Fast lithographic source optimization adopting RMSProp with iterative shrinkage-thresholding algorithm compressive sensing for high fidelity patterning

Zhen Li; He Yang; Miao Yuan; Zhaoxuan Li; Yuqing Chen; Yanqiu Li

doi:10.1117/12.3052755

10 December 2024 Fast lithographic source optimization adopting RMSProp with iterative shrinkage-thresholding algorithm compressive sensing for high fidelity patterning

Zhen Li, He Yang, Miao Yuan, Zhaoxuan Li, Yuqing Chen, Yanqiu Li

Author Affiliations +

Proceedings Volume 13423, Eighth International Workshop on Advanced Patterning Solutions (IWAPS 2024); 134230H (2024) https://doi.org/10.1117/12.3052755
Event: 8th International Workshop on Advanced Patterning Solutions (IWAPS 2024), 2024, Jiaxing, Zhejiang, China

Abstract

Fast Source Optimization (SO) is a critical requirement for the 14-5nm node in integrated lithography online technology. Our previous research introduced Bayesian Compressed Sensing SO (CCS-BCS-SO), which effectively delivered high pattern fidelity. However, its processing speed still lags behind that of compressive sensing (CS) SO. This paper introduces the first application of the iterative shrinkage - thresholding algorithm with RMSProp (RMSProp-ISTA) in compressive sensing. This innovation aims to ensure a high-fidelity pattern while improve convergence speed and accelerating SO. The results indicate that the CCS-RMSProp-ISTA-SO method is three times faster than the CCS-BCS-SO method, achieving the fast SO like CS-SO and the high pattern fidelity of SD-SO.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Zhen Li, He Yang, Miao Yuan, Zhaoxuan Li, Yuqing Chen, and Yanqiu Li "Fast lithographic source optimization adopting RMSProp with iterative shrinkage-thresholding algorithm compressive sensing for high fidelity patterning", Proc. SPIE 13423, Eighth International Workshop on Advanced Patterning Solutions (IWAPS 2024), 134230H (10 December 2024); https://doi.org/10.1117/12.3052755

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KEYWORDS

Compressed sensing

Lithography

Machine learning

Mathematical optimization

Matrices

Optical lithography

Light sources

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