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Proceedings Paper

Pixel-based mask optimization via particle swarm optimization algorithm for inverse lithography
Author(s): Lei Wang; Sikun Li; Xiangzhao Wang; Chaoxing Yang; Feng Tang
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Paper Abstract

An efficient pixel-based mask optimization method via particle swarm optimization (PSO) algorithm for inverse lithography is proposed. Because of the simplicity of principles, the ease of implementation and the efficiency of convergence, PSO has been widely used in many fields. In this study, PSO is used to solve the inverse problem of mask optimization. The pixel-based mask patterns are transformed into frequency space using discrete cosine transformation and the frequency components are encoded into particles. The pattern fidelity is adopted as the fitness function to evaluate these particles. The mask optimization method is implemented by updating the velocities and positions of these particles. Simulation results show that the image fidelity has been efficiently improved after using the proposed method.

Paper Details

Date Published: 15 March 2016
PDF: 9 pages
Proc. SPIE 9780, Optical Microlithography XXIX, 97801V (15 March 2016); doi: 10.1117/12.2230404
Show Author Affiliations
Lei Wang, Shanghai Institute of Optics and Fine Mechanics (China)
Univ. of Chinese Academy of Sciences (China)
Sikun Li, Shanghai Institute of Optics and Fine Mechanics (China)
Univ. of Chinese Academy of Sciences (China)
Xiangzhao Wang, Shanghai Institute of Optics and Fine Mechanics (China)
Univ. of Chinese Academy of Sciences (China)
Chaoxing Yang, Shanghai Institute of Optics and Fine Mechanics (China)
Univ. of Chinese Academy of Sciences (China)
Feng Tang, Shanghai Institute of Optics and Fine Mechanics (China)
Univ. of Chinese Academy of Sciences (China)


Published in SPIE Proceedings Vol. 9780:
Optical Microlithography XXIX
Andreas Erdmann; Jongwook Kye, Editor(s)

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