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Proceedings Paper

The statistical inverse problem of scatterometry: Bayesian inference and the effect of different priors
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Paper Abstract

Scatterometry is a fast indirect optical method for the determination of grating profile parameters of photomasks. Profile parameters are obtained from light diffracted intensities by solving an inverse problem. There are diverse methods to reconstruct profile parameters and to calculate associated uncertainties. To fit the upcoming need for improved accuracy and precision as well as for the reduction of uncertainties different measurements should be combined. Such a combination increases the knowledge about parameters and may yield smaller uncertainties. The Bayesian approach provides an appropriate method to evaluate combined measurements and to obtain the associated uncertainties. However, for computationally expensive problems like scatterometry, the direct application of Bayesian inference is very time consuming. Here, we use an approximation method based on a polynomial chaos expansion. To probe the quality of this approximation, we reconstructed geometry parameters, quantify uncertainties and study the effect of different prior informations onto the obtained grating profile parameters by using simulation data superimposed by noise.

Paper Details

Date Published: 21 June 2015
PDF: 6 pages
Proc. SPIE 9526, Modeling Aspects in Optical Metrology V, 95260U (21 June 2015); doi: 10.1117/12.2185707
Show Author Affiliations
Sebastian Heidenreich, Physikalisch-Technische Bundesanstalt (Germany)
Hermann Gross, Physikalisch-Technische Bundesanstalt (Germany)
Matthias Wurm, Physikalisch-Technische Bundesanstalt (Germany)
Bernd Bodermann, Physikalisch-Technische Bundesanstalt (Germany)
Markus Bär, Physikalisch-Technische Bundesanstalt (Germany)

Published in SPIE Proceedings Vol. 9526:
Modeling Aspects in Optical Metrology V
Bernd Bodermann; Karsten Frenner; Richard M. Silver, Editor(s)

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