Distributed model calibration using Levenberg-Marquardt algorithm

Mark Lu; Liang Zhu; Li Ling; Gary Zhang; Walter Chan; Xin Zhou

doi:10.1117/12.711564

26 March 2007 Distributed model calibration using Levenberg-Marquardt algorithm

Mark Lu, Liang Zhu, Li Ling, Gary Zhang, Walter Chan, Xin Zhou

Proceedings Volume 6520, Optical Microlithography XX; 65203C (2007) https://doi.org/10.1117/12.711564
Event: SPIE Advanced Lithography, 2007, San Jose, California, United States

Abstract

The number of tunable parameters increases dramatically as we push forward to the next node of hyper-NA immersion lithography. It is very important to keep the lithographic process model calibration time under control, and its end result insensitive to either the starting point in the parameter space or the noise in the measurement data. For minimizing the least-squares error of a multivariate non-linear system, the industry standard is the Levenberg-Marquardt algorithm. We describe a distributed computing technique that is natural to the algorithm, and easy to implement in a cluster of computers. Applying this technique to calibrating lithographic process model, we can achieve robust optimization results in nearly constant calibration time.

Citation Download Citation

Mark Lu, Liang Zhu, Li Ling, Gary Zhang, Walter Chan, and Xin Zhou "Distributed model calibration using Levenberg-Marquardt algorithm", Proc. SPIE 6520, Optical Microlithography XX, 65203C (26 March 2007); https://doi.org/10.1117/12.711564

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