| Zugriffsnummer | 30853 |
| Dokumenttyp | Konferenzartikel in Zeitschrift |
| Peer Review | unbekannt |
| Sprache | Englisch |
| Titel | A surrogate model enables a Bayesian approach to the inverse problem of scatterometry |
| Autor(in); Institution |
Heidenreich, Sebastian; 8.4, Mathematische Modellierung und Datenanalyse, PTB-Berlin
Gross, Hermann; 8.4, Mathematische Modellierung und Datenanalyse, PTB-Berlin
Henn, Mark-Alexander; 8.4, Mathematische Modellierung und Datenanalyse, PTB-Berlin
Elster, Clemens; 8.4, Mathematische Modellierung und Datenanalyse, PTB-Berlin
Bär, Markus; 8.4, Mathematische Modellierung und Datenanalyse, PTB-Berlin
|
| Quelle/Jahr | Journal of Physics: Conference Series: 490 (2014), 1, 1 - 4 |
| Artikelnummer | 012007 |
| ISSN | 1742-6588 (PRINT) ; 1742-6596 (ONLINE) |
| DOI | |
| Verlag | Bristol: IOP Publ. |
| Konferenzangaben | 2nd International Conference on Mathematical Modeling in Physical Sciences 2013 (IC-MSQUARE 2013), Prague, 1-5, September, 2013, Czech Republic |
| Klassifikationscode | PACS: 02.30.Zz ; PACS: 02.30.Jr ; PACS: 02.50.Ng ; PACS: 02.50.Cw ; PACS: 02.50.Ga ; PACS: 02.10.De |
| Freie Schlagworte | Bayesian inference ; surrogate model ; scatterometry ; polynomial chaos |
| Zusammenfassung | Scatterometry is an indirect optical method for the determination of photomask geometry parameters from scattered light intensities by solving an inverse problem. The Bayesian approach is a powerful method to solve the inverse problem. In the Bayesian framework estimates of parameters and associated uncertainties are obtained from posterior distributions. The determination the probability distribution is typically based on Markov chain Monte Carlo (MCMC) methods. However, in scatterometry the evaluation of MCMC steps require solutions of partial differential equations that are computationally expensive and application of MCMC methods is thus impractical. In this article we introduce a surrogate model for scatterometry based on polynomial chaos that can be treated by Bayesian inference. We compare the results of the surrogate model with rigorous finite element simulations and demonstrate its convergence. The accuracy reaches a value of lower than one percent for a sufficient fine mesh and the speed up amounts more than two order of magnitudes. Furthermore, we apply the surrogate model to MCMC calculations and we reconstruct geometry parameters of a photomask. |
| Kostenfreier Zugang | Open Access Gold |
| Rechteinformation | CC BY 3.0 ; Creative Commons Attribution 3.0 License |