Importance sampling in Gaussian random field EUV stochastic model for quantification of stochastic variability of EUV vias

Zexin Pan; Azat Latypov; Chih-I Wei; Peter De Bisschop; Germain Fenger; John Sturtevant

doi:10.1117/12.2658651

28 April 2023 Importance sampling in Gaussian random field EUV stochastic model for quantification of stochastic variability of EUV vias

Zexin Pan, Azat Latypov, Chih-I Wei, Peter De Bisschop, Germain Fenger, John Sturtevant

Author Affiliations +

Proceedings Volume 12494, Optical and EUV Nanolithography XXXVI; 1249419 (2023) https://doi.org/10.1117/12.2658651
Event: SPIE Advanced Lithography + Patterning, 2023, San Jose, California, United States

Conference Poster

Abstract

Importance Sampling methods allow to substantially reduce the number of trials in estimation of the rare failure probability or other stochastic metrics. These methods can be viewed as a rigorous generalization of quantitative “torture” or “stress” methods where the process is artificially modified to increase the probability of failure, and the failure probability estimations obtained for such modified process are extrapolated to the original process with rare failures. Applications of Importance Sampling methods are presented and demonstrated on computationally efficient estimations of via failure probability and via LCDU. The accuracy of the Importance Sampling LCDU estimates is verified by comparison with experimental results. Applications of Importance Sampling methods to experimental measurements are discussed.

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Zexin Pan, Azat Latypov, Chih-I Wei, Peter De Bisschop, Germain Fenger, and John Sturtevant "Importance sampling in Gaussian random field EUV stochastic model for quantification of stochastic variability of EUV vias", Proc. SPIE 12494, Optical and EUV Nanolithography XXXVI, 1249419 (28 April 2023); https://doi.org/10.1117/12.2658651

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