Quantifying parameter uncertainties in optical scatterometry using Bayesian inversion
We present a Newton-like method to solve inverse problems and to quantify parameter uncertainties. We apply the method to parameter reconstruction in optical scatterometry, where we take into account a priori information and measurement uncertainties using a Bayesian approach. Further, we discuss th...
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| creator | Hammerschmidt, M Weiser, M X Garcia Santiago Zschiedrich, L Bodermann, B Burger, S |
| description | We present a Newton-like method to solve inverse problems and to quantify parameter uncertainties. We apply the method to parameter reconstruction in optical scatterometry, where we take into account a priori information and measurement uncertainties using a Bayesian approach. Further, we discuss the influence of numerical accuracy on the reconstruction result. |
| doi_str_mv | 10.48550/arxiv.1707.08467 |
| format | Article |
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| subjects | Bayesian analysis Inverse problems Newton methods Parameter uncertainty Physics - Computational Physics Physics - Optics Reconstruction |
| title | Quantifying parameter uncertainties in optical scatterometry using Bayesian inversion |
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