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Proceedings Paper

Source mask optimization using real-coded genetic algorithms
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Paper Abstract

Source mask optimization (SMO) is considered to be one of the technologies to push conventional 193nm lithography to its ultimate limits. In comparison with other SMO methods that use an inverse problem formulation, SMO based on genetic algorithm (GA) requires very little knowledge of the process, and has the advantage of flexible problem formulation. Recent publications on SMO using a GA employ a binary-coded GA. In general, the performance of a GA depends not only on the merit or fitness function, but also on the parameters, operators and their algorithmic implementation. In this paper, we propose a SMO method using real-coded GA where the source and mask solutions are represented by floating point strings instead of bit strings. Besides from that, the selection, crossover, and mutation operators are replaced by corresponding floating-point versions. Both binary-coded and real-coded genetic algorithms were implemented in two versions of SMO and compared in numerical experiments, where the target patterns are staggered contact holes and a logic pattern with critical dimensions of 100 nm, respectively. The results demonstrate the performance improvement of the real-coded GA in comparison to the binary-coded version. Specifically, these improvements can be seen in a better convergence behavior. For example, the numerical experiments for the logic pattern showed that the average number of generations to converge to a proper fitness of 6.0 using the real-coded method is 61.8% (100 generations) less than that using binary-coded method.

Paper Details

Date Published: 12 April 2013
PDF: 14 pages
Proc. SPIE 8683, Optical Microlithography XXVI, 86831T (12 April 2013); doi: 10.1117/12.2010137
Show Author Affiliations
Chaoxing Yang, Shanghai Institute of Optics and Fine Mechanics (China)
Graduate School of the Chinese Academy of Sciences
Xiangzhao Wang, Shanghai Institute of Optics and Fine Mechanics (China)
Graduate School of the Chinese Academy of Sciences (China)
Sikun Li, Shanghai Institute of Optics and Fine Mechanics (China)
Graduate School of the Chinese Academy of Sciences
Andreas Erdmann, Fraunhofer-Institut für Integrierte Systeme und Bauelementetechnologie (Germany)


Published in SPIE Proceedings Vol. 8683:
Optical Microlithography XXVI
Will Conley, Editor(s)

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