Methods, devices, media, program products and terminals for determining the similarity of curve mask layouts.

Abstract

This application provides a method, apparatus, medium, program product, and terminal for similarity determination of curve mask layouts. It acquires a reference curve layout and a curve layout to be tested, calculates their respective minimum bounding rectangles, and performs a preliminary determination. If the relative difference between the long and short sides of the rectangles is less than a set first threshold, the two are considered similar graphics and proceed to depth similarity determination; otherwise, they are determined to be dissimilar. In the depth determination, relevant resolution parameters are generated based on the shortest side width, an optical intensity distribution map is generated using optical simulation, and the difference between the light intensity distribution maps is calculated. If the difference is less than a second threshold, they are ultimately determined to be similar. This application achieves accurate determination of layout similarity from a geometric to an optical characteristic level. It solves the problem of insufficient accuracy in existing similarity determination of complex curve layouts, significantly improves the accuracy and reliability of similarity determination, and effectively enhances the efficiency and accuracy of optical analysis and design.

Description

Technical Field

[0001] This application relates to the semiconductor field, and in particular to a method, apparatus, medium, program product, and terminal for determining the similarity of curve mask layouts. Background Technology

[0002] Mask pattern similarity assessment refers to the process of quantitatively evaluating the degree of similarity between different mask patterns in semiconductor manufacturing. This assessment is crucial for mask layout design optimization, process control, and yield improvement. In semiconductor manufacturing, the importance of mask pattern similarity assessment is mainly reflected in the following aspects: helping to identify pattern features that may lead to manufacturing defects; optimizing layout design and improving manufacturing yield; and assessing the impact of process changes on product performance.

[0003] In existing technologies, mask pattern similarity determination methods are mainly based on comparison of pure geometric parameters. This method performs well when dealing with traditional Manhattan structures (i.e., rectangular patterns composed of orthogonal line segments), and the determination process is relatively simple and direct. Specific determination parameters typically include geometric features such as the side length, area, size, boundary contour, and corner positions of the pattern.

[0004] However, existing judgment methods have the following shortcomings: oversensitivity: for curved patterns, even the slightest geometric difference may be judged as a different pattern, resulting in overly strict judgments; insufficient process relevance: judgments based purely on geometric parameters fail to fully consider the characteristics of semiconductor manufacturing processes and are insufficient to reflect the impact of pattern differences on the actual manufacturing process; and a single judgment standard: existing methods rely excessively on geometric parameters and lack a comprehensive assessment of process sensitivity. These problems are particularly prominent in modern semiconductor manufacturing, especially as process nodes advance, mask pattern design becomes increasingly complex, and the use of curved patterns becomes more and more common. Summary of the Invention

[0005] In view of the shortcomings of the prior art described above, the purpose of this application is to provide a method, apparatus, medium, program product and terminal for determining the similarity of curved mask layouts, in order to solve the problem that the mask pattern similarity determination method in the prior art relies too much on pure geometric parameters, resulting in excessive sensitivity to minor differences in curved patterns and failing to effectively reflect the actual needs of semiconductor manufacturing processes.

[0006] To achieve the above and other related objectives, a first aspect of this application provides a method for determining the similarity of curve mask layouts, comprising: acquiring a reference curve layout and a curve layout to be tested; generating the minimum bounding rectangle of the reference curve layout as a first rectangle; generating the minimum bounding rectangle of the curve layout to be tested as a second rectangle; performing a preliminary similarity determination operation on the reference curve layout and the curve layout to be tested based on the first rectangle and the second rectangle; and if the determination result is similar graphics, performing a depth similarity determination operation on the reference curve layout and the curve layout to be tested based on simulated light intensity to generate a similarity determination result.

[0007] In some embodiments of the first aspect of this application, the process of performing a similarity depth determination operation on the reference curve layout and the curve layout to be tested based on simulated light intensity includes: performing a light intensity distribution generation operation on the first rectangle to generate a first light intensity distribution map of the reference curve layout; performing a light intensity distribution generation operation on the second rectangle to generate a second light intensity distribution map of the curve layout to be tested; calculating the light intensity difference between the first light intensity distribution map and the second light intensity distribution map; if the light intensity difference is less than a second threshold, then determining that the reference curve layout and the curve layout to be tested are similar graphics; otherwise, determining that they are dissimilar graphics.

[0008] In some embodiments of the first aspect of this application, the process of performing the light intensity distribution generation operation on a target rectangle to generate a corresponding light intensity distribution map includes the following steps: generating a corresponding resolution parameter based on the short side line width of the target rectangle; sampling sequentially from the top to the bottom of the target rectangle according to a preset sampling interval; the sampling process includes: performing an optical simulation operation on each sampling position based on the resolution parameter to generate a corresponding light intensity parameter value; establishing a two-dimensional coordinate system with the sampling sequence number as the abscissa and the light intensity parameter value as the ordinate to generate a light intensity distribution map.

[0009] In some embodiments of the first aspect of this application, the resolution parameters include any one or more of the following: light source wavelength, objective lens numerical aperture, lithography process factor, and coherence coefficient.

[0010] In some embodiments of the first aspect of this application, the light intensity difference includes any one or more of the following: maximum value difference, minimum value difference, and slope of the light intensity curve.

[0011] In some embodiments of the first aspect of this application, the process of performing a preliminary similarity determination operation on the reference curve layout and the curve layout to be tested includes: if the relative difference between the long side and the short side of the first rectangle and the second rectangle is less than a first threshold, then the first rectangle and the second rectangle are determined to be similar graphics; otherwise, they are determined to be dissimilar graphics.

[0012] To achieve the above and other related objectives, a second aspect of this application provides a similarity determination device for curve mask layouts, comprising: a data acquisition module for acquiring a reference curve layout and a curve layout to be tested; a preliminary judgment module for generating the minimum bounding rectangle of the reference curve layout as a first rectangle; generating the minimum bounding rectangle of the curve layout to be tested as a second rectangle; and performing a preliminary similarity determination operation on the reference curve layout and the curve layout to be tested based on the first rectangle and the second rectangle; and a depth judgment module for performing a similarity depth judgment operation on the reference curve layout and the curve layout to be tested based on simulated light intensity if the judgment result is similar graphics, so as to generate a similarity determination result.

[0013] To achieve the above and other related objectives, a third aspect of this application provides a computer-readable storage medium having a computer program stored thereon, wherein the computer program, when executed by a processor, implements a method for determining the similarity of the curve mask layout.

[0014] To achieve the above and other related objectives, a fourth aspect of this application provides a computer program product, which includes computer program code that, when executed on a computer, enables the computer to implement the similarity determination method for the curve mask layout.

[0015] To achieve the above and other related objectives, a fifth aspect of this application provides an electronic terminal, including a memory, a processor, and a computer program stored in the memory; the processor executes the computer program to implement the similarity determination method for the curve mask layout.

[0016] As described above, the similarity determination method, apparatus, medium, program product, and terminal for curve mask layouts in this application have the following beneficial effects: By initially judging the relative differences of the rectangular sides, similar and dissimilar graphics are quickly filtered out, reducing computational load and improving efficiency. Subsequently, in-depth analysis using the light intensity distribution map can accurately capture and compare key parameters of optical characteristics, thereby significantly improving the accuracy and reliability of similarity determination. In addition, the optical resolution matching strategy adapted to the shortest side width ensures the clarity of the light intensity distribution map and avoids misjudgments and deviations in traditional methods. It is not only applicable to photolithography process optimization and optical design verification, but also significantly improves the efficiency and accuracy of optical analysis and design. Attached Figure Description

[0017] Figure 1 This is a schematic flowchart illustrating an embodiment of the curve mask layout similarity determination method of this application.

[0018] Figure 2The image shows a target mask layout in one embodiment of the similarity determination method for curve mask layouts of this application.

[0019] Figure 3 The image shows the target rectangle of the target submerged map in one embodiment of the similarity determination method for the curve mask map of this application.

[0020] Figure 4 This diagram illustrates the optical simulation operation path in one embodiment of the similarity determination method for curve mask layouts of this application.

[0021] Figure 5 The image shows a light intensity distribution diagram in one embodiment of the similarity determination method for the curve mask layout of this application.

[0022] Figure 6 This diagram shows a structural schematic of an embodiment of the similarity determination device for curve mask layouts of this application.

[0023] Figure 7 This diagram shows a structural schematic of an embodiment of a similarity determination terminal for curve mask layouts according to this application. Detailed Implementation

[0024] The following specific examples illustrate the implementation of this application. Those skilled in the art can easily understand other advantages and effects of this application from the content disclosed in this specification. This application can also be implemented or applied through other different specific embodiments, and various details in this specification can also be modified or changed based on different viewpoints and applications without departing from the spirit of this application. It should be noted that, unless otherwise specified, the following embodiments and features in the embodiments can be combined with each other.

[0025] Before providing a further detailed description of this application, the nouns and terms used in the embodiments of this application are explained, and the nouns and terms used in the embodiments of this application shall be interpreted as follows:

[0026] <1> Mask pattern similarity determination: Mask pattern similarity determination involves comparing two mask patterns under specific criteria to assess their similarity.

[0027] <2> Light intensity distribution map: A light intensity distribution map is a visualization of the light intensity distribution emitted by a light source in two-dimensional or three-dimensional space, used to depict the light intensity variations in a specific region. This graphic provides important information for the performance analysis of the light source and its optical system, including evaluating illumination uniformity and diffraction characteristics.

[0028] <3> Linewidth: Linewidth refers to the width of the pattern being created. Precise control of linewidth directly affects circuit characteristics and performance; linewidths that are too wide or too narrow can lead to circuit malfunction or instability.

[0029] <4> Rayleigh criterion: The Rayleigh criterion is used to determine whether two adjacent point light sources can be clearly distinguished. A critically resolvable state is defined as when the intensities of the main lobe and the second lobe in the diffraction patterns of these two sources are equal. This definition has wide applications in optical and microscopic imaging.

[0030] <5> Wavelength of a light source: The wavelength of light emitted by a light source refers to the wavelength of the light wave emitted by the light source, expressed in nanometers (nm). Different wavelengths not only affect the color of light, but also determine the transmission characteristics, interference effects, and diffraction behavior of light in an optical system.

[0031] <6> Objective lens numerical aperture (NA): The numerical aperture (NA) of an objective lens is a key optical parameter that determines how much light the lens can collect during imaging. A larger numerical aperture means a higher light-collecting efficiency, thereby improving image sharpness and resolution.

[0032] <7> Photolithography process factors: These include the wavelength of the light source, the chemical properties of the photoresist, and the conditions of the development process. These factors interact to jointly determine the resolution and quality of the final pattern during the photolithography process.

[0033] <8> Coherence coefficient: The coherence coefficient is a metric used to quantify the coherence between two light waves or images, and is usually calculated in the form of complex amplitude. Coherence plays a crucial role in interference and diffraction phenomena, affecting the intensity and propagation mode of light.

[0034] To facilitate understanding of the embodiments of this application, firstly, in conjunction with Figure 1 Detailed explanation. Figure 1 This document illustrates a flowchart of a curve mask layout similarity determination method according to an embodiment of this application. The curve mask layout similarity determination method in this embodiment mainly includes the following steps:

[0035] Step S11: Obtain the baseline curve layout and the curve layout to be tested.

[0036] In one embodiment of this application, a baseline curve mask serves as a known reference design graphic, providing a comparison standard for similarity comparison. The curve mask to be tested is the object graphic to be inspected. By comparing the curve mask to be tested with the baseline curve mask, the similarity between the two can be determined. The necessity of comparing the two lies in the fact that the baseline curve mask represents an ideal design standard, which, after verification, can effectively reflect the basic performance of a specific technical field. By comparing with the baseline mask, the degree of deviation of the curve mask to be tested can be quantified, thereby providing a clear basis for judging its conformity.

[0037] It should be noted that the purpose of similarity comparison is mainly reflected in the following aspects: First, in the quality control process, similarity comparison helps identify products that do not meet design standards, ensuring the pass rate in the production process; second, in the design verification stage, comparing the new design with the baseline mask can assess the rationality of the design and provide a reference for further design optimization; third, in fault diagnosis, by checking the similarity between the test curve mask and the baseline mask, potential faults and anomalies can be identified, facilitating timely adjustments and optimizations; finally, in consistency assessment, similarity comparison can ensure that products from different batches or locations are consistent in design. Therefore, the process of comparing the baseline mask with the test curve mask helps support product quality assessment, design optimization, and fault detection, thereby enhancing the accuracy of industrial production and R&D.

[0038] Step S12: Generate the minimum bounding rectangle of the reference curve layout as the first rectangle; generate the minimum bounding rectangle of the curve layout to be tested as the second rectangle; based on the first rectangle and the second rectangle, perform a preliminary similarity determination operation on the reference curve layout and the curve layout to be tested.

[0039] In one embodiment of this application, the minimum bounding rectangle (i.e., the first rectangle) of the reference curve layout is generated based on the boundary of the reference curve to ensure that it can enclose all parts of the entire reference curve. At the same time, the minimum bounding rectangle (i.e., the second rectangle) of the curve to be tested layout is also generated based on the data of the curve to be tested to ensure that the second rectangle can completely enclose all parts of the curve to be tested.

[0040] In one embodiment of this application, the process of performing a preliminary similarity determination operation on the reference curve layout and the curve layout to be tested includes: if the relative difference between the long side and the short side of the first rectangle and the second rectangle is less than a first threshold, then the first rectangle and the second rectangle are determined to be similar graphics; otherwise, they are determined to be dissimilar graphics.

[0041] In this embodiment, the process of generating the minimum bounding rectangle (i.e., the first rectangle) of the reference curve layout includes: obtaining the leftmost, rightmost, topmost, and bottommost boundary points on the reference curve layout; from these boundary points, the width of the rectangle in the x-direction can be obtained. ) and width in the y direction ( Similarly, the minimum bounding rectangle (i.e., the second rectangle) of the curve layout to be tested is also determined by the same method to obtain its boundary points and its width in the x-direction. ) and width in the y direction ( These key parameters of the rectangle will be used for subsequent similarity determination.

[0042] Furthermore, after generating these two rectangles, the process of calculating their relative difference includes: calculating the widths of the reference rectangle in the x and y directions respectively, subtracting the corresponding widths of the rectangle to be measured from these widths, and dividing the resulting difference by the width of the reference rectangle. and If both of the above ratios are less than the set threshold (e.g., 1%, which can be adjusted according to actual needs), then the two rectangles are considered to be sufficiently similar in size, and the next step of in-depth judgment can be performed; otherwise, they are directly judged as dissimilar graphics.

[0043] Step S13: If the determination result is similar graphics, then perform a similarity depth determination operation on the reference curve layout and the curve layout to be tested based on the simulated light intensity to generate a similarity determination result.

[0044] In one embodiment of this application, the process of performing a similarity depth determination operation on the reference curve layout and the curve layout to be tested based on simulated light intensity includes: performing a light intensity distribution generation operation on the first rectangle to generate a first light intensity distribution map of the reference curve layout; performing a light intensity distribution generation operation on the second rectangle to generate a second light intensity distribution map of the curve layout to be tested; calculating the light intensity difference between the first light intensity distribution map and the second light intensity distribution map; if the light intensity difference is less than a second threshold, then the reference curve layout and the curve layout to be tested are determined to be similar graphics; otherwise, they are determined to be dissimilar graphics.

[0045] In this embodiment, the process of determining depth pattern similarity by analyzing the differences in light intensity distribution includes the following steps: generating light intensity distribution for a selected rectangular area in the reference curve pattern to obtain two-dimensional distribution data related to the optical characteristics of the area; then, performing light intensity distribution simulation again for the corresponding rectangular area of ​​the curve pattern to be tested.

[0046] It should be noted that the optical parameters used in the simulated exposure operations of the reference curve pattern and the curve pattern to be tested can be the same or different, but it is essential to ensure that their relative sharpness is consistent. This relative sharpness is defined by the size of the shorter side of the rectangle and the Rayleigh criterion. Specifically, selecting an appropriate wavelength is crucial to ensuring that the light resolution of the two patterns matches under the same optical conditions, thereby making the generated intensity distribution maps comparable.

[0047] Specifically, the resolving power of the imaging system is determined based on the Rayleigh criterion by calculating the dimensions of the shorter side of the rectangle and its corresponding diffraction limit. According to the Rayleigh criterion, when two point light sources are at a certain distance, the minimum distance at which their images on the focal plane can be resolved depends on the wavelength of the light and the numerical aperture of the optical system. Therefore, during simulated exposure, by appropriately setting optical parameters such as wavelength, the consistency of the relative sharpness of the two images is ensured, laying the foundation for effective comparison of the intensity distribution maps. Finally, by analyzing the maximum and minimum values ​​and the slope of the intensity curves of the two intensity distribution maps, the similarity between them can be further determined.

[0048] In one embodiment of this application, the process of performing the light intensity distribution generation operation on a target rectangle to generate a corresponding light intensity distribution map includes the following steps: generating a corresponding resolution parameter based on the short side width of the target rectangle; sampling sequentially from the top to the bottom of the target rectangle according to a preset sampling interval; the sampling process includes: performing an optical simulation operation on each sampling position based on the resolution parameter to generate a corresponding light intensity parameter value; establishing a two-dimensional coordinate system with the sampling sequence number as the abscissa and the light intensity parameter value as the ordinate to generate a light intensity distribution map.

[0049] In this embodiment, the target rectangle includes a first rectangle and a second rectangle. The above process includes performing a light intensity distribution generation operation on the first matrix to generate a first light intensity distribution map, and also includes performing a light intensity distribution generation operation on the second matrix to generate a second light intensity distribution map.

[0050] In one embodiment of this application, the light intensity difference includes any one or more of the following: maximum value difference, minimum value difference, and slope of the light intensity curve.

[0051] In this embodiment, the process of sampling sequentially from the top to the bottom of the target rectangle according to a preset sampling interval includes: the line width of the short side of the target rectangle, in micrometers; setting the interval d of the horizontal lines based on the line width of the short side, and selecting a certain proportion of the line width as the interval. For example, for a short side line width of 100nm, a proportion of one-tenth can be set, setting d to 10nm, thereby ensuring sufficient sampling density and accuracy on the lines.

[0052] Furthermore, from the target rectangle top Begin by uniformly dividing the target rectangle along its longitudinal direction with horizontal lines at predetermined intervals d. The resulting lines are denoted sequentially as follows: Each d mark spans the width of the target rectangle, and the vertical spacing between adjacent d marks is equal, denoted by d. The purpose of this process is to provide multiple sampling cross-sections for subsequent optical simulation operations, reflecting the variation of light intensity along the target rectangle.

[0053] Subsequently, based on the preset optical simulation parameters, the top boundary line was... Optical calculations are performed using a fixed optical model (such as ray tracing, wave optics simulation, Fourier diffraction simulation, etc.). The model's input parameters include preset optical parameters such as light source characteristics, wavelength, and numerical aperture, as well as the geometric dimensions and material properties of the target rectangle. Then, calculations are performed along each horizontal line. (i is the line number), calculate the light intensity distribution point by point and record the corresponding light intensity changes. Along each line... This involves analyzing light intensity distribution data and extracting the maximum and minimum points, as well as the slope of the light intensity curve. The maximum point refers to the location of the peak point on the light intensity curve and its corresponding light intensity value. The minimum point refers to the location of the valley point in the light intensity curve and its light intensity value. .

[0054] In one embodiment of this application, the slope of the light intensity curve is the maximum slope value in the light intensity curve from a trough to a peak (or from a peak to a trough). As shown in Formula 1, This represents the interval of the light intensity curve.

[0055] (Formula 1)

[0056] In one embodiment of this application, the slope of the light intensity curve is the average value of the light intensity slope within a preset range of peak measurement. The average value represents the overall gradient of the light intensity curve in the peak region. and The left and right half-height and width points of the peak or other specific locations are shown in Formula 2.

[0057] (Formula 2)

[0058] In one embodiment of this application, the slope of the light intensity curve is the connection point of the maximum value. and minimum point The slope of the line is shown in Formula 3.

[0059] (Formula 3)

[0060] In one embodiment of this application, the process of generating a light intensity distribution map includes: in a two-dimensional coordinate system, with the line number i as the abscissa (X-axis), and key light intensity parameters (such as maximum values) as the coordinates. Minimum value or slope Using the vertical axis (Y-axis), the corresponding curve is plotted. By integrating the light intensity parameters of each horizontal line, a target rectangular light intensity distribution map with a global view is generated, thus intuitively showing the layer-by-layer variation trend of light intensity with depth and its distribution pattern within the target rectangular area.

[0061] The resolution parameters include any one or more of the following: light source wavelength, objective lens numerical aperture, photolithography process factor, and coherence coefficient.

[0062] In this embodiment, the resolution parameter conforms to the Rayleigh criterion. The process of the Rayleigh criterion is shown in Formula 4. According to the Rayleigh criterion, the resolution R of an optical system is the minimum distance that can effectively distinguish two adjacent point light sources, which is affected by the light source wavelength λ, numerical aperture NA, and photolithography process factor. Restrictions.

[0063] (Formula 4)

[0064] Where λ is the wavelength of the light source, representing the wavelength of light used by the optical system, usually measured in nanometers (nm); NA represents numerical aperture, defined as the optical performance parameter of the objective lens, expressed as NA = n*Sin(θ), where n is the refractive index of the medium and θ is the maximum angle of refraction of the objective lens. The larger the numerical aperture, the stronger the resolving power; R represents the photolithography process factor, an empirical parameter indicating the level of process quality. It is related to process precision and equipment and is usually a fixed value, such as 0.5 or 0.75. R represents the resolution, which is the smallest feature size that the optical system can clearly resolve.

[0065] In this embodiment, when using the shorter side cd of the target rectangle with a smaller line width, the required wavelength λ can be derived in reverse according to R = cd and the resolution formula, as shown in Formula 5.

[0066] (Formula 5)

[0067] The numerical aperture NA is determined by the objective lens design parameters, and the process factor... These are the standard settings for lithography equipment and process conditions. The wavelength λ is dynamically adjusted by the target linewidth cd. By controlling λ, the resolution of the optical system can be precisely matched with the target linewidth.

[0068] In one embodiment of this application, the process of performing optical simulation operations for each sampling location based on the resolution parameters includes: generating and analyzing an optical model using electronic design automation (EDA) tools. The EDA tools are accessed via an API interface, and the optical parameters corresponding to the target rectangle are automatically input. In the optical simulation, the linewidth of the boundary rectangle is input into the optical model to ensure the rectangle's resolvability within this scale range. By controlling the sharpness of the short side, the final contrast value of the light intensity distribution (such as the difference between peak and valley values, slope changes, etc.) directly affects subsequent analysis.

[0069] In this embodiment, using the shortest side of the outer rectangle, which is not based on the reference curve pattern and the curve pattern to be tested, as the wavelength parameter for determining the optical simulation operation may lead to the following problems: First, it is impossible to effectively distinguish between two adjacent point light sources, resulting in blurred imaging and a lack of obvious contrast in the light intensity distribution; second, the extreme points (such as maximum and minimum values) in the light intensity distribution map may shift, which will fail to accurately reflect the optical characteristics of the region; finally, without effective control of sharpness, the light intensity curves of different target curves cannot be effectively compared, thus limiting subsequent optical analysis and verification processes. These problems will directly affect the accuracy and reliability of the optical simulation, therefore, accurate selection of the wavelength parameter is crucial.

[0070] Figures 2 to 5 This illustration shows a schematic diagram of performing a depth determination operation on a target layout in one embodiment of this application. Figure 2 A schematic diagram of the target layout in this embodiment is shown; Figure 3 The smallest bounding rectangle for generating the target layout in this embodiment is shown, where the shorter side of the bounding rectangle is a and the longer side is b; Figure 4 The diagram illustrates the division of the minimum bounding rectangle in this embodiment at preset intervals, where optical simulation operations are performed sequentially from top to bottom for each green line to generate, as shown in the diagram. Figure 5 The light intensity distribution diagram shown in the diagram has the horizontal axis representing the number of samples taken in the sampling rectangle and the vertical axis representing the light intensity of the corresponding sampling operation.

[0071] In the embodiments of this application, terms such as "first" and "second" are used to distinguish identical or similar items with essentially the same function and purpose. For example, "first rectangle" and "second rectangle" are used merely to distinguish different rectangles and do not limit their order. Those skilled in the art will understand that terms such as "first" and "second" do not limit the quantity or execution order, and that "first" and "second" do not necessarily imply that they are different.

[0072] It should be noted that, in the embodiments of this application, the words "exemplary" or "for example" indicate examples, illustrations, or descriptions. Any embodiment or design described as "exemplary" or "for example" in this application should not be construed as being more preferred or advantageous than other embodiments or designs. Specifically, the use of words such as "exemplary" or "for example" is intended to present the relevant concepts in a concrete manner.

[0073] In this application embodiment, "at least one" refers to one or more, and "more than one" refers to two or more. "And / or" describes the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A alone, A and B simultaneously, or B alone, where A and B can be singular or plural. The character " / " generally indicates that the preceding and following related objects are in an "or" relationship. "At least one of the following" or similar expressions refer to any combination of these items, including any combination of single or plural items. For example, at least one of a, b, or c can represent: a, b, c, ab, ac, bc, or abc, where a, b, and c can be single or multiple.

[0074] Figure 6 This is a schematic block diagram of a curve mask layout similarity determination device provided in an embodiment of this application. For example... Figure 6 As shown, the device includes a data acquisition module 601, a preliminary judgment module 602, and a depth judgment module 603.

[0075] Data acquisition module 601: used to acquire the baseline curve layout and the curve layout to be tested.

[0076] Preliminary judgment module 602: used to generate the minimum bounding rectangle of the reference curve layout as the first rectangle; generate the minimum bounding rectangle of the curve layout to be tested as the second rectangle; and perform a preliminary similarity judgment operation on the reference curve layout and the curve layout to be tested based on the first rectangle and the second rectangle.

[0077] Depth determination module 603: If the determination result is similar graphics, it performs a similarity depth determination operation on the reference curve layout and the curve layout to be tested based on simulated light intensity to generate a similarity determination result.

[0078] It should be understood that the specific process of each module performing the above-mentioned steps has been described in detail in the above method embodiments, and will not be repeated here for the sake of brevity.

[0079] It should also be understood that the module division in the embodiments of this application is illustrative and only represents a logical functional division; in actual implementation, there may be other division methods. Furthermore, the functional modules in the various embodiments of this application can be integrated into a single processor, exist as separate physical entities, or be integrated into a single module. The integrated modules described above can be implemented in hardware or as software functional modules.

[0080] Figure 7 This is a schematic block diagram of the electronic terminal provided in an embodiment of this application. Figure 7As shown, the electronic terminal includes at least one processor 701, a memory 702, at least one network interface 703, and a user interface 705. The various components in the device are coupled together via a bus system 704. It is understood that the bus system 704 is used to implement communication between these components. In addition to a data bus, the bus system 704 also includes a power bus, a control bus, and a status signal bus. However, for clarity, in... Figure 7 The general will label all buses as bus systems.

[0081] The user interface 705 may include a monitor, keyboard, mouse, trackball, clicker, button, touchpad, or touch screen.

[0082] It is understood that memory 702 can be volatile memory or non-volatile memory, or both. Non-volatile memory can be read-only memory (ROM) or programmable read-only memory (PROM), which serves as an external cache. By way of example, but not limitation, many forms of RAM are available, such as static random access memory (SRAM) and synchronous static random access memory (SSRAM). The memories described in the embodiments of this application are intended to include, but are not limited to, these and any other suitable categories of memory.

[0083] In this embodiment, the memory 702 is used to store various types of data to support the operation of the electronic terminal 700. Examples of this data include any executable program that operates on the electronic terminal 700, such as the operating system 7021 and application programs 7022. The operating system 7021 contains various system programs, such as the framework layer, core library layer, and driver layer, used to implement various basic services and handle hardware-based tasks. The application program 7022 may contain various applications, such as a media player and a browser, used to implement various application services. The similarity determination method for the curve mask layout provided in this embodiment can be included in the application program 7022.

[0084] The methods disclosed in the embodiments of this application can be applied to processor 701, or implemented by processor 701. Processor 701 may be an integrated circuit chip with signal processing capabilities. In the implementation process, each step of the above method can be completed by the integrated logic circuit of the hardware in processor 701 or by instructions in the form of software. The processor 701 may be a general-purpose processor, a digital signal processor (DSP), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. Processor 701 can implement or execute the methods, steps, and logic block diagrams disclosed in the embodiments of this application. General-purpose processor 701 may be a microprocessor or any conventional processor, etc. The steps of the accessory optimization method provided in the embodiments of this application can be directly reflected as being executed by a hardware decoding processor, or being executed by a combination of hardware and software modules in the decoding processor. The software module may be located in a storage medium, which is located in memory. The processor reads the information in the memory and combines it with its hardware to complete the steps of the aforementioned method.

[0085] In an exemplary embodiment, the electronic terminal 700 may be used by one or more application-specific integrated circuits (ASICs), DSPs, programmable logic devices (PLDs), or complex programmable logic devices (CPLDs) to execute the aforementioned method.

[0086] According to the method provided in the embodiments of this application, this application also provides a computer program product, which includes: computer program code, which, when run on a computer, causes the computer to execute the curve mask layout similarity determination method as described in any of the embodiments above.

[0087] According to the method provided in the embodiments of this application, this application also provides a computer-readable storage medium storing program code, which, when run on a computer, causes the computer to execute the curve mask layout similarity determination method as described in any of the embodiments above.

[0088] As used in this specification, the terms "component," "module," "system," etc., are used to refer to computer-related entities, hardware, firmware, combinations of hardware and software, software, or software in execution. For example, a component can be, but is not limited to, a process running on a processor, a processor, an object, an executable file, an execution thread, a program, and / or a computer. As illustrated, applications running on computing devices and computing devices can both be components. One or more components may reside in a process and / or an execution thread, and components may be located on a single computer and / or distributed among two or more computers. Furthermore, these components can be executed from various computer-readable media on which various data structures are stored. Components can communicate, for example, via local and / or remote processes based on signals having one or more data packets (e.g., data from two components interacting with another component between a local system, a distributed system, and / or a network, such as the Internet interacting with other systems via signals).

[0089] Those skilled in the art will recognize that the various illustrative logical blocks and steps described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementations should not be considered beyond the scope of this application.

[0090] Those skilled in the art will understand that, for the sake of convenience and brevity, the specific working processes of the systems, devices, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0091] In the several embodiments provided in this application, it should be understood that the disclosed systems, apparatuses, and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between apparatuses or units may be electrical, mechanical, or other forms.

[0092] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0093] In addition, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit.

[0094] In the above embodiments, the functions of each functional unit can be implemented entirely or partially through software, hardware, firmware, or any combination thereof. When implemented using software, it can be implemented entirely or partially in the form of a computer program product. A computer program product includes one or more computer instructions (programs). When the computer program instructions (programs) are loaded and executed on a computer, all or part of the flow or function according to the embodiments of this application is generated. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. Computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via wired (e.g., coaxial cable, fiber optic, Digital Subscriber Line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) means. The computer-readable storage medium can be any available medium that a computer can access or a data storage device such as a server or data center that integrates one or more available media. The available media can be magnetic media (e.g., floppy disks, hard disks, magnetic tapes), optical media (e.g., high-density digital video discs (DVDs)), or semiconductor media (e.g., solid-state drives (SSDs)).

[0095] If a function is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods of the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0096] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

[0097] In summary, this application provides a method, apparatus, medium, program product, and terminal for similarity determination of curve mask layouts. This application offers a method to improve the efficiency and accuracy of similarity determination for curve mask layouts. It involves acquiring a reference curve layout and a curve layout to be tested, calculating their respective minimum bounding rectangles, and making a preliminary determination. If the relative difference between the long and short sides of the rectangles is less than a set first threshold, the two are considered similar graphics and proceed to depth similarity determination; otherwise, they are determined to be dissimilar. In the depth determination, relevant resolution parameters are generated based on the width of the shortest side, an optical intensity distribution map is generated using optical simulation, and the difference between the light intensity distribution maps is calculated. If the difference is less than a second threshold, they are ultimately determined to be similar. This application achieves accurate determination of layout similarity from a geometric to an optical characteristic level. It solves the problem of insufficient accuracy in existing similarity determination of complex curve layouts, significantly improving the accuracy and reliability of similarity determination, and effectively enhancing the efficiency and accuracy of optical analysis and design. Therefore, this application effectively overcomes the various shortcomings of the prior art and has high industrial applicability.

[0098] The above embodiments are merely illustrative of the principles and effects of this application and are not intended to limit this application. Any person skilled in the art can modify or alter the above embodiments without departing from the spirit and scope of this application. Therefore, all equivalent modifications or alterations made by those skilled in the art without departing from the spirit and technical concept disclosed in this application should still be covered by the claims of this application.

Claims

1. A method for determining the similarity of curve mask layouts, characterized in that, include: Obtain the baseline curve layout and the curve layout to be tested; Generate the minimum bounding rectangle of the reference curve layout, and use it as the first rectangle; Generate the minimum bounding rectangle of the curve layout to be tested, and use it as the second rectangle; Based on the first rectangle and the second rectangle, a preliminary similarity determination operation is performed on the reference curve layout and the curve layout to be tested; The preliminary similarity determination operation includes: if the relative difference between the long side and the short side of the first rectangle and the second rectangle is less than a first threshold, then the first rectangle and the second rectangle are determined to be similar graphics; otherwise, they are determined to be dissimilar graphics. If the determination result is that the two curves are similar, then a similarity depth determination operation is performed on the reference curve layout and the curve layout to be tested based on simulated light intensity to generate a similarity determination result. The similarity depth determination operation includes: performing a light intensity distribution generation operation on the first rectangle to generate a first light intensity distribution map of the reference curve layout; performing a light intensity distribution generation operation on the second rectangle to generate a second light intensity distribution map of the curve layout to be tested; calculating the light intensity difference between the first light intensity distribution map and the second light intensity distribution map; if the light intensity difference is less than a second threshold, then the reference curve layout and the curve layout to be tested are determined to be similar curves; otherwise, they are determined to be dissimilar curves. The process of performing the light intensity distribution generation operation on the target rectangle to generate a corresponding light intensity distribution map includes the following steps: generating a corresponding resolution parameter based on the short side line width of the target rectangle, so that the clarity at the short side line widths of the first rectangle and the second rectangle is consistent; sampling is performed sequentially from the top to the bottom of the target rectangle according to a preset sampling interval; the sampling process includes: performing an optical simulation operation on each sampling position based on the resolution parameter to generate a corresponding light intensity parameter value; establishing a two-dimensional coordinate system with the sampling sequence number as the abscissa and the light intensity parameter value as the ordinate to generate a light intensity distribution map; the light intensity difference includes any one or more of the following: maximum value difference, minimum value difference, and light intensity curve slope.

2. The method for determining the similarity of curve mask layouts according to claim 1, characterized in that, The resolution parameters include any one or more of the following: light source wavelength, objective lens numerical aperture, photolithography process factor, and coherence coefficient.

3. A similarity determination device for a curve mask layout, characterized in that, include: Data acquisition module: used to acquire the baseline curve layout and the curve layout to be tested; Preliminary judgment module: used to generate the minimum bounding rectangle of the reference curve layout as the first rectangle; and to generate the minimum bounding rectangle of the curve layout to be tested as the second rectangle; Based on the first rectangle and the second rectangle, a preliminary similarity determination operation is performed on the reference curve layout and the curve layout to be tested; The preliminary similarity determination operation includes: if the relative difference between the long side and the short side of the first rectangle and the second rectangle is less than a first threshold, then the first rectangle and the second rectangle are determined to be similar graphics; otherwise, they are determined to be dissimilar graphics. Depth Judgment Module: If the judgment result is similar graphics, it performs a similarity depth judgment operation on the reference curve layout and the curve layout to be tested based on simulated light intensity to generate a similarity judgment result. The similarity depth judgment operation includes: performing a light intensity distribution generation operation on the first rectangle to generate a first light intensity distribution map of the reference curve layout; performing a light intensity distribution generation operation on the second rectangle to generate a second light intensity distribution map of the curve layout to be tested; calculating the light intensity difference between the first light intensity distribution map and the second light intensity distribution map; if the light intensity difference is less than a second threshold, the reference curve layout and the curve layout to be tested are determined to be similar graphics; otherwise, they are determined to be dissimilar graphics. The process of performing the light intensity distribution generation operation on the target rectangle to generate a corresponding light intensity distribution map includes the following steps: generating a corresponding resolution parameter based on the short side line width of the target rectangle, so that the clarity at the short side line widths of the first rectangle and the second rectangle is consistent; sampling is performed sequentially from the top to the bottom of the target rectangle according to a preset sampling interval; the sampling process includes: performing an optical simulation operation on each sampling position based on the resolution parameter to generate a corresponding light intensity parameter value; establishing a two-dimensional coordinate system with the sampling sequence number as the abscissa and the light intensity parameter value as the ordinate to generate a light intensity distribution map; the light intensity difference includes any one or more of the following: maximum value difference, minimum value difference, and light intensity curve slope.

4. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the similarity determination method for the curve mask layout as described in any one of claims 1 to 2.

5. A computer program product, characterized in that, The computer program product includes computer program code, which, when run on a computer, enables the computer to implement the similarity determination method for curve mask layouts as described in any one of claims 1 to 2.

6. An electronic terminal, comprising a memory, a processor, and a computer program stored in the memory, characterized in that, The processor executes the computer program to implement the similarity determination method for curve mask layouts according to any one of claims 1 to 2.

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