Applications
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Challenges of Grazing Emission X-ray Fluorescence (GEXRF) for the Characterization of Advanced Nanostructured Surfaces
In this paper, the grazing emission X-ray fluorescence (GEXRF) technique is analyzed to determine the spatial distribution of various chemical elements in nanostructures and is compared to the well-established GISAXS method. Simulations of the X-ray standing wave field in the vicinity of and inside the nanostructure are performed with JCMsuite to obtain the angle-resolved fluorescence intensities and the far field scattering intensities.
D. Skroblin et al. Challenges of grazing emission X-ray fluorescence (GEXRF) for the characterization of advanced nanostructured surfaces. Nanoscale, 14, 15475, (2022)
2022 DOI Publication link
Optical Metrology and Sensing, Optical and EUV Lithography, Light Scattering Computation, Optimization and Parameter Retrieval Methods
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Machine learning enhanced in situ electron beam lithography of photonic nanostructures
Pattern recognition based on specifically trained machine learning algorithms is applied to strongly enhance the capabilities of in-situ electron beam lithography. This is applied to integrate single InGaAs quantum dots into circular Bragg grating resonators, with an optimized device design derived using JCMsuite.
J. Donges et al. Machine learning enhanced in situ electron beam lithography of photonic nanostructures. Nanoscale 14, 14529 (2022).
2022 DOI Publication link
Light Sources, integrated optics, optical resonators and antennas, quantum optics, Optimization and Parameter Retrieval Methods
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Numerical optimization of single-mode fiber-coupled single-photon sources based on semiconductor quantum dots
Fiber-coupled single-photon sources emitting in the near-infrared, O- and C-band are designed for high photon coupling efficiencies. Extensive numerical simulations and optimizations with JCMsuite are performed to maximize the photon extraction and fiber-coupling efficiency of quantum dot single-photon sources based on micro mesas, microlenses, circular Bragg grating cavities, and micropillars.
L. Bremer, et al. Numerical optimization of single-mode fiber-coupled single-photon sources based on semiconductor quantum dots. Opt. Express 30, 15913-15928 (2022)
2022 DOI Publication link
Light Sources, quantum optics, Light Scattering Computation, Optimization and Parameter Retrieval Methods
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Bayesian Target-Vector Optimization for Efficient ParameterReconstruction
In this paper, a Bayesian target-vector optimization scheme, specialized for parameter reconstruction problems with hundreds of observations is presented. The performance is compared to established methods for an optical metrology problem and two least-square problems.
M. Plock, et al. Bayesian Target-Vector Optimization for Efficient ParameterReconstruction. Advanced Theory and Simulations, 5, 2200112 (2022).
2022 DOI Publication link
Optical Metrology and Sensing, Optimization and Parameter Retrieval Methods, Uncertainty Quantification Methods
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Eigenfrequency sensitivities using Riesz projections for efficient optimization of nanophotonic resonators
The Riesz projection method allows to efficiently compute the eigenfrequency sensitivities of resonance problems. These are then used to optimize a nano resonator in terms of Q-factor, where the required scattering solutions are computed with the FEM method of JCMsuite.
F. Binkowski, et al. Computation of eigenfrequency sensitivities using Riesz projections for efficient optimization of nanophotonic resonators. Commun. Phys. 5, 202 (2022).
2022 DOI Publication link
optical resonators and antennas, Advanced Finite Element Methods, Optimization and Parameter Retrieval Methods, Resonance Mode Computation
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Compact Plug and Play Optical Frequency Reference Device Based on Doppler-free Spectroscopy of Rubidium Vapor
A standalone plug-and-play optical frequency reference device based on frequency modulation spectroscopy of the D2-transition in rubidium at 780 nm is presented. The Bayesian optimizer from JCMsuite is used to demonstrate a short-term frequency stability improvement by varying the modulation parameters.
A. Strangerfeld, et al. Compact plug and play optical frequency reference device based on Doppler-free spectroscopy of rubidium vapor. Opt. Express, 30, 12039-12047, (2022).
2022 DOI Publication link
other fields, quantum optics, Optimization and Parameter Retrieval Methods
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Electromagnetically Chiral Scatterers at Optical Frequencies
The CD of Silver helices within Milli-Q water is measured at discrete frequencies from far infrared to the optical band. The em-chirality of the helices is optimized with JCMsuite by combining the shape derivatives for the T-matrices with the Bayesian optimization algorithm.
X. Garcia-Santiago, et al. Toward Maximally Electromagnetically Chiral Scatterers at Optical Frequencies. ACS Photonics 9, 1954 (2022).
2022 DOI Publication link
optical chirality, plasmonics, Optimization and Parameter Retrieval Methods
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Bayesian optimization with improved scalability and derivative information for efficient design of nanophotonic structures
The authors propose an iterative inversion scheme for Bayesian optimization to find optimal designs of nanophotonic devices. This improves the scalability of the approach and allows to apply it in situations where a larger number of iterations is required and where derivative information is available.
X. Garcia-Santiago, et al. Bayesian Optimization With Improved Scalability and Derivative Information for Efficient Design of Nanophotonic Structures. J. Lightwave Technol., 39, 167 (2021).
2021 DOI Publication link
all, integrated optics, Light Scattering Computation, Optimization and Parameter Retrieval Methods
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Optimized diamond inverted nanocones for enhanced color center to fiber coupling
The emission from color centers in inverted nanocones is numerically investigated using JCMsuite's finite-element solver and Bayesian optimizer. The study considers, e.g., optimizations of the nano cone geometry and the parameters of the collecting optics to maximize the fiber coupling efficiency.
C. G. Torun, et al. Optimized diamond inverted nanocones for enhanced color center to fiber coupling. Appl. Phys. Lett, 118, 234002 (2021).
2021 DOI Publication link
Light Sources, quantum optics, Light Scattering Computation, Optimization and Parameter Retrieval Methods, Propagation Mode Computation
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Bayesian optimization of metal grating back reflectors for multijunction solar cells
A triple-junction solar cell with a metal grating back reflector is accurately simulated using JCMsuite's finite-element solver. Based on the simulations the parameters of the metal grating are optimized with JCMsuite's Analysis and Optimization Toolkit to maximize the efficiency of the solar cell.
P. Tillmann, et al. Optimizing metal grating back reflectors for III-V-on-silicon multijunction solar cells. Opt. Express 29, 22517 (2021).
2021 DOI Publication link
Photovoltaics, diffractive optics, plasmonics, Light Scattering Computation, Optimization and Parameter Retrieval Methods, Uncertainty Quantification Methods
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Shape- and element-sensitive reconstruction of periodic nanostructures with grazing incidence X-ray fluorescence analysis and machine learning
The angular resolved fluorescence signal from a grazing incidence X-ray illumination of periodic nanostructures is used to reconstruct its geometry parameters. The parameter reconstruction using JCMsuite is based on a finite-element model of the scattering and fluorescence process as well as an efficient Bayesian minimization of the disagreement between the simulated and the measured fluorescence signal.
A. Andrle, et al. Shape- and element-sensitive reconstruction of periodic nanostructures with grazing incidence X-ray fluorescence analysis and machine learning. Nanomaterials, 11, 7 (2021).
2021 DOI Publication link
Optical Metrology and Sensing, Light Scattering Computation, Optimization and Parameter Retrieval Methods, Uncertainty Quantification Methods
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Recent advances in Bayesian optimization with applications to parameter reconstruction in optical nano-metrology
A Bayesian target vector optimization method is presented that enables the fast reconstruction of model parameters from measurements. It combines the advantages of conventional Bayesian optimization with specialized curve fitting algorithms such as the Levenberg-Marquardt method. The method is implemented in JCMsuite's Analysis and Optimization Toolkit.
M. Plock, et al. Recent advances in Bayesian optimization with applications to parameter reconstruction in optical nano-metrology. Proc. SPIE 11783,117830J (2021).
2021 DOI Publication link
Optical Metrology and Sensing, Optimization and Parameter Retrieval Methods
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Deterministically fabricated spectrally-tunable quantum dot based single-photon source
A spectrally-tunable quantum light sources is presented, which consitst of a quantum-dot integrated into a microlens that is bonded onto a piezoelectric actuator. The device and lens geometry were optimized using JCMsuite.
M. Schmidt, et al. Deterministically fabricated spectrally-tunable quantum dot based single-photon source. Optical Materials Express, 10.1, 76 (2020).
2020 DOI Publication link
Light Sources, integrated optics, quantum optics, Light Scattering Computation, Optimization and Parameter Retrieval Methods
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Benchmark of Global Optimization Approaches for Nano-optical Shape Optimization and Parameter Reconstruction
Several global optimization methods for three typical nano-optical optimization problems are benchmarked: particle swarm optimization, differential evolution, and Bayesian optimization as well as multistart versions of downhill simplex optimization and the limited-memory Broyden–Fletcher–Goldfarb–Shanno (L-BFGS) algorithm. In the shown examples, Bayesian optimization, mainly known from machine learning applications, obtains significantly better results in a fraction of the run times of the other optimization methods.
P.-I. Schneider, et al. Benchmarking five global optimization approaches for nano-optical shape optimization and parameter reconstruction. ACS Photonics 6, 2726 (2019).
2019 DOI
Metamaterials, Optical Metrology and Sensing, Optical and EUV Lithography, quantum optics, Optimization and Parameter Retrieval Methods, software benchmarks
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JCMsuite used for Mueller matrix ellipsometry
JCMsuite is used as Maxwell solver in Mueller matrix ellipsometry, in this work by the German national metrology institute PTB.
T. Kaeseberg, et al. Mueller matrix ellipsometry for enhanced optical form metrology of sub-lambda structures. Proc. SPIE 11057, 110570R (2019).
2019 DOI
Optical Metrology and Sensing, Optimization and Parameter Retrieval Methods, software benchmarks
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Gaussian process regression for efficient parameter reconstruction
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. The performance of Bayesian optimization as implemented in JCMsuite's optimization toolbox is compared to different local minimization algorithms for this numerical optimization problem. Bayesian optimization uses Gaussian-process regression to find promising parameter values. The paper examines how pre-computed simulation results can be used to train the Gaussian process and to accelerate the optimization.
P.-I. Schneider, et al. Using Gaussian process regression for efficient parameter reconstruction. Proc. SPIE 10959, 1095911 (2019).
2019 DOI
Optical Metrology and Sensing, Optical and EUV Lithography, Optimization and Parameter Retrieval Methods, software benchmarks
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Grazing incidence x-ray fluorescence based profile reconstruction
Rigorous field simulations obtained from a Maxwell solver (JCMsuite) in combination with Bayesian optimization allow to determine the spatial distribution of elemental species and the geometrical shape with sub-nm resolution.
A. Andrle, et al. Grazing incidence x-ray fluorescence based characterization of nanostructures for element sensitive profile reconstruction. Proc. SPIE 11057, 110570M (2019).
2019 DOI
Optical Metrology and Sensing, Optical and EUV Lithography, Advanced Finite Element Methods, Optimization and Parameter Retrieval Methods
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Element sensitive reconstruction of nanostructured surfaces with finite elements and grazing incidence soft X-ray fluorescence
The geometry of lamellar gratings is investigated experimentally with reference-free grazing-incidence X-ray fluorescence analysis. The demonstrated combination of GIXRF and finite-element simulations paves the way for a versatile characterization of nanoscale-structured surfaces.
V. Soltwisch, et al. Element sensitive reconstruction of nanostructured surfaces with finite elements and grazing incidence soft X-ray fluorescence. Nanoscale 10, 6177 (2018).
2018 DOI
Optical Metrology and Sensing, Optical and EUV Lithography, Light Scattering Computation, Optimization and Parameter Retrieval Methods
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Optimization of free-form shapes using a global optimization method
Optimizing free-form shapes of photonic nanostructures is a high-dimensional problem. A Bayesian optimization algorithm with a hyper-parameter learning routine is applied to optimize the shape of a reflecting meta-surface.
X. Garcia-Santiago, et al. Shape design of a reflecting surface using Bayesian Optimization. J. Phys.: Conf. Ser. 963, 012003 (2018).
2018 DOI Publication link
Metamaterials, diffractive optics, Optimization and Parameter Retrieval Methods
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Evaluating the effects of modeling errors for isolated finite three-dimensional targets
Optical three-dimensional (3-D) nanostructure metrology utilizes a model-based metrology approach to determine critical dimensions (CDs) that are well below the inspection wavelength. A project at the National Institute of Standards and Technology is evaluating how to attain key CD and shape parameters from engineered in-die capable metrology targets. The performance of simplified models is validated using highly accurate, fully 3D simulations.
M. A. Henn, et al. Evaluating the effects of modeling errors for isolated finite three-dimensional targets. J. of Micro/Nanolithography, MEMS, and MOEMS, 16, 044001 (2017).
2017 DOI
Optical Metrology and Sensing, Optical and EUV Lithography, Advanced Finite Element Methods, Optimization and Parameter Retrieval Methods