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Optics Express

Optics Express

  • Editor: Andrew M. Weiner
  • Vol. 22, Iss. 4 — Feb. 24, 2014
  • pp: 3924–3937

Efficient source mask optimization with Zernike polynomial functions for source representation

Xiaofei Wu, Shiyuan Liu, Jia Li, and Edmund Y. Lam  »View Author Affiliations

Optics Express, Vol. 22, Issue 4, pp. 3924-3937 (2014)

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In 22nm optical lithography and beyond, source mask optimization (SMO) becomes vital for the continuation of advanced ArF technology node development. The pixel-based method permits a large solution space, but involves a time-consuming optimization procedure because of the large number of pixel variables. In this paper, we introduce the Zernike polynomials as basis functions to represent the source patterns, and propose an improved SMO algorithm with this representation. The source patterns are decomposed into the weighted superposition of some well-chosen Zernike polynomial functions, and the number of variables decreases significantly. We compare the computation efficiency and optimization performance between the proposed method and the conventional pixel-based algorithm. Simulation results demonstrate that the former can obtain substantial speedup of source optimization while improving the pattern fidelity at the same time.

© 2014 Optical Society of America

OCIS Codes
(110.5220) Imaging systems : Photolithography
(110.1758) Imaging systems : Computational imaging
(110.4235) Imaging systems : Nanolithography

ToC Category:
Physical Optics

Original Manuscript: November 25, 2013
Revised Manuscript: January 28, 2014
Manuscript Accepted: January 30, 2014
Published: February 12, 2014

Xiaofei Wu, Shiyuan Liu, Jia Li, and Edmund Y. Lam, "Efficient source mask optimization with Zernike polynomial functions for source representation," Opt. Express 22, 3924-3937 (2014)

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