programming languages—such as Java, Smalltalk, C++, and Python—and conventional procedural programming languages—such as the "C" language or similar programming languages. The program code can be executed entirely on the user's computer, partially on the user's computer, as a standalone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving remote computers, the remote computer can be connected to the user's computer via any type of network—including a local area network (LAN) or a wide area network (WAN)—or can be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0052] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of this disclosure. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those indicated in the drawings. For example, two consecutively indicated blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should be noted that each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, can be implemented using a dedicated hardware-based system that performs the specified function or operation, or using a combination of dedicated hardware and computer instructions.

[0053] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A method for rapid de-polarization in forward modeling during thin film measurement, characterized in that, include: A wavelength sequence of a set of measured spectra is obtained, and the first Stokes vector corresponding to each wavelength point in the wavelength sequence is obtained through forward modeling; Calculate the node sequence based on the preset number of Gaussian nodes; calculate the weight value of each node based on the node sequence. Based on the node sequence and preset depolarization parameters, each wavelength point of the wavelength sequence is depolarized to obtain multiple depolarized wavelength points; based on the first Stokes vector corresponding to each depolarized wavelength point, the Stokes vector sequence corresponding to the multiple depolarized wavelength points is calculated by an interpolation algorithm. Based on the Stokes vector sequence of the multiple depolarization wavelength points and the weights of the corresponding nodes, calculate the second Stokes vector corresponding to each wavelength point; Based on the second Stokes vector corresponding to each wavelength point, the forward modeling spectrum after depolarization of the wavelength point is calculated.

2. The method for rapid de-polarization in forward modeling during thin film measurement according to claim 1, characterized in that, The calculation of the weight value of each node based on the node sequence includes: Substitute the node sequence into the Gaussian function and calculate the Gaussian function value for each node to obtain the weight value for each node.

3. The method for rapid de-polarization in forward modeling during thin film measurement according to claim 2, characterized in that, The node sequence is obtained by arranging the floating-point number of Gaussian nodes at equal intervals.

4. The method for rapid de-polarization in forward modeling during thin film measurement according to claim 1, characterized in that, The step of calculating the sequence of Stokes vectors corresponding to the plurality of depolarization wavelength points using an interpolation algorithm based on the first Stokes vector corresponding to each depolarization wavelength point includes: Based on the correspondence between each wavelength point in the wavelength sequence and the first Stokes vector, the Stokes vector corresponding to each depolarized wavelength point is calculated using the Lagrange interpolation algorithm.

5. The method for rapid de-polarization in forward modeling during thin film measurement according to claim 4, characterized in that, The interpolation algorithm also includes spline interpolation algorithm or linear interpolation algorithm.

6. The method for rapid de-polarization in forward modeling during thin film measurement according to claim 1, characterized in that, The calculation of the second Stokes vector corresponding to each wavelength point based on the Stokes vector sequence of the multiple depolarization wavelength points and the weights of the corresponding nodes includes: Multiply each Stok vector in the Stok vector sequence by its corresponding node weight to obtain the updated Stok vector sequence; Add all the updated Stokes vector sequences together to obtain the second Stokes vector corresponding to each wavelength point.

7. A rapid de-polarization device for forward modeling in thin film measurement, characterized in that, include: The acquisition module is used to acquire a wavelength sequence of a set of measured spectra, and obtain the first Stokes vector corresponding to each wavelength point of the wavelength sequence through forward modeling; The weighting module is used to calculate the node sequence based on a preset number of Gaussian nodes; Calculate the weight value of each node based on the node sequence; An interpolation module is used to de-polarize each wavelength point of the wavelength sequence based on the node sequence and preset de-polarization parameters to obtain multiple de-polarized wavelength points; and to calculate the Stokes vector sequence corresponding to the multiple de-polarized wavelength points based on the first Stokes vector corresponding to each de-polarized wavelength point through an interpolation algorithm. The first calculation module is used to calculate the second Stoke vector corresponding to each wavelength point based on the Stoke vector sequence of the multiple depolarization wavelength points and the weights of the corresponding nodes. The second calculation module is used to calculate the forward modeling spectrum after depolarization of the wavelength point based on the second Stokes vector corresponding to each wavelength point.

8. The rapid de-polarization device for forward modeling in thin film measurement according to claim 7, characterized in that, The first computing module includes: The first calculation unit is used to multiply each Stokes vector in the Stokes vector sequence by the corresponding node weight to obtain the updated Stokes vector sequence. The second calculation unit is used to add up all the updated Stokes vector sequences to obtain the second Stokes vector corresponding to each wavelength point.

9. An electronic device, comprising: One or more processors; A storage device for storing one or more programs, which, when executed by one or more processors, cause the one or more processors to implement the fast depolarization method for forward modeling in thin film measurements as described in any one of claims 1 to 6.

10. A computer-readable medium having a computer program stored thereon, wherein, When the computer program is executed by the processor, it implements the fast depolarization method for forward modeling in thin film measurement as described in any one of claims 1 to 6.

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