使用基于物理的特征映射和专门设计的DCNN快速准确的机器学习逆光刻

2020 International Workshop on Advanced Patterning Solutions (IWAPS) Pub Date : 2020-11-05 DOI:10.1109/IWAPS51164.2020.9286814

X. Shi, Yan Yan, Tao Zhou, Xueru Yu, Chen Li, Shoumian Chen, Yuhang Zhao

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引用次数: 7

摘要

为了实现全芯片逆光刻技术(ILT)解决方案，我们在本研究中提出了一种混合方法，将前几个基于物理的特征映射作为模型输入与专门设计的DCNN结构相结合，以学习严格的ILT算法。我们的研究结果表明，这种方法可以使机器学习ILT变得简单、快速和更准确。

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Fast and Accurate Machine Learning Inverse Lithography Using Physics Based Feature Maps and Specially Designed DCNN

To achieve full chip inverse lithography technology (ILT) solution, we proposed a hybrid approach in this study by combining first few physics based feature maps as model input with a specially designed DCNN structure to learn the rigorous ILT algorithm. Our results show that this approach can make machine learning ILT easy, fast and more accurate.

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来源期刊

2020 International Workshop on Advanced Patterning Solutions (IWAPS)

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