Thickness measuring and resolving method for optical thin film

Abstract

The invention relates to the technical field of material thickness measurement, and discloses a thickness measurement resolving method of an optical thin film. The method comprises the following steps: acquiring an interference spectrum signal of the optical thin film through an interference spectrum method; acquiring the actual reflectivity of the optical thin film; on the basis of the relation between the reflectivity of the optical thin film and the thickness of the thin film, the thickness of the optical thin film is searched by adopting a hybrid optimization algorithm formed by a simulated annealing algorithm and a genetic algorithm, so that the deviation degree between the theoretical reflectivity corresponding to the searched thickness of the thin film and the actual reflectivity is minimum; wherein when the hybrid optimization algorithm is adopted to search the film thickness, the genetic algorithm is utilized to perform global search to obtain an initial individual close to global optimum, and the simulated annealing algorithm is utilized to perform local search on the basis of the initial individual to obtain a target individual closer to global optimum, so that the measurement precision of the optical film thickness is improved.

Description

Technical Field

[0001] The invention relates to the technical field of material thickness measurement, and in particular to a method for measuring and calculating the thickness of an optical film. Background Art

[0002] In scientific research and engineering applications, material thickness measurement is an important task, especially the thickness measurement of transparent materials from nanometers to millimeters has a wide range of application value. This range of thickness measurement technology plays a key role in semiconductor manufacturing, optical component coating, solar cells, coating technology, etc. For example, in microelectronics manufacturing, accurate measurement of film thickness is crucial to the function and performance of the chip; in the coating industry, thickness measurement can be used to control the uniformity and anti-corrosion performance of the coating; in optical component manufacturing, measuring the thickness of optical films can ensure accurate control of transmittance and reflectivity. Therefore, the thickness measurement technology of transparent materials from nanometers to millimeters plays a vital role in the production and detection needs of many fields.

[0003] As a non-contact spectral measurement method, interference spectroscopy is widely used to measure the thickness and optical parameters of transparent or semi-transparent films with thickness ranging from nanometers to micrometers in the fields of semiconductors, coatings, LCDs, optical components, solar cells, polymer films, and touch screens. However, the current interference spectroscopy has low measurement accuracy for optical film thickness. Summary of the invention

[0004] The object of the present invention is to provide a method for measuring and calculating the thickness of an optical film, which can improve the measurement accuracy of the thickness of the optical film.

[0005] In order to solve the above technical problems, an embodiment of the present invention provides a method for measuring the thickness of an optical film, comprising the following steps: Obtaining interference spectrum signals of the optical film to be measured by interference spectroscopy; Obtain the actual reflectivity of the optical film; Based on the relationship between the reflectivity of the optical film and its film thickness revealed by the interference spectroscopy method, a hybrid optimization algorithm formed by a simulated annealing algorithm and a genetic algorithm is used to search for the film thickness of the optical film so as to minimize the deviation between the theoretical reflectivity and the actual reflectivity of the optical film corresponding to the searched film thickness; Among them, when the hybrid optimization algorithm is used to search for film thickness, a genetic algorithm is used to perform a global search to obtain an initial individual close to the global optimum, and based on the initial individual, a simulated annealing algorithm is used to perform a local search to obtain a target individual closer to the global optimum.

[0006] In some optional embodiments, there is a first functional relationship between the reflectivity of the optical film and the film thickness of the optical film, the refractive index of the optical film, the extinction coefficient of the optical film, the refractive index of the substrate, the extinction coefficient of the substrate, the refractive index of air, and the wavelength of the interference spectrum signal; The method of using a hybrid optimization algorithm formed by a simulated annealing algorithm and a genetic algorithm to search for the film thickness of the optical film includes: A hybrid optimization algorithm is adopted to search for the film thickness, refractive index and extinction coefficient of the optical film through the refractive index of the substrate, the extinction coefficient of the substrate, the refractive index of the air, the wavelength of the interference spectrum signal and the first functional relationship.

[0007] The film thickness, refractive index and extinction coefficient of the optical film are searched by a hybrid optimization algorithm through the refractive index of the substrate, the extinction coefficient of the substrate, the refractive index of the air and the wavelength of the interference spectrum signal.

[0008] In some optional embodiments, there is a second functional relationship between the refractive index of the optical film, the extinction coefficient of the optical film, and the wavelength of the interference spectrum signal, and the second functional relationship is described by a Cauchy dispersion model; Before the hybrid optimization algorithm formed by the simulated annealing algorithm and the genetic algorithm is used to search for the film thickness of the optical film, the method further includes: According to the Cauchy dispersion model, the search for the refractive index of the optical film and the search for the extinction coefficient of the optical film are respectively converted into the search for the first preset constant and the search for the second preset constant.

[0009] In some optional embodiments, the Cauchy dispersion model is expressed by the following formula: ; ; In the formula, The third functional relationship between the refractive index of the optical film and the wavelength of the interference spectrum signal is represented by: The fourth functional relationship between the extinction coefficient of the optical film and the wavelength of the interference spectrum signal is represented by: λ represents the wavelength of the interference spectrum signal, Both represent preset constants that are independent of the wavelength of the interference spectrum signal.

[0010] In some optional embodiments, the degree of deviation between the theoretical reflectivity and the actual reflectivity of the optical film corresponding to the searched film thickness is specifically a minimum mean square error value between the theoretical reflectivity and the actual reflectivity.

[0011] In some optional embodiments, the minimum mean square error between the theoretical reflectivity and the actual reflectivity is expressed by the following formula: ; In the formula, represents the number of sampling points of the interference spectrum signal, represents the theoretical reflectivity, They represent the thickness, refractive index and extinction coefficient of the optical film respectively. λ i represents the wavelength of the interference spectrum signal, Indicates the actual reflectivity.

[0012] In some optional embodiments, the optical film is a SiO2 transparent film or a Si3N4 transparent film.

[0013] In some optional embodiments, the method of using a hybrid optimization algorithm formed by a simulated annealing algorithm and a genetic algorithm to search for the film thickness of the optical film includes: A hybrid optimization algorithm formed by a simulated annealing algorithm and a genetic algorithm is used to search for the film thickness of the optical film within a preset parameter search range.

[0014] The optical film thickness measurement and calculation method provided by the present invention has at least the following beneficial effects: Since when the interference spectroscopy method is used to measure the thickness of an optical film, its multi-beam interference formula describes the functional relationship between the film thickness of the optical film and its reflectivity, the film thickness of the optical film can be inverted and inferred by the reflectivity of the optical film. Therefore, in the present invention, after obtaining the interference spectrum signal of the optical film to be measured by the interference spectroscopy method, the actual reflectivity of the optical film is first measured, and then a hybrid optimization algorithm is used to search for the film thickness that can accurately describe the spectral characteristics in the interference spectrum signal, and the optimization goal of the algorithm is to minimize the deviation between the theoretical reflectivity of the optical film corresponding to the searched film thickness and its actual reflectivity, thereby realizing the thickness measurement of the optical film.

[0015] Moreover, the hybrid optimization algorithm is formed by a simulated annealing algorithm and a genetic algorithm. When searching for film thickness, the genetic algorithm is first used for global search to obtain an initial individual close to the global optimum, and based on the initial individual, the simulated annealing algorithm is used for local search to obtain a target individual closer to the global optimum. The present invention can not only use the global search capability of the genetic algorithm to quickly locate the possible optimal solution area, but also use the local search capability of the simulated annealing algorithm to perform a detailed search in these areas, so as to find a more accurate optimal solution. This combination strategy not only improves the accuracy of the final solution, but also enhances the robustness and stability of the algorithm. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] One or more embodiments are exemplarily described by the pictures in the corresponding drawings, and these exemplary descriptions do not constitute limitations on the embodiments.

[0017] Figure 1 is a flow chart of a method for measuring and calculating the thickness of an optical film provided according to an embodiment of the present invention; Figure 2 is an execution flow chart of an optimization algorithm provided according to an embodiment of the present invention; Figure 3 is a flow chart of an implementation of a hybrid optimization algorithm provided according to an embodiment of the present invention; Figure 4 It is a schematic diagram comparing the reflectivity curve fitting results of three algorithms provided according to an embodiment of the present invention. DETAILED DESCRIPTION

[0018] In order to make the purpose, technical scheme and advantages of the embodiments of the present invention clearer, the embodiments of the present invention will be described in detail below in conjunction with the accompanying drawings. However, it will be appreciated by those skilled in the art that in the embodiments of the present invention, many technical details are proposed in order to enable the reader to better understand the present invention. However, even without these technical details and various changes and modifications based on the following embodiments, the technical scheme claimed in the present invention can be implemented. The division of the following embodiments is for the convenience of description and should not constitute any limitation on the specific implementation of the present invention. The various embodiments can be combined and referenced with each other without contradiction.

[0019] An embodiment of the present invention relates to a method for measuring and solving the thickness of an optical film. The implementation details of the method for measuring and solving the thickness of an optical film of this embodiment are specifically described below. The following content is only the implementation details provided for the convenience of understanding and is not necessary for implementing this solution.

[0020] The specific process of the optical film thickness measurement and calculation method of this embodiment can be as follows: Figure 1 As shown, including: Step 101: Obtain interference spectrum signals of the optical film by interference spectroscopy.

[0021] Step 102: Acquire the actual reflectivity of the optical film.

[0022] Step 103, based on the relationship between the reflectivity and the film thickness of the optical film indicated by the interference spectroscopy method, a hybrid optimization algorithm formed by a simulated annealing algorithm and a genetic algorithm is used to search for the film thickness of the optical film, so as to minimize the deviation between the theoretical reflectivity and the actual reflectivity of the optical film corresponding to the searched film thickness; wherein, when the hybrid optimization algorithm is used to search for the film thickness, a genetic algorithm is used to perform a global search to obtain an initial individual close to the global optimum, and based on the initial individual, a simulated annealing algorithm is used to perform a local search to obtain a target individual closer to the global optimum.

[0023] In a specific implementation, there is a first functional relationship between the reflectivity of the optical film and the film thickness of the optical film, the refractive index of the optical film, the extinction coefficient of the optical film, the refractive index of the substrate, the extinction coefficient of the substrate, the refractive index of the air, and the wavelength of the interference spectrum signal. Therefore, when a hybrid optimization algorithm formed by a simulated annealing algorithm and a genetic algorithm is used to search for the film thickness of the spectral characteristics of the interference spectrum signal of the optical film, the hybrid optimization algorithm can be used to search for the film thickness of the optical film, the refractive index of the optical film, and the extinction coefficient of the optical film through the refractive index of the substrate, the extinction coefficient of the substrate, the refractive index of the air, the wavelength of the interference spectrum signal, and the first functional relationship.

[0024] Specifically, interference spectroscopy is an important method for measuring film thickness. Its interference spectrum signal contains key film parameters such as film thickness and refractive index. Therefore, this embodiment specifically uses a suitable thickness measurement algorithm to solve film parameters such as film thickness and refractive index from the spectrum signal. The spectrum fitting optimization algorithm is a method that simulates and matches actual spectrum data by building a mathematical model. Its core is to find parameters that can accurately describe the spectral characteristics, thereby solving the film thickness and optical parameters. Based on this, the thickness measurement of optical films is achieved through an optimization algorithm in this embodiment.

[0025] Among them, the multi-beam interference formula of interference spectroscopy is as follows: ; In the formula, , , , , , .

[0026] In the formula, represents the reflectivity of the optical film, Indicates the thickness of the optical film (i.e. film thickness), represents the refractive index of the optical film, represents the extinction coefficient of the optical film, represents the refractive index of the substrate, represents the extinction coefficient of the substrate, is the refractive index of air, Represents the wavelength of the interference spectrum signal.

[0027] It can be seen that the reflectivity It is a function of the thickness of the optical film, the refractive index and extinction coefficient of the optical film, the refractive index and extinction coefficient of the substrate, the refractive index of air, and the wavelength of the interference spectrum signal, that is, .because , , and is known, the reflectivity at this time is only The function of .

[0028] Therefore, the corresponding reflectivity can be calculated when the film parameters (i.e. the thickness, refractive index and extinction coefficient of the optical film) are known. However, the reflectivity is an easy-to-detect value, and the film parameters are the values ​​that need to be solved, so an inverse calculation is required. First, the search range of the film parameters can be set based on the theoretical parameters obtained through experience: , , , and then use the optimization algorithm to find a set of optimal film parameters, that is, use a hybrid optimization algorithm formed by simulated annealing algorithm and genetic algorithm to search for the film thickness of the optical film within the preset parameter search range. When the deviation between its corresponding theoretical reflectivity and the actually detected reflectivity (that is, the actual reflectivity) reaches the minimum, it is considered that the fitting effect is the best, and the film parameters set at this time are identified as the actual parameters of this film.

[0029] In the specific implementation, we first need to set a condition to determine when the deviation between the theoretically calculated reflectivity and the actual measured reflectivity reaches the minimum value, that is, the condition to determine whether the curve fitting is completed. Therefore, we need to construct a judgment standard, that is, an evaluation function (that is, the minimum optimization objective function). By constructing the evaluation function, the calculation of the film parameters is transformed into a problem of minimizing the evaluation function. Compare the reflectivity obtained by actual measurement with the reflectivity calculated theoretically, and take the minimum mean square error function (MSE in English) as the target optimization function. The evaluation function is defined as follows: ; In the formula, represents the number of sampling points of the interference spectrum signal, represents the theoretical reflectivity, They represent the thickness, refractive index and extinction coefficient of the optical film respectively. represents the wavelength of the interference spectrum signal, Indicates the actual reflectivity.

[0030] The smaller the MSE value of the evaluation function, the better the fitting effect and the more accurate the algorithm calculation. When the calculated theoretical reflectivity curve matches the actual measured reflectivity curve to the greatest extent, the evaluation function MSE reaches the global minimum. At this time, the film parameters corresponding to the theoretical reflectivity can be regarded as the real parameters of the film.

[0031] In one example, there is a second functional relationship between the refractive index of the optical film, the extinction coefficient of the optical film, and the wavelength of the interference spectrum signal, and the second functional relationship is described by a Cauchy dispersion model. At this time, before using a hybrid optimization algorithm formed by a simulated annealing algorithm and a genetic algorithm to search for the film thickness used to describe the spectral characteristics of the interference spectrum signal, first, according to the Cauchy dispersion model, the search for the refractive index of the optical film and the search for the extinction coefficient of the optical film are converted into the search for the first preset constant and the search for the second preset constant, respectively. Then, by using the hybrid optimization algorithm, the search for the first preset constant and the second preset constant are searched to obtain the refractive index of the optical film and the extinction coefficient of the optical film, and then the film thickness of the optical film is obtained.

[0032] Specifically, in order to more accurately describe the film parameters and reduce the number of unknown variables in the fitting process, the dispersion model of the material is introduced during the calculation. There is a functional relationship between the refractive index and extinction coefficient of the optical film and the wavelength, and this relationship is described by the dispersion model of the dielectric material. Commonly used dispersion models include: Cauchy model, Forouhi-Bloomer model, Smelleier model, Tauc-Lorentz model, Drude model, etc. These models are applicable to different ranges of materials. When applying, it is necessary to select a suitable dispersion model according to the actual material category.

[0033] This embodiment adopts the Cauchy model, which is applicable to most thin film materials with low absorption rate, and the formula is: ; ; In the formula, The third functional relationship between the refractive index of the optical film and the wavelength of the interference spectrum signal is represented by: The fourth functional relationship between the extinction coefficient of the optical film and the wavelength of the interference spectrum signal is represented by: λ represents the wavelength of the interference spectrum signal, Both represent preset constants that are independent of the wavelength of the interference spectrum signal.

[0034] The refractive index that varies with wavelength is converted into and extinction coefficient Convert to constant It should be noted that when the optical film is a dielectric transparent material such as SiO2 film or Si3N4 film, its The value can be ignored, only the impact.

[0035] Based on the above, this embodiment first establishes a theoretical reflectivity model , the reflectivity at this time is only a function of the film parameters. Then, in order to more accurately describe the optical properties of the film, the dispersion model is introduced to convert the variables that change with wavelength into the solution of constants. The reflectivity model at this time is .

[0036] At this time, an optimization algorithm is used to find a set of optimal film parameters. The process of the optimization algorithm is as follows: Figure 2 As shown, the algorithm iteratively searches the parameter space to minimize the difference between the theoretical reflectivity and the actual detected reflectivity. The evaluation function is used to quantify this difference. When the evaluation function reaches the minimum value, the fitting effect is considered to be the best. At this time, the constant set It is determined to be the actual parameter of this film.

[0037] The optimization algorithm in this embodiment specifically adopts a hybrid optimization algorithm formed by a simulated annealing algorithm and a genetic algorithm. Among them, the simulated annealing algorithm (SA) simulates the physical annealing process, adopts a serial optimization structure, and accepts poor solutions with a certain probability during the search process, thereby jumping out of the local optimal solution trap, and has a strong local search capability. The genetic algorithm (GA) simulates the genetic mechanism in the biological evolution process, adopts a group parallel search structure, searches for the optimal solution in a global scope, and has a strong global search capability. This embodiment combines the two for improvement to make full use of the local search capability of the SA algorithm serial optimization and the global search capability of the GA algorithm group parallel.

[0038] The hybrid optimization algorithm can be mainly divided into two processes. The first process is to use the GA algorithm to perform genetic operations on the randomly generated population, including selection, crossover and mutation, and select several potential optimal individuals from a large number of solutions through a global search in parallel. Then, the best performing individuals are selected from the population optimized by the GA algorithm as the high-quality initial solution of the SA algorithm. In the second process, the SA algorithm will take over the high-quality initial solution generated by the GA algorithm and perform further local search optimization based on it. In this process, the algorithm can perform a detailed search in the local range to find a solution that is closer to the global optimal solution.

[0039] By combining the GA algorithm and the SA algorithm, the hybrid optimization algorithm can not only use the global search capability of the GA algorithm to quickly locate the possible optimal solution area, but also use the local search capability of the SA algorithm to perform a detailed search in these areas, thereby finding a more accurate optimal solution. This combination strategy not only improves the accuracy of spectral fitting, but also enhances the robustness and stability of the algorithm.

[0040] The implementation flow chart of the hybrid optimization algorithm is as follows: Figure 3 As shown, the key steps and parameter settings are as follows: (1) Initialization: Set the population size to 200 and the maximum number of evolution generations , crossover probability , mutation probability , initial temperature , termination temperature , temperature attenuation coefficient , the number of perturbations at each temperature . Randomly generate 200 sets of parameters to be found within the given search range. The initial population is then encoded in binary.

[0041] (2) Genetic evolution: The population is genetically evolved based on the fitness of the individuals until the maximum number of evolutionary generations is reached, and then the five individuals with the best performance are selected from the finally generated population as the high-quality initial solutions for simulated annealing.

[0042] (3) Simulated annealing: At this time, the concept of group is introduced into the SA algorithm, and simulated annealing optimization is performed simultaneously on the group consisting of 5 groups of initial solutions.

[0043] (4) End algorithm: If the temperature decays to the minimum temperature, or the evaluation function value of the optimal solution , then the algorithm ends and outputs the individual with the minimum evaluation function value .

[0044] In order to verify the thickness measurement method of the optical film of this embodiment, the following experimental verifications were carried out on the SA algorithm, the GA algorithm and the hybrid optimization algorithm: a SiO2 film coated on the surface of a silicon wafer with a reference thickness of 113.73 nm and a refractive index of 1.4648 (corresponding to a wavelength of 589 nm) was selected as a sample, and the SA algorithm, the GA algorithm and the hybrid optimization algorithm were used to perform spectral fitting optimization processing on the reflection spectrum signal collected from the central area of ​​the sample to solve its thickness and refractive index. The average value of 10 repeated measurements was taken to ensure the accuracy of the measurement results, and the performance of each algorithm program was comprehensively evaluated.

[0045] The reflectivity curve fitting results of the three algorithms are shown in Figure 4 The detailed measurement results are shown in Table 1, Table 2 and Table 3.

[0046] As can be seen from the figure, the reflectivity curve fitted by the hybrid optimization algorithm is highly consistent with the measured reflectivity curve, showing an excellent fitting effect. This intuitively shows that since the hybrid optimization algorithm combines the SA algorithm and the GA algorithm, it can more accurately simulate and reflect the actual measurement situation, thereby improving the accuracy and reliability of the fitting.

[0047] Table 1

[0048] Table 2

[0049] Table 3

[0050] From Table 1, Table 2 and Table 3, it can be seen that the results of 10 repeated measurements of the SiO2 film with a reference thickness of 113.73 nm and a refractive index of 1.4648 (wavelength 589 nm) by the SA algorithm, GA algorithm and hybrid optimization algorithm are as follows: The thickness measurement result of the SA algorithm is 120.585 nm, the range is 1.912 nm, and the repeatability (standard deviation) is 0.5982; the refractive index measurement result is 1.4907, the range is 0.0126, and the repeatability (standard deviation) is 0.0038; the evaluation function is The calculation time is about 5s.

[0051] The thickness measurement result of the GA algorithm is 114.909nm, the range is 6.590nm, and the repeatability (standard deviation) is 1.9682; the refractive index measurement result is 1.4790, the range is 0.0382, and the repeatability (standard deviation) is 0.0139; the evaluation function is The calculation time is about 31 seconds.

[0052] The thickness measurement result of the hybrid optimization algorithm is 113.012nm, the range is 3.315nm, and the repeatability (standard deviation) is 1.1068; the refractive index measurement result is 1.4665, the range is 0.0315, and the repeatability (standard deviation) is 0.0116; the evaluation function is The calculation time is about 32 seconds.

[0053] It can be seen that the hybrid optimization algorithm combines the advantages of the SA algorithm and the GA algorithm, balances the measurement accuracy and repeatability, and has higher measurement accuracy without sacrificing excessive stability and measurement time.

[0054] In this embodiment, since the multi-beam interference formula describes the functional relationship between the film thickness of the optical film and its reflectivity when the interference spectroscopy method is used to measure the thickness of the optical film, the film thickness of the optical film can be inverted and inferred by the reflectivity of the optical film. Therefore, after obtaining the interference spectrum signal of the optical film to be measured by the interference spectroscopy method, the actual reflectivity of the optical film is first measured, and then the hybrid optimization algorithm is used to search for the film thickness that can accurately describe the spectral characteristics in the interference spectrum signal, and the optimization goal of the algorithm is to minimize the deviation between the theoretical reflectivity of the optical film corresponding to the searched film thickness and its actual reflectivity, thereby realizing the measurement of the thickness of the optical film. In addition, the hybrid optimization algorithm is formed by a simulated annealing algorithm and a genetic algorithm. When searching for the film thickness, the genetic algorithm is first used to perform a global search to obtain an initial individual close to the global optimum, and based on the initial individual, a simulated annealing algorithm is used to perform a local search to obtain a target individual closer to the global optimum. It can not only use the global search capability of the genetic algorithm to quickly locate the possible optimal solution area, but also use the local search capability of the simulated annealing algorithm to perform a detailed search in these areas, so as to find a more accurate optimal solution. This combined strategy not only improves the accuracy of the final solution, but also enhances the robustness and stability of the algorithm.

[0055] The step division of the various methods above is only for clear description. When implemented, they can be combined into one step or some steps can be split and decomposed into multiple steps. As long as they include the same logical relationship, they are all within the protection scope of the present invention. Adding insignificant modifications or introducing insignificant designs to the algorithm or process without changing the core design of the algorithm and process are all within the protection scope of the invention.

[0056] Those skilled in the art can understand that the above embodiments are specific embodiments of the present invention, and in practical applications, various changes can be made to them in form and detail without departing from the spirit and scope of the embodiments of the present invention. Any person skilled in the art can make various changes and modifications without departing from the spirit and scope of the embodiments of the present invention, so the protection scope of the embodiments of the present invention shall be based on the scope defined in the claims.

Claims

1. A method for measuring the thickness of an optical film, characterized in that: The method comprises: Obtaining interference spectrum signals of optical thin films by interference spectroscopy; Obtain the actual reflectivity of the optical film; Based on the relationship between the reflectivity and film thickness of the optical film revealed by the interference spectroscopy method, a hybrid optimization algorithm formed by a simulated annealing algorithm and a genetic algorithm is used to search for the film thickness of the optical film so as to minimize the deviation between the theoretical reflectivity and the actual reflectivity of the optical film corresponding to the searched film thickness; Among them, when the hybrid optimization algorithm is used to search for film thickness, a genetic algorithm is used to perform a global search to obtain an initial individual close to the global optimum, and based on the initial individual, a simulated annealing algorithm is used to perform a local search to obtain a target individual closer to the global optimum.

2. The method for measuring the thickness of an optical film according to claim 1, characterized in that: There is a first functional relationship between the reflectivity of the optical film and the film thickness of the optical film, the refractive index of the optical film, the extinction coefficient of the optical film, the refractive index of the substrate, the extinction coefficient of the substrate, the refractive index of air, and the wavelength of the interference spectrum signal; The method of using a hybrid optimization algorithm formed by a simulated annealing algorithm and a genetic algorithm to search for the film thickness of the optical film includes: A hybrid optimization algorithm is adopted to search for the film thickness, refractive index and extinction coefficient of the optical film through the refractive index of the substrate, the extinction coefficient of the substrate, the refractive index of the air, the wavelength of the interference spectrum signal and the first functional relationship.

3. The method for measuring the thickness of an optical film according to claim 2, characterized in that: There is a second functional relationship between the refractive index of the optical film, the extinction coefficient of the optical film and the wavelength of the interference spectrum signal, and the second functional relationship is described by a Cauchy dispersion model; Before the hybrid optimization algorithm formed by the simulated annealing algorithm and the genetic algorithm is used to search for the film thickness of the optical film, the method further includes: According to the Cauchy dispersion model, the search for the refractive index of the optical film and the search for the extinction coefficient of the optical film are respectively converted into the search for the first preset constant and the search for the second preset constant.

4. The method for measuring the thickness of an optical film according to claim 3, characterized in that: The Cauchy dispersion model is expressed by the following formula: ； ； In the formula, The third functional relationship between the refractive index of the optical film and the wavelength of the interference spectrum signal is represented by: The fourth functional relationship between the extinction coefficient of the optical film and the wavelength of the interference spectrum signal is represented by: λ represents the wavelength of the interference spectrum signal, Both represent preset constants that are independent of the wavelength of the interference spectrum signal.

5. The method for measuring the thickness of an optical film according to claim 1, characterized in that: The degree of deviation between the theoretical reflectivity and the actual reflectivity of the optical film corresponding to the searched film thickness is specifically the minimum mean square error value between the theoretical reflectivity and the actual reflectivity.

6. The method for measuring the thickness of an optical film according to claim 5, characterized in that: The minimum mean square error between the theoretical reflectivity and the actual reflectivity is expressed by the following formula: ； In the formula, N represents the number of sampling points of the interference spectrum signal, represents the theoretical reflectivity, They represent the thickness, refractive index and extinction coefficient of the optical film respectively. λ i represents the wavelength of the interference spectrum signal, Indicates the actual reflectivity.

7. The method for measuring the thickness of an optical film according to any one of claims 1 to 6, characterized in that: The optical film is a SiO2 transparent film or a Si3N4 transparent film.

8. The method for measuring the thickness of an optical film according to claim 1, characterized in that: The method of using a hybrid optimization algorithm formed by a simulated annealing algorithm and a genetic algorithm to search for the film thickness of the optical film includes: A hybrid optimization algorithm formed by a simulated annealing algorithm and a genetic algorithm is used to search for the film thickness of the optical film within a preset parameter search range.

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