| Zugriffsnummer | 39059 |
| Dokumenttyp | Konferenzartikel |
| Sprache | Englisch |
| Titel | Quantifying parameter uncertainties in optical scatterometry using Bayesian inversion |
| Autor(in); Institution |
Hammerschmidt, Martin; JCMwave GmbH, Berlin, GERMANY; Zuse Institut Berlin (ZIB), Berlin, GERMANY
Weiser, Martin; Zuse Institut Berlin (ZIB), Berlin, GERMANY
Garcia Santiago, Xavier; JCMwave GmbH, Berlin, GERMANY; Institut für Theoretische Festkörperphysik (KIT) Karlsruhe, GERMANY
Zschiedrich, Lin; JCMwave GmbH, Berlin, GERMANY
Bodermann, Bernd; 4.2, Bild- und Wellenoptik, PTB-Braunschweig
Burger, Sven; JCMwave GmbH, Berlin, GERMANY; Zuse Institut Berlin (ZIB), Berlin, GERMANY
|
| Quelle/Jahr | Modeling Aspects in Optical Metrology VI:(2017), 1033004-1 - 1033004-10 |
| Schriftenreihe | Proceedings of SPIE: 10330 |
| Herausgeber(in) |
Bodermann, Bernd; 4.2, Bild- und Wellenoptik, PTB-Braunschweig
|
| ISBN | 978-1-5106-1105-4 |
| DOI | |
| URL | |
| Verlag | Bellingham, Wash.: SPIE |
| Konferenzangaben | SPIE Conference Optical Metrology: Modeling Aspects in Optical Metrology VI, Munich, 26-28, Juni, 2017, Germany |
| Freie Schlagworte | computational metrology ; optical metrology ; computational lithography ; nanolithography ; finite-element methods ; nanooptics |
| Zusammenfassung | Optical scatterometry is a method to measure the size and shape of periodic micro- or nanostructures on surfaces. For this purpose the geometry parameters of the structures are obtained by reproducing experimental measurement results through numerical simulations. Such simulations are typically performed using parameterized models and nonlinear optimization algorithms to find parameter settings which minimize differences between the measurements and the numerically obtained result. Often also knowledge about experimental measurement errors and model uncertainties is available, as well as prior knowledge obtained from additional measurements. This can be used to also quantify uncertainties of the reconstructed parameter values. Here we demonstrate an efficent method for parameter reconstruction and uncertainty quantification using a Newton method to solve the inverse problem, an efficient finite-element based solver for the forward-problem, and a Bayesian approach for relating measurement uncertainties and prior knowledge to the reconstruction results. |
Zitierung
Hammerschmidt, M., Weiser, M., Garcia Santiago, X., Zschiedrich, L., Bodermann, B., & Burger, S. (2017). Quantifying parameter uncertainties in optical scatterometry using Bayesian inversion. SPIE Conference Optical Metrology: Modeling Aspects in Optical Metrology VI, Munich, 26-28, Juni, 2017, Germany. https://doi.org/10.1117/12.2270596