Displaying items by tag: optimization and parameter retrieval methods

Recent advances in Bayesian optimization with applications to parameter reconstruction in optical nano-metrology

Published in 2021
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Shape- and element-sensitive reconstruction of periodic nanostructures with grazing incidence X-ray fluorescence analysis and machine learning

Published in 2021
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Optimized diamond inverted nanocones for enhanced color center to fiber coupling

Published in 2021
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Bayesian optimization of metal grating back reflectors for multijunction solar cells

Published in 2021
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Bayesian optimization with improved scalability and derivative information for efficient design of nanophotonic structures

Published in 2021
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Deterministically fabricated spectrally-tunable quantum dot based single-photon source

Published in 2020
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Element sensitive reconstruction of nanostructured surfaces with finite elements and grazing incidence soft X-ray fluorescence

Published in 2018
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Optimization of free-form shapes using a global optimization method

Published in 2018
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Metrology of nanoscale grating structures by UV scatterometry

Published in 2017
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Investigating surface structures by EUV scattering

Published in 2017
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Evaluating the effects of modeling errors for isolated finite three-dimensional targets

Published in 2017
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Quantifying parameter uncertainties in optical scatterometry using Bayesian inversion

Published in 2017
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Quantitative optical imaging for in-die-capable critical dimension targets

Published in 2016
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Fiber grating couplers on SOI

Published in 2014
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Efficient Bayesian inversion for shape reconstruction of lithography masks

Published in 2010
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JCMsuite used for Mueller matrix ellipsometry

Published in 2019
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Benchmark of Global Optimization Approaches for Nano-optical Shape Optimization and Parameter Reconstruction

Published in 2019
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Gaussian process regression for efficient parameter reconstruction

Published in 2019
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Grazing incidence x-ray fluorescence based profile reconstruction

Published in 2019
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