Pattern selection in high-dimensional parameter spaces

Georg Viehoever; Brian Ward; Hans-Juergen Stock

doi:10.1117/12.916352

13 March 2012 Pattern selection in high-dimensional parameter spaces

Georg Viehoever, Brian Ward, Hans-Juergen Stock

Proceedings Volume 8326, Optical Microlithography XXV; 832618 (2012) https://doi.org/10.1117/12.916352
Event: SPIE Advanced Lithography, 2012, San Jose, California, United States

Abstract

Pattern selection for OPC model calibration is frequently done by image parameter space (IPS) coverage methods. These ensure that the images of the chosen test patterns cover important regions of an n-dimensional parameter space spawned by image parameters, such as minimum and maximum intensity I_min, I_max, curvature, slope and image density. But such a small number of parameters is often insufficient for finding a good set of patterns for the calibration process. We present results for the extended nPS method which ensures coverage of a high dimensional parameter space with a high number of parameters, even permitting the use of all pixels of the aerial images (n >> 1000) as parameters.

Citation Download Citation

Georg Viehoever, Brian Ward, and Hans-Juergen Stock "Pattern selection in high-dimensional parameter spaces", Proc. SPIE 8326, Optical Microlithography XXV, 832618 (13 March 2012); https://doi.org/10.1117/12.916352

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