Sampling-based imaging model for fast source and mask optimization in immersion lithography

Current source and mask optimization (SMO) research tends to focus on advanced inverse optimization algorithms to accelerate SMO procedures. However, innovations of forward imaging models currently attract little attention, which impacts computational efficiency more significantly. A sampling-based...

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Bibliographic Details
Published in:Applied optics. Optical technology and biomedical optics Vol. 61; no. 2; p. 523
Main Authors: Sun, Yiyu, Li, Yanqiu, Liao, Guanghui, Yuan, Miao, Wei, Pengzhi, Li, Yaning, Zou, Lulu, Liu, Lihui
Format: Journal Article
Language:English
Published: United States 10.01.2022
ISSN:1539-4522, 2155-3165, 1539-4522
Online Access:Get more information
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Summary:Current source and mask optimization (SMO) research tends to focus on advanced inverse optimization algorithms to accelerate SMO procedures. However, innovations of forward imaging models currently attract little attention, which impacts computational efficiency more significantly. A sampling-based imaging model is established with the innovation of an inverse point spread function to reduce computational dimensions, which can provide an advanced framework for fast inverse lithography. Simulations show that the proposed SMO method with the help of the proposed model can further speed up the algorithm-accelerated SMO procedure by a factor of 3.
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ISSN:1539-4522
2155-3165
1539-4522
DOI:10.1364/AO.437655