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Proceedings Paper

Pattern selection in high-dimensional parameter spaces
Author(s): Georg Viehoever; Brian Ward; Hans-Juergen Stock
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Paper 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.

Paper Details

Date Published: 13 March 2012
PDF: 12 pages
Proc. SPIE 8326, Optical Microlithography XXV, 832618 (13 March 2012); doi: 10.1117/12.916352
Show Author Affiliations
Georg Viehoever, Synopsys GmbH (Germany)
Brian Ward, Synoposys, Inc. (United States)
Hans-Juergen Stock, Synopsys GmbH (Germany)


Published in SPIE Proceedings Vol. 8326:
Optical Microlithography XXV
Will Conley, Editor(s)

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