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...

Ausführliche Beschreibung

Gespeichert in:

Bibliographische Detailangaben
Veröffentlicht in:	Applied optics. Optical technology and biomedical optics Jg. 61; H. 2; S. 523
Hauptverfasser:	Sun, Yiyu, Li, Yanqiu, Liao, Guanghui, Yuan, Miao, Wei, Pengzhi, Li, Yaning, Zou, Lulu, Liu, Lihui
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	United States 10.01.2022
ISSN:	1539-4522, 2155-3165, 1539-4522
Online-Zugang:	Weitere Angaben
Tags:	Tag hinzufügen Keine Tags, Fügen Sie den ersten Tag hinzu!

Beschreibung
Zusammenfassung:	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.
Bibliographie:	ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23
ISSN:	1539-4522 2155-3165 1539-4522
DOI:	10.1364/AO.437655