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5 papers · 1 filter
Recent advances in Bayesian optimization with applications to parameter reconstruction in optical nano-metrology
Matthias Plock, Sven Burger, Philipp-Immanuel Schneider
Parameter reconstruction is a common problem in optical nano metrology. It generally involves a set of measurements, to which one attempts to fit a numerical model of the measureme…
Bayesian optimization with improved scalability and derivative information for efficient design of nanophotonic structures
Xavier Garcia-Santiago, Sven Burger, Carsten Rockstuhl +1
We propose the combination of forward shape derivatives and the use of an iterative inversion scheme for Bayesian optimization to find optimal designs of nanophotonic devices. This…
Effective medium approximation of ellipsometric response from random surface roughness simulated by finite-element method
B. Fodor, P. Kozma, S. Burger +2
We used numerical simulations based on the finite element method (FEM) to calculate both the amplitude and phase information of the scattered electric field from random rough surfa…
Molecular dynamics of open systems: construction of a mean-field particle reservoir
Luigi Delle Site, Christian Krekeler, John Whittaker +3
The simulation of open molecular systems requires explicit or implicit reservoirs of energy and particles. Whereas full atomistic resolution is desired in the region of interest, t…
Quantifying parameter uncertainties in optical scatterometry using Bayesian inversion
M. Hammerschmidt, M. Weiser, X. Garcia Santiago +3
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 w…