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Fast Convolution Method and Its Application in Mask Optimization for Intensity Calculation Using Basis Expansion

机译:快速卷积方法及其在基于基数展开的面罩优化强度计算中的应用

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摘要

Finer grid representation is required for a more accurate description of mask patterns in inverse lithography techniques, thus resulting in a large-size mask representation and heavy computational cost. To mitigate the computation problem caused by intensive convolutions in mask optimization, a new method called convolution using basis expansion (CBE) is discussed in this paper. Matrices defined in fine grid are projected on coarse gird under a base matrix set. The new matrices formed by the expansion coefficients are used to perform convolution on the coarse grid. The convolution on fine grid can be approximated by the sum of a few convolutions on coarse grid following an interpolation procedure. The CBE is verified by random matrix convolutions and intensity calculation in lithography simulation. Results show that the use of the CBE method results in similar image quality with significant running speed enhancement compared with traditional convolution method.
机译:为了更精确地描述反光刻技术中的掩模图案,需要更精细的网格表示,从而导致大尺寸的掩模表示和沉重的计算成本。为了缓解掩模优化中密集卷积引起的计算问题,本文讨论了一种新的方法,即使用基础扩展卷积(CBE)。细网格中定义的矩阵将投影在基本矩阵集下的粗网格上。由扩展系数形成的新矩阵用于对粗网格进行卷积。细网格上的卷积可以通过遵循插值过程的粗网格上的一些卷积之和来近似。通过随机矩阵卷积和光刻仿真中的强度计算来验证CBE。结果表明,与传统的卷积方法相比,使用CBE方法可获得相似的图像质量,并且运行速度显着提高。

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