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13 June 2022 Principal component analysis of stochasticity in resist films
Hiroshi Fukuda
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Proceedings Volume PC12051, Optical and EUV Nanolithography XXXV; PC120510J (2022) https://doi.org/10.1117/12.2610998
Event: SPIE Advanced Lithography + Patterning, 2022, San Jose, California, United States
Abstract
Spatial fluctuation in reactions throughout exposed resist films is analyzed by principal component analysis (PCA) or singular value decomposition (SVD), which is known as generalization of Fourie transform. In optical simulations, image is expressed by a wave function obtained from SVD of matrix representation of optical images. We attempt to extend this to density/probability distributions of resist reactions for analyzing probabilistic behavior of resists such as LER/LCDU and stochastic defects. To show its effectiveness, PCA is applied to reaction distributions calculated by the fully coupled Monte-Carlo simulation, which visualizes correlated reaction influences on spatial feature and probability of pattern anomalies.
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Hiroshi Fukuda "Principal component analysis of stochasticity in resist films", Proc. SPIE PC12051, Optical and EUV Nanolithography XXXV, PC120510J (13 June 2022); https://doi.org/10.1117/12.2610998
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KEYWORDS
Principal component analysis
Fourier transforms
Image transmission
Lithography
Monte Carlo methods
Optical simulations
Stochastic processes
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