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Optics Express

Optics Express

  • Editor: Andrew M. Weiner
  • Vol. 21, Iss. 7 — Apr. 8, 2013
  • pp: 8076–8090

Efficient source and mask optimization with augmented Lagrangian methods in optical lithography

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

Optics Express, Vol. 21, Issue 7, pp. 8076-8090 (2013)

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Source mask optimization (SMO) is a powerful and effective technique to obtain sufficient process stability in optical lithography, particularly in view of the challenges associated with 22nm process technology and beyond. However, SMO algorithms generally involve computation-intensive nonlinear optimization. In this work, a fast algorithm based on augmented Lagrangian methods (ALMs) is developed for solving SMO. We first convert the optimization to an equivalent problem with constraints using variable splitting, and then apply an alternating minimization method which gives a straightforward implementation of the algorithm. We also use the quasi-Newton method to tackle the sub-problem so as to accelerate convergence, and a tentative penalty parameter schedule for adjustment and control. Simulation results demonstrate that the proposed method leads to faster convergence and better pattern fidelity.

© 2013 OSA

OCIS Codes
(110.3960) Imaging systems : Microlithography
(110.5220) Imaging systems : Photolithography
(110.1758) Imaging systems : Computational imaging

ToC Category:
Imaging Systems

Original Manuscript: January 31, 2013
Manuscript Accepted: March 8, 2013
Published: March 27, 2013

Jia Li, Shiyuan Liu, and Edmund Y. Lam, "Efficient source and mask optimization with augmented Lagrangian methods in optical lithography," Opt. Express 21, 8076-8090 (2013)

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