Machine learning (ML)-guided OPC using basis functions of polar Fourier transform
作者： Suhyeong Choi , Seongbo Shim , Youngsoo Shin
DOI: 10.1117/12.2219073
关键词:
摘要: With shrinking feature size, runtime has become a limitation of model-based OPC (MB-OPC). A few machine learning-guided OPC (ML-OPC) have been studied as candidates for next-generation OPC, but they all employ too many parameters (eg local densities), which set their own limitations. We propose to use basis functions of polar Fourier transform (PFT) as parameters of ML-OPC. Since PFT functions are orthogonal each other and well reflect light phenomena, the number of parameters can significantly be reduced without loss of …
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