阅读说明：本技术 全视场低像差敏感度一体化光刻方法及光刻系统 (Full-field low-aberration sensitivity integrated photoetching method and photoetching system ) 是由 李艳秋 李铁 刘阳 孙义钰 于 2019-08-28 设计创作，主要内容包括：本发明的一种一体化光刻方法,在实施分辨率增强的过程中考虑了光的偏振特性,能够精确描述超大NA情形下光的传播、聚焦和成像过程,有效降低了随机像差对光刻成像的影响,提高了光刻工艺的稳定性；本发明计算当前状态下各视场点对应的光刻成像图形误差；根据当前光刻成像图形误差自适应地确定下一次迭代各视场点的权重；构造全视场目标函数,该方法能够充分平衡全视场光刻成像质量,提高光刻工艺稳定性；构造了光刻成像和矢量光瞳的解析关系,使用共轭梯度法有效求解最优的矢量光瞳分布使得光刻成像图形误差最小,该方法极大地提升了光瞳优化的自由度,能够有效补偿厚掩模复杂衍射带来的偏振效应和光刻系统的偏振像差。(According to the integrated photoetching method, the polarization characteristic of light is considered in the process of implementing resolution enhancement, the transmission, focusing and imaging processes of light under the condition of super-large NA can be accurately described, the influence of random aberration on photoetching imaging is effectively reduced, and the stability of a photoetching process is improved; calculating photoetching imaging graphic errors corresponding to each view field point in the current state; adaptively determining the weight of each field-of-view point of the next iteration according to the current photoetching imaging pattern error; the full-field objective function is constructed, the method can fully balance the full-field photoetching imaging quality, and the photoetching process stability is improved; the analytical relation between the photoetching imaging and the vector pupil is constructed, the optimal vector pupil distribution is effectively solved by using a conjugate gradient method, so that the photoetching imaging pattern error is minimum, the degree of freedom of pupil optimization is greatly improved, and the polarization effect caused by the complicated diffraction of a thick mask and the polarization aberration of a photoetching system can be effectively compensated.)

1. A full-field low-aberration sensitivity integrated photoetching method is characterized by comprising the following steps:

step 1, determining a strict vector imaging model for forming a simulation space image graph;

step 2, based on the photoetching imaging model, iteratively updating a light source intensity distribution graph and a mask transmittance distribution graph by using a Newton method, wherein the specific process comprises the following steps:

21. selecting a plurality of representative field-of-view points in an exposure field of a lithography objective, wherein the number is expressed by M; considering lithography objectivesPolarization aberration PA of the m-th field of view point_mCalculating the photoetching space imaging I of the mth field-of-view point according to the imaging model in the step 1 by using the current light source intensity distribution graph and the mask transmittance distribution graph_m；m＝1,2,...M；

22. Constructing a graphic error expression of the mth view point:

wherein the content of the first and second substances,

23. obtaining a light source intensity distribution graph J according to the current h-th iteration^(h)And mask transmittance distribution pattern M^(h)Obtaining the photoetching space imaging of each representative field-of-view point according to the imaging model in the step 1, and then calculating the photoetching imaging figure error of the representative field-of-view pointCalculating and determining the weight factor of each field of view point of the h-th iteration

Wherein h represents the iteration times, and the initial value is 0; the first iteration where h is 0,

24. calculating an objective function D^(h)For the current light source intensity distribution pattern J^(h)And mask transmittance distribution pattern M^(h)Gradient matrix ofAnd

25. updating the light source intensity distribution pattern according to the calculation result of the step 24

26. Updating the iteration times h to h + 1;

27. and (3) judging: if h does not reach the set iteration times and the pattern error does not reach the lower limit, returning to the step 21; if h reaches the set iteration times or the pattern error reaches the lower limit, terminating the optimization, and outputting the current light source intensity distribution pattern and the mask transmittance distribution pattern as optimization results;

and step 3, pupil optimization:

31. calculating a strict three-dimensional mask near-field diffraction spectrum G corresponding to the current light source intensity distribution pattern and the mask transmittance distribution pattern_3DConsidering the pupil distribution function pupil, the analytical function for calculating the spatial image pattern I is:

wherein, J (x)_s,y_s) The coordinate of the intensity distribution pattern of the front light source is (x)_s,y_s) The intensity at the pixel point of the light source,

32. calculating the current photoetching imaging I 'of each field of view point according to formula (2)'_mAnd then calculating the point pattern error of each view field in the k iteration

calculating and determining the weight factor of each field of view point of the current k-th iteration

33. Calculating and storing pupil distribution function pupil of the kth iteration^(k)Gradient of (2)

Wherein, pupil^k＝pupil^(k-1)+step_pupil×direction^(k-1)(ii) a step _ pupil is a preset pupil optimization step; direction^(k-1)Represents the optimization direction of the last iteration, the initial optimization direction when the first iteration, i.e. k is 1⁽⁰⁾Arranged in the gradient direction

34. updating a pupil distribution function pupil^(k+1)＝pupil^(k)+step_pupil×direction^(k)；

35. Calculating an objective function F^(k)Pupil distribution function pupil for the k +1 th iteration^(k+1)Gradient of (2)

36. Calculating and storing the optimization direction of the (k + 1) th iteration:

37. updating the iteration times k to k + 1;

38. and (3) judging: if the iteration number k reaches the upper limit or the figure error reaches the lower limit, the optimization is terminated, and the current pupil distribution function is output as an optimization result; and if the iteration times k do not reach the upper limit and the pattern error does not reach the lower limit, returning to the step 31 and continuing the iteration.

2. The method as claimed in claim 1, wherein in step 21, a strict three-dimensional mask near-field diffraction spectrum G corresponding to the current light source intensity distribution pattern and the mask transmittance distribution pattern is calculated by using finite-difference time domain or strict coupled wave electromagnetic field finite element algorithm_3D。

3. A lithography system for implementing the integrated lithography method according to claim 1 or 2, wherein the computational lithography subsystem in the integrated lithography system implements the integrated lithography method.

Technical Field

The invention belongs to the technical field of resolution enhancement of integrated circuit design, manufacturing equipment, processes, microscopic imaging, telescopic imaging and the like, and particularly relates to a full-field low-aberration sensitivity integrated photoetching method and a photoetching system, and more particularly relates to a light source optimization method and a mask optimization method for effectively reducing the sensitivity of photoetching imaging to random aberration and a vector pupil optimization method for effectively balancing the full-field photoetching imaging quality.

Background

Optical lithography is a key technology in the field of very large scale integrated circuit manufacturing. The working wavelength of the current mainstream photoetching system in the industry is 193 nanometers, and as the photoetching process enters into the technical nodes of 7 nanometers and below, the minimum line width on an integrated circuit layout is far smaller than the working wavelength, so that a photoetching resolution enhancement technology with high resolution and high fidelity is urgently needed. The integrated lithography technology can integrate all subsystems of a lithography machine, including a hardware system including an illumination projection system and an imaging system, a software system for realizing computational lithography, a detection system for detecting imaging errors and the like, and is the lithography resolution enhancement technology with the most potential for realizing the next generation of nodes.

In order to ensure the productivity of the lithography system, a lithography projection objective with a large field of view is usually adopted for exposure imaging. According to the aberration theory of applied optics, the aberration of an optical system depends on the position of a field of view, and the large exposure field of view can cause the aberration of each area on the mask surface to be uneven, thereby causing the imaging of each exposure area on the image surface to be uneven. The existing lithography technology (Journal of micro/Nanolithography, MEMS, and MOEMS, 2012, 11:043008) only optimizes imaging of a single field point, cannot ensure consistency of imaging quality of a full field, and is not beneficial to improvement of yield of the lithography process.

At a low technology node, the photoetching imaging is very sensitive to random errors of a photoetching system, and the photoetching system always has various random errors such as full-field wave aberration and polarization aberration, similar aberration caused by a thick mask 3D effect, approximate error of a photoetching imaging model, calculation error and algorithm error in calculation photoetching, detection error in processing and assembly of an optical system, detection error of a mask structure and material refractive index, edge blurring of an illumination light source, random vibration in the horizontal direction and the vertical direction of a workpiece table, photoresist process error and the like. The existence of the errors seriously influences the stability of the photoetching process, and the existing literature is rarely researched on the low-error-sensitivity integrated photoetching method and the photoetching system. From optical imaging theory, the effect of various errors on lithographic imaging can be attributed to the effects on the intensity, phase, and polarization of the pupil plane, i.e., the effects on optical system aberrations. Therefore, the reduction of the sensitivity of the photoetching imaging to the random aberration is equivalent to the reduction of the influence of various random errors on the photoetching imaging, and the stability of the photoetching process is improved. Furthermore, since the technology nodes of integrated circuits have reached 14 to 7 nanometers, which is much smaller than the light source wavelength 193 nanometers, the polarization effects of three-dimensional mask complex diffraction are not negligible. However, the prior art (applied optics,2014,53: 6861-.

Disclosure of Invention

The invention discloses a full-field low-aberration sensitivity integrated photoetching method and a photoetching system, which can realize high-stability and high-fidelity parameter correction of all subsystems of a photoetching machine and overcome the problems.

A full-field low-aberration sensitivity integrated photoetching method comprises the following steps:

step 1, determining a strict vector imaging model for forming a simulation space image graph;

step 2, based on the photoetching imaging model, iteratively updating a light source intensity distribution graph and a mask transmittance distribution graph by using a Newton method, wherein the specific process comprises the following steps:

21. selecting a plurality of representative field-of-view points in an exposure field of a lithography objective, wherein the number is expressed by M; considering the polarization aberration PA of the mth field point in the lithography objective_mCalculating the photoetching space imaging I of the mth field-of-view point according to the imaging model in the step 1 by using the current light source intensity distribution graph and the mask transmittance distribution graph_m； m＝1,2,...M；

22. Constructing a graphic error expression of the mth view point:

wherein the content of the first and second substances,

denotes the two norm, Z_mThe photoresist image representing the m-th field of view point is represented by aerial image I_mThe threshold value is taken to obtain the threshold value,

representing a target graphic;

23. obtaining a light source intensity distribution graph J according to the current h-th iteration^(h)And mask transmittance distribution pattern M^(h)Obtaining the photoetching space imaging of each representative field-of-view point according to the imaging model in the step 1, and then calculating the photoetching imaging figure error of the representative field-of-view point

Calculating and determining the weight factor of each field of view point of the h-th iteration

Constructing a full-field objective function of the iteration

Wherein h represents the iteration times, and the initial value is 0; the first iteration where h is 0,

D⁽⁰⁾＝∑_mω_mPAE_m；

24. calculating an objective function D^(h)For the current light source intensity distribution pattern J^(h)And mask transmittance distribution pattern M^(h)Gradient matrix of (a), (b)

And

) And sea plug matrix (

And

)；

25. updating the light source intensity distribution pattern according to the calculation result of the step 24

Updating mask transmittance distribution patterns

Step _ source and step _ mask are respectively a preset light source optimization step length and a preset mask optimization step length; initial light source intensity distribution pattern J⁽⁰⁾Set as ring illumination, initial mask transmittance distribution pattern M⁽⁰⁾Set as a target graphic

26. Updating the iteration times h to h + 1;

27. and (3) judging: if h does not reach the set iteration times and the pattern error does not reach the lower limit, returning to the step 21; if h reaches the set iteration times or the pattern error reaches the lower limit, terminating the optimization, and outputting the current light source intensity distribution pattern and the mask transmittance distribution pattern as optimization results;

and step 3, pupil optimization:

31. calculating a strict three-dimensional mask near-field diffraction spectrum G corresponding to the current light source intensity distribution pattern and the mask transmittance distribution pattern_3DConsidering the pupil distribution function pupil, the analytical function for calculating the spatial image pattern I is:

wherein, J (x)_s,y_s) The coordinate of the intensity distribution pattern of the front light source is (x)_s,y_s) The intensity at the pixel point of the light source,

representing the inverse fourier transform, C is the irradiance correction constant;

is a coordinate rotation matrix; PA is the polarization aberration of the lithography system; e_iRepresenting the polarization state of incident light;

32. calculating the current photoetching imaging I 'of each field of view point according to formula (2)'_mAnd then calculating the point pattern error of each view field in the k iteration

Z′_mThe photoresist image representing the m-th field point is composed of an aerial image I'_mObtaining a threshold value; k represents the iteration number, and the initial value is 0;

calculating and determining the weight factor of each field of view point of the current k-th iterationConstructing a full-field objective function of the iteration

33. Calculating and storing pupil distribution function pupil of the kth iteration^(k)Gradient of (2)

Wherein, pupil^k＝pupil^(k-1)+step_pupil×direction^(k-1)(ii) a step _ pupil is a preset pupil optimization step; direction^(k-1)Represents the optimization direction of the last iteration, the initial optimization direction when the first iteration, i.e. k is 1⁽⁰⁾Arranged in the gradient direction

Initial pupil distribution function pupil⁽⁰⁾Setting the unit matrix;

34. updating a pupil distribution function pupil^(k+1)＝pupil^(k)+step_pupil×direction^(k)；

35. Calculating an objective function F^(k)Pupil distribution function pupil for the k +1 th iteration^(k+1)Gradient of (2)

36. Calculating and storing the optimization direction of the (k + 1) th iteration:

37. updating the iteration times k to k + 1;

38. and (3) judging: if the iteration number k reaches the upper limit or the figure error reaches the lower limit, the optimization is terminated, and the current pupil distribution function is output as an optimization result; and if the iteration times k do not reach the upper limit and the pattern error does not reach the lower limit, returning to the step 31 and continuing the iteration.

Preferably, in the step 21, a strict three-dimensional mask near-field diffraction spectrum G corresponding to the current light source intensity distribution pattern and the mask transmittance distribution pattern is calculated by using a finite-difference time domain or a strict coupled-wave electromagnetic field finite element algorithm_3D。

An integrated photoetching system, a computing photoetching subsystem realizes the integrated photoetching method.

The invention has the following beneficial effects:

(1) the invention relates to an integrated photoetching method, which is characterized in that in a calculation photoetching server of an integrated photoetching system, resolution enhancement of full-field low-aberration sensitivity is carried out on the basis of a vector imaging model, and relevant parameters of the integrated photoetching system corresponding to a resolution enhancement technology are obtained; using all relevant parameters of the current integrated photoetching system to obtain an imaging graph at the wafer surface in the integrated photoetching system; detecting imaging errors and errors of the integrated lithography system by using a plurality of detection devices; the calculation lithography server iteratively adjusts each relevant parameter of the integrated lithography system by using the error information, so that the optimization degree of freedom can be greatly increased, and the improvement of the fidelity and the resolution of the lithography system is facilitated.

(2) According to the method, the polarization characteristic of light is considered in the process of implementing resolution enhancement, the transmission, focusing and imaging processes of light under the condition of super-large NA can be accurately described, the influence of random aberration on photoetching imaging is effectively reduced, and the stability of a photoetching process is improved;

(3) the invention discloses a self-adaptive full-field photoetching resolution enhancement technology, which is characterized in that a full-field objective function is constructed in a self-adaptive manner, and the main steps are as follows: calculating the photoetching imaging pattern error corresponding to each view field point under the current (k-th iteration) state

Adaptively determining the weight of each field of view point of the next iteration (the (k + 1) th iteration) according to the current photoetching imaging pattern errorConstructing a full field of view objective function

The method can fully balance the full-field photoetching imaging quality and improve the photoetching process stability.

(4) In the vector pupil optimization process, the analytical relation between the photoetching imaging and the vector pupil is constructed, and the optimal vector pupil distribution is effectively solved by using a conjugate gradient method so that the photoetching imaging graphic error is minimum; the method greatly improves the degree of freedom of pupil optimization, and can effectively compensate the polarization effect caused by complicated diffraction of a thick mask and the polarization aberration of a photoetching system.

Drawings

FIG. 1 is a schematic diagram of one embodiment of an integrated lithography system.

FIG. 2 is a flow diagram of integrated photolithography method steps according to one embodiment of the present invention.

FIG. 3 is a schematic diagram of an initial light source, an initial mask and its corresponding imaging in photoresist.

FIG. 4 is a schematic diagram of a light source pattern, a mask pattern, a pupil distribution and an image formed in a corresponding photoresist after being optimized by using the technical scheme in the prior art (Applied Optics,2014,53: 6861-.

FIG. 5 is a schematic view of a light source pattern, a mask pattern, a pupil distribution and corresponding imaging in photoresist optimized by the method of FIG. 2.

FIG. 6 is a comparison graph of full-field graphic error distributions corresponding to the prior art (Applied Optics,2014,53: 6861-.

Detailed Description

The present invention will be further described in detail with reference to the accompanying drawings. The drawings are given as illustrative examples of the invention so as to enable those skilled in the art to practice the invention, and it should be noted that the drawings and examples below are not meant to limit the scope of the invention to a single embodiment.

FIG. 1 schematically depicts an integrated lithography system, the main components comprising: 101 is an illumination optical system, 101(a) is a light source laser, 101(b) is a polarization regulation wave plate group, 101(c) is a micro mirror array, and 101(d) is a light source intensity distribution graph; 102 is a mask; 103 is a projection imaging system, comprising two lens groups 103 (a) and 103(c) and a pupil regulating device 103 (b); 104 is an exposure system comprising photoresist and the like; 105 is an image of the mask pattern formed on the wafer plane; 106 is a variety of detection devices including, but not limited to, a wave aberration detection device, a polarization aberration detection device, a defocus detection device, a critical dimension uniformity detection device, a pattern shift detection device, etc.; 108 is the detected imaging error and the integrated lithography system error; 109 is a computational lithography server, which stores integrated computational lithography software; 109(a) - (e) respectively adjust parameters such as polarization control slide group, micro-mirror array, mask transmittance distribution, projection objective pupil distribution, and various process parameters in exposure development in the integrated photoetching system for integrated computing photoetching software.

As shown in fig. 2, the light source-mask-pupil optimization method specifically includes the following steps:

step 1, determining a strict vector imaging model for forming a simulated space image pattern, wherein the imaging model represents a photoetching imaging process:

according to the technical content disclosed in patent CN102692814B, if the current light source intensity distribution pattern J and the mask transmittance distribution pattern M are known, under the thin mask assumption (the thin mask assumption means that the complex diffraction effect of the three-dimensional mask is ignored, and the mask diffraction near-field distribution is assumed to be equal to the mask transmittance distribution), the analytical function of the simulated aerial image pattern I is calculated as:

wherein J is a size N_s×N_sM is a matrix of size N × N; j (x)_s,y_s) Is a coordinate of (x)_s,y_s) The intensity at the pixel point of the light source,

and | | l represents the modulus of each element in the matrix, and the final calculation result I is a matrix with the size of N multiplied by N and represents the current spatial image intensity distribution.

Is light source point J (x)_s,y_s) The corresponding mask diffraction matrix, which has a size of N, is defined as each point (m, N) on the mask to the light source point J (x) according to Hopkins approximation_s,y_s) The optical path length of (a):

where j is an imaginary unit, λ represents the light source wavelength, NA represents the object-side numerical aperture of the projection system, and pixel represents the side length of each sub-region on the mask pattern.

Representing convolution, ⊙ representing direct multiplication of elements corresponding to two matrixes, wherein p is x, y, and z represents three polarization directions of x, y and z;

is an equivalent point spread function with the size of N multiplied by N;

representing the inverse Fourier transform, n_wThe refractive index of the immersion liquid on the image side of the lithography system is shown, and R is the reduction magnification of an ideal projection system and is generally 4; v'_pComprising vector matrices (if an element in a matrix is a vector or a matrix, it is called a vector matrix)

P-component composition of each element in (a); p here represents the polarization direction of light, and represents the vector characteristic of the imaging model. The specific calculation process of V' is described in detail in patent CN102692814B, and is not described herein again.

The above aerial image intensities are ideally calculated from a vector imaging model. Now consider the aberration actually existing in the lithography system, taking polarization aberration PA as an example, V' should be corrected to

It should be noted here that V' has a different form of correction if other aberrations or other errors are present in the lithography system.

Step 2, based on the photoetching imaging model, iteratively updating a light source intensity distribution graph and a mask transmittance distribution graph by using a Newton method, wherein the specific process comprises the following steps:

21. selecting a plurality of representative field-of-view points in an exposure field of a lithography objective, wherein the number is expressed by M; considering the polarization aberration PA of the mth field point in the lithography objective_mUsing the current light source intensity distribution pattern and maskCalculating photoetching space imaging I of the mth field of view point according to the formula (1) by using the transmittance distribution graph_m；

22. Constructing a graphic error expression of the mth view point:

wherein the content of the first and second substances,

denotes the two norm, Z_mThe photoresist image representing the m-th field point can be represented by an aerial image I_mThe threshold value is taken to obtain the threshold value,

representing a target graphic;

23. obtaining a light source intensity distribution graph J according to the current h-th iteration^(h)And mask transmittance distribution pattern M^(h)Obtaining the photoetching space imaging of each representative field-of-view point according to the formula (1), and then calculating the photoetching imaging figure error of the representative field-of-view point

Calculating and determining the weight factor of each field of view point of the current iteration (h-th iteration)

Constructing a full-field objective function of the iteration

Wherein h represents the iteration times, and the initial value is 0; on the first iteration, i.e. when h is 0,

D⁽⁰⁾＝∑_mω_mPAE_m；

24. calculating an objective function D^(h)For the current light source intensity distribution pattern J^(h)And mask penetrationRate distribution pattern M^(h)Gradient matrix of (a), (b)And

) And sea plug matrix (

And)；

25. updating the light source intensity distribution pattern according to the calculation result of the step 24Updating mask transmittance distribution patterns

Step _ source and step _ mask are respectively a preset light source optimization step length and a preset mask optimization step length; initial light source intensity distribution pattern J⁽⁰⁾Set as ring illumination, initial mask transmittance distribution pattern M⁽⁰⁾Set as a target graphic

26. Updating the iteration times h to h + 1;

27. and (3) judging: if h does not reach the set iteration times and the pattern error does not reach the lower limit, returning to the step 21; and if h reaches the set iteration times or the pattern error reaches the lower limit, terminating the optimization, and outputting the current light source intensity distribution pattern and the mask transmittance distribution pattern as optimization results.

And step 3, pupil optimization:

31. calculating a strict three-dimensional mask near-field diffraction spectrum corresponding to the current light source intensity distribution graph J and the mask transmittance distribution graph M by using an electromagnetic field finite element algorithm such as a time domain finite difference or a strict coupled waveG_3DConsidering the pupil distribution function pupil, the analytical function for calculating the spatial image pattern I is:

wherein, J (x)_s,y_s) The coordinate of the front light intensity distribution pattern J is (x)_s,y_s) The intensity at the pixel point of the light source,

representing the inverse fourier transform, C is the irradiance correction constant;is a coordinate rotation matrix, wherein each element is a 3 x 2 matrix, which has the function of converting a two-dimensional vector in a local coordinate system into a three-dimensional vector in a global coordinate system,

the specific analytic formula and derivation process of (a) can be seen from the technical content disclosed in patent CN102692814B, and are not described herein again; PA is the polarization aberration of the lithography system; e_iRepresenting the polarization state of incident light;

32. calculating the current photoetching imaging I 'of each field of view point according to formula (2)'_mAnd then calculating the point pattern error of each view field in the k iteration

Z′_mThe photoresist image representing the m-th field point can be represented by an aerial image I'_mObtaining a threshold value; k represents the iteration number, and the initial value is 0;

calculating and determining the weight factor of each field of view point of the current iteration (the k-th iteration)Constructing a full-field objective function of the iteration

33. Calculating and storing pupil distribution function pupil of the kth iteration^(k)Gradient of (2)

Wherein, pupil^k＝pupil^(k-1)+step_pupil×direction^(k-1)(ii) a step _ pupil is a preset pupil optimization step; direction^(k-1)Represents the optimization direction of the last iteration, the initial optimization direction when the first iteration, i.e. k is 1⁽⁰⁾Arranged in the gradient direction

Initial pupil distribution function pupil⁽⁰⁾Setting the unit matrix;

34. updating a pupil distribution function pupil^(k+1)＝pupil^(k)+step_pupil×direction^(k)；

35. Calculating an objective function F^(k)Pupil distribution function pupil for the k +1 th iteration^(k+1)Gradient of (2)

36. Calculating and storing the optimization direction of the (k + 1) th iteration:

37. updating the iteration times k to k + 1;

38. and (3) judging: if the iteration number k reaches the upper limit or the figure error reaches the lower limit, the optimization is terminated, and the current pupil distribution function is output as an optimization result; and if the iteration times k do not reach the upper limit and the pattern error does not reach the lower limit, returning to the step 31 and continuing the iteration.

Example of implementation of the invention:

in this embodiment, the magnitude of the lithographic imaging fidelity is evaluated by the figure error, the smaller the figure error, the greater the lithographic imaging fidelity, and vice versa. The pattern error (PAE) is defined as:

where Z (x, y) is the value of the target pattern Z at the coordinates (x, y) and Z (x, y) is the value of the actual resist image Z at the coordinates (x, y).

FIG. 3 is a schematic diagram of the initial light source pattern, the initial mask pattern and its corresponding imaging in the photoresist. In fig. 3, 301 is an initial light source pattern, white represents a light emitting portion, and black represents a non-light emitting portion. 302 is the initial mask pattern and also the target pattern, white represents the light-transmitting area and black represents the light-blocking area, with a feature size of 22 nm. 303 is the initial pupil distribution function, which has a phase distribution of 0 at each point in the numerical aperture range. Reference numeral 304 denotes an image formed in the resist of the lithography system by using 301 as a light source, 302 as a mask, and 303 as a pupil, and the pattern error thereof is 1802.

FIG. 4 shows a prior art (Applied Optics,2014,53:6861-

Method A) optimized light source pattern, mask pattern, pupil distribution and their corresponding imaged in photoresist. In fig. 4, 401 is an optimized light source pattern; 402 is an optimized mask pattern; 403 is the optimized pupil phase distribution; in 404, after the image is formed in the photoresist of the lithography system by using 401 as a light source, 402 as a mask, and 403 as a pupil, the pattern error is 1315.

Fig. 5 is a schematic diagram showing a light source pattern, a mask pattern, a pupil distribution and an image formed in a photoresist corresponding to the light source pattern, the mask pattern, the pupil distribution, which are optimized by using the full-field integrated lithography method (hereinafter referred to as method B) provided by the present invention. In fig. 5, 501 is an optimized light source pattern; 502 is the optimized mask pattern; 503 is the optimized pupil distribution; the pattern error is 840 for an image formed in the photoresist of the lithography system after using 501 as a light source, 502 as a mask, 503 as a pupil 504. It is noted that the pupil distribution function in 503 is a 2 × 2 Jones matrix, since the method B proposed by the present invention can optimize the vector pupil. Due to the reasons, the integrated photoetching method provided by the invention improves the optimization degree of freedom, can effectively compensate the polarization error in the photoetching system, and finally improves the pattern fidelity of photoetching imaging.

Fig. 6 is a comparison graph of the full-field graphic error distributions corresponding to the method a and the method B. The abscissa is the sequence number of the field of view points, and the ordinate is the graphic error of each field of view point. Quantitatively, the average value of the full-field graphic error distribution corresponding to the method A is 1622, and the standard deviation is 230; the mean value of the full-field graphic error distribution corresponding to method B is 867 and the standard deviation is 30. A smaller mean value means a higher lithographic imaging quality and a smaller standard deviation means a more uniform lithographic imaging distribution. Therefore, the method B provided by the invention not only integrally reduces the graphic error of each field point, but also improves the uniformity and consistency of the photoetching imaging of each field point

Although the embodiments of the present invention have been described with reference to the accompanying drawings, it will be understood by those skilled in the art that various changes, substitutions and alterations can be made herein without departing from the principles of the invention, and these should be considered as falling within the scope of the invention.