@inproceedings{b1016de3d30c448895cf58cf67ab0d38,
title = "Fast lithographic source optimization adopting RMSProp with iterative shrinkage-thresholding algorithm compressive sensing for high fidelity patterning",
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.",
keywords = "compressive sensing, Computational lithography, DUV, lithographic, SO",
author = "Zhen Li and He Yang and Miao Yuan and Zhaoxuan Li and Yuqing Chen and Yanqiu Li",
note = "Publisher Copyright: {\textcopyright} 2024 SPIE.; 8th International Workshop on Advanced Patterning Solutions, IWAPS 2024 ; Conference date: 15-10-2024 Through 16-10-2024",
year = "2024",
doi = "10.1117/12.3052755",
language = "English",
series = "Proceedings of SPIE - The International Society for Optical Engineering",
publisher = "SPIE",
editor = "Yayi Wei and Tianchun Ye",
booktitle = "Eighth International Workshop on Advanced Patterning Solutions, IWAPS 2024",
address = "United States",
}