Genetic algorithms to improve mask and illumination geometries in lithographic imaging systems

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Abstract

This paper proposes the use of a genetic algorithm to optimize mask and illumination geometries in optical projection lithography. A fitness function is introduced that evaluates the imaging quality of arbitrary line patterns in a specified focus range. As a second criterion the manufacturability and inspectability of the mask are taken into account. With this approach optimum imaging conditions can be identified without any additional a-priori knowledge of the lithographic process. Several examples demonstrate the successful application and further potentials of the proposed concept. © Springer-Verlag 2004.

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Fühner, T., Erdmann, A., Farkas, R., Tollkühn, B., & Kókai, G. (2004). Genetic algorithms to improve mask and illumination geometries in lithographic imaging systems. Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 3005, 208–218. https://doi.org/10.1007/978-3-540-24653-4_22

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