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9 November 2005 The novel approach for optical proximity correction using genetic algorithms
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This paper proposes a new approach to optical proximity correction (OPC) using an adjustable OPCed cell and genetic algorithms (GA) to achieve optimal OPC feature generation for the full-chip area at fast operational speeds. GA is an efficient optimization technique based on population genetics. In this new approach, an adjustable OPCed cell consists of two parts. The first part is the original design data. The second part consists of two kinds of OPC features. The first kind is referred to as "fixed features", which include OPC feature data from a conventional OPC technique. The second kind, named "adjustable features", are located in the peripheral regions of the cell and include adjustable OPC variables. As the values of these variables are greatly influenced by neighboring cell patterns, the variables are quickly optimized by the GA after chip layout. The effectiveness of this approach, in terms of reduced times for accurate simulations and repeated modification of OPCed features, is demonstrated through computational experiments.
© (2005) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Tetsuaki Matsunawa, Hirokazu Nosato, Hidenori Sakanashi, Masahiro Murakawa, Nobuharu Murata, Tsuneo Terasawa, Toshihiko Tanaka, Nobuyuki Yoshioka, Osamu Suga, and Tetsuya Higuchi "The novel approach for optical proximity correction using genetic algorithms", Proc. SPIE 5992, 25th Annual BACUS Symposium on Photomask Technology, 599254 (9 November 2005);


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