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Robust pixel-based source and mask optimization for inverse lithography

机译:针对反光刻的基于像素的稳健源和掩模优化

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摘要

A robust pixel-based simultaneous source and mask optimization (SMO) method is proposed. A three dimensional (3D) partially coherent imaging model is used in this method. The process variations, such as defocus, exposure dose, aberrations, radiometric correction and apodization are incorporated in the 3D imaging model and the optimization framework. The pattern error is calculated with respect to the 3D image in the photoresist. The expectation of the pattern error is used as the cost function. The sensitivity of the cost function is employed to guide cost function in the decedent direction during optimization. The framework is finally solved by joint optimization of the source and mask patterns. Numerical results verify the validity of the proposed method. Influences caused by the aberrations are also shown by simulations.
机译:提出了一种鲁棒的基于像素的同时源和掩码优化(SMO)方法。此方法使用三维(3D)部分相干成像模型。诸如散焦,曝光剂量,像差,放射线校正和切趾的过程变化都包含在3D成像模型和优化框架中。针对光刻胶中的3D图像计算图案误差。模式误差的期望值用作成本函数。成本函数的敏感性用于在优化过程中沿后继方向引导成本函数。最终通过联合优化源和掩模图案来解决该框架。数值结果验证了该方法的有效性。模拟还显示了由像差引起的影响。

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