Fast aerial image simulations for partially coherent systems by transmission cross coefficient decomposition with analytical kernels

Fast aerial image simulations for partially coherent systems by transmission cross coefficient decomposition with analytical kernels
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通过使用分析内核的传输交叉系数分解对部分相干系统进行快速航空图像模拟

DOI:
10.1116/1.4767442
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发表时间:
2012-11
影响因子:
1.4
通讯作者:
Xinjiang Zhou
Xinjiang Zhou
中科院分区:
工程技术4区
文献类型:
--
作者:
Peng Gong;Shiyuan Liu;Wen Lv;Xinjiang Zhou

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航空图像模拟是基于模型的光学邻近校正(OPC)中最关键的组成部分之一,它已成为用于提高亚波长光学光刻性能的分辨率增强技术的必要组成部分。本文通过将传输交叉系数(TCC)分解为解析核,提出了一种针对部分相干系统的快速航空图像仿真方法。 TCC 矩阵被投影到以解析圆采样函数 (CSF) 为基础的函数空间上,并转换为更小的投影矩阵。通过对投影矩阵执行奇异值分解 (SVD),其特征向量与 CSF 一起用于生成一组分析 TCC 核。该方法避免了直接对大型 TCC 矩阵执行 SVD,使其比传统的 SVD 方法运行时效率更高。此外,在航拍图像模拟中,核的网格大小可以灵活设置为任何所需值,这是传统SVD方法无法实现的。将所提方法与传统SVD方法计算的航拍图像强度误差和边缘位置误差进行比较,证实了所提方法的有效性。还提供了一个 OPC 示例来进一步证明其效率。
Aerial image simulation is one of the most critical components in the model-based optical proximity correction (OPC), which has become a necessary part of resolution enhancement techniques used to improve the performance of subwavelength optical lithography. In this paper, a fast aerial image simulation method is proposed for partially coherent systems by decomposing the transmission cross coefficient (TCC) into analytical kernels. The TCC matrix is projected onto a function space whose basis is analytical circle-sampling functions (CSFs) and converted into a much smaller projected matrix. By performing singular value decomposition (SVD) to the projected matrix, its eigenvectors together with the CSFs are used to generate a set of analytical TCC kernels. The proposed method avoids directly performing SVD to the large TCC matrix, making it much more runtime efficient than the conventional SVD method. Furthermore, the grid size of the kernels can be flexibly set to any desired value in aerial image simulations, which is not realizable with the conventional SVD method. The comparison of aerial image intensity errors and edge placement errors calculated by the proposed method and the conventional SVD method has confirmed the validity of the proposed method. An OPC example is also provided to further demonstrate its efficiency.
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