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Proceedings Paper

Compressive sensing method for EUV source optimization using different bases
Author(s): Jiaxin Lin; Lisong Dong; Taian Fan; Xu Ma; Rui Chen; Xiaoran Zhang; Hans-Juergen Stock; Yayi Wei
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Paper Abstract

An EUV source optimization technique using compressive sensing is introduced in this paper. The pixelated source pattern is sparsely represented in a set of certain basis functions. Blue noise sampling method is used to select sampling points around the margins of the target layout for imaging fidelity evaluation. Based on the compressive sensing theory, the EUV SO is formulated as an l1-norm inverse reconstruction problem and solved by the linearized Bregman algorithm. Different types of sparse bases are also experimented in this paper to investigate their impact on the SO results. These bases include the 2D-DCT basis, spatial basis, Zernike basis, and Haar wavelet basis. Simulations show that ℓthe Haar wavelet basis results in the best imaging fidelity among the four types of bases.

Paper Details

Date Published: 23 March 2020
PDF: 7 pages
Proc. SPIE 11323, Extreme Ultraviolet (EUV) Lithography XI, 113232J (23 March 2020); doi: 10.1117/12.2551897
Show Author Affiliations
Jiaxin Lin, Institute of Microelectronics (China)
Univ. of Chinese Academy of Sciences (China)
Lisong Dong, Institute of Microelectronics (China)
Taian Fan, Institute of Microelectronics (China)
Xu Ma, Beijing Institute of Technology (China)
Rui Chen, Institute of Microelectronics (China)
Xiaoran Zhang, North China Univ. of Technology (China)
Hans-Juergen Stock, Synopsys GmbH (Germany)
Yayi Wei, Institute of Microelectronics (China)
Univ. of Chinese Academy of Sciences (China)


Published in SPIE Proceedings Vol. 11323:
Extreme Ultraviolet (EUV) Lithography XI
Nelson M. Felix; Anna Lio, Editor(s)

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