Maximizing test pattern coverage for OPC model build
Andrew Khoh, Shyue-Fong Quek, YeeMei Foong, Jacky Cheng, Byoung-Il Choi · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 2006
OPC model stability is important at low k-1. Unstable OPC model leads to catastrophic OPC failures. For parametric OPC models, one of the major contributions to model instability is inadequate test pattern coverage over the parameter space where actual product designs reside. In this paper, we present a systematic approach to maximizing the coverage of existing test patterns. In this approach, the entire space over which all pattern variants reside is first approximated by varying the pattern dimensions in simple patterns. We call the generated parameter spaces reference domains. Next, regions in the parameter space that are sparsely covered are determined by overlaying parameter data points corresponding to existing test patterns over the reference domains. Systematically analyzing the characteristics of the reference domains, the required test patterns to maximize test pattern coverage can be inferred. Test pattern coverage is hence maximized. In this study, a parametric model with three parameters is considered.