TY - JOUR A1 - Sekulic, Ivan A1 - Schaible, Jonas A1 - Müller, Gabriel A1 - Plock, Matthias A1 - Burger, Sven A1 - Martínez-Lahuerta, Víctor José A1 - Gaaloul, Naceur A1 - Schneider, Philipp-Immanuel T1 - Physics-informed Bayesian optimization of expensive-to-evaluate black-box functions JF - Mach. Learn. Sci. Technol. N2 - Abstract Bayesian optimization with Gaussian process surrogates is a popular approach for optimizing expensive-to-evaluate functions in terms of time, energy, or computational resources. Typically, a Gaussian process models a scalar objective derived from observed data. However, in many real-world applications, the objective is a combination of multiple outputs from physical experiments or simulations. Converting these multidimensional observations into a single scalar can lead to information loss, slowing convergence and yielding suboptimal results. To address this, we propose to use multi-output Gaussian processes to learn the full vector of observations directly, before mapping them to the scalar objective via an inexpensive analytical function. This physics-informed approach retains more information from the underlying physical processes, improving surrogate model accuracy. As a result, the approach accelerates optimization and produces better final designs compared to standard implementations. Y1 - 2025 U6 - https://doi.org/10.1088/2632-2153/ae1f5f VL - 6 SP - 040503 PB - IOP Publishing ER - TY - THES A1 - Plock, Matthias T1 - On Methods for Bayesian Optimization of Least Squares Problems and Optimization of Nanophotonic Devices Y1 - 2025 U6 - https://doi.org/10.17169/refubium-48179 ER - TY - GEN A1 - Sekulic, Ivan A1 - Schaible, Jonas A1 - Müller, Gabriel A1 - Plock, Matthias A1 - Burger, Sven A1 - Martinez-Lahuerta, Victor J. A1 - Gaaloul, Naceur A1 - Schneider, Philipp-Immanuel T1 - Data publication for Physics-informed Bayesian optimization of expensive-to-evaluate black-box functions T2 - Zenodo Y1 - 2025 U6 - https://doi.org/10.5281/zenodo.16751507 ER - TY - CHAP A1 - Hammerschmidt, Martin A1 - Plock, Matthias A1 - Burger, Sven A1 - Truong, Vinh A1 - Soltwisch, Victor A1 - Schneider, Philipp-Immanuel T1 - Machine learning approach for full Bayesian parameter reconstruction T2 - Proc. SPIE Y1 - 2025 U6 - https://doi.org/10.1117/12.3062268 VL - 13568 SP - 1356806 ER - TY - JOUR A1 - Binkowski, Felix A1 - Koulas-Simos, Aris A1 - Betz, Fridtjof A1 - Plock, Matthias A1 - Sekulic, Ivan A1 - Manley, Phillip A1 - Hammerschmidt, Martin A1 - Schneider, Philipp-Immanuel A1 - Zschiedrich, Lin A1 - Munkhbat, Battulga A1 - Reitzenstein, Stephan A1 - Burger, Sven T1 - High Purcell enhancement in all-TMDC nanobeam resonator designs with active monolayers for nanolasers JF - Phys. Rev. B Y1 - 2025 U6 - https://doi.org/10.1103/nxh9-dhvx VL - 112 SP - 235410 ER - TY - GEN A1 - Binkowski, Felix A1 - Koulas-Simos, Aris A1 - Betz, Fridtjof A1 - Plock, Matthias A1 - Sekulic, Ivan A1 - Manley, Phillip A1 - Hammerschmidt, Martin A1 - Schneider, Philipp-Immanuel A1 - Zschiedrich, Lin A1 - Munkhbat, Battulga A1 - Reitzenstein, Stephan A1 - Burger, Sven T1 - Source code and simulation results: High Purcell enhancement in all-TMDC nanobeam resonator designs with active monolayers for nanolasers T2 - Zenodo Y1 - 2025 U6 - https://doi.org/10.5281/zenodo.16533803 ER - TY - CHAP A1 - Schneider, Philipp-Immanuel A1 - Sekulic, Ivan A1 - Plock, Matthias A1 - Hammerschmidt, Martin A1 - Rodt, Sven A1 - Reitzenstein, Stephan A1 - Burger, Sven T1 - Physics-informed Bayesian optimization of nanophotonic devices T2 - Advanced Photonics Congress Y1 - 2025 U6 - https://doi.org/10.1364/IPRSN.2025.ITu1A.2 VL - IPRSN SP - ITu1A.2 ER - TY - GEN A1 - Bopp, Julian M. A1 - Plock, Matthias A1 - Turan, Tim A1 - Pieplow, Gregor A1 - Burger, Sven A1 - Schröder, Tim T1 - ‘Sawfish’ Photonic Crystal Cavity for Near-Unity Emitter-to-Fiber Interfacing in Quantum Network Applications (Advanced Optical Materials 13/2024) T2 - Adv. Optical Mater. Y1 - 2024 U6 - https://doi.org/10.1002/adom.202470046 VL - 12 SP - 2470046 ER - TY - JOUR A1 - Bopp, Julian M. A1 - Plock, Matthias A1 - Turan, Tim A1 - Pieplow, Gregor A1 - Burger, Sven A1 - Schröder, Tim T1 - Sawfish Photonic Crystal Cavity for Near-Unity Emitter-to-Fiber Interfacing in Quantum Network Applications JF - Adv. Opt. Mater. Y1 - 2024 U6 - https://doi.org/10.1002/adom.202301286 VL - 12 SP - 2301286 ER - TY - JOUR A1 - Plock, Matthias A1 - Binkowski, Felix A1 - Zschiedrich, Lin A1 - Schneider, Phillip-Immanuel A1 - Burger, Sven T1 - Fabrication uncertainty guided design optimization of a photonic crystal cavity by using Gaussian processes JF - J. Opt. Soc. Am. B Y1 - 2024 U6 - https://doi.org/10.1364/JOSAB.505767 VL - 41 SP - 850 ER - TY - GEN A1 - Plock, Matthias A1 - Binkowski, Felix A1 - Zschiedrich, Lin A1 - Schneider, Phillip-Immanuel A1 - Burger, Sven T1 - Research data for "Fabrication uncertainty guided design optimization of a photonic crystal cavity by using Gaussian processes" T2 - Zenodo Y1 - 2024 U6 - https://doi.org/10.5281/zenodo.8131611 SP - doi: 10.5281/zenodo.8131611 ER - TY - CHAP A1 - Bopp, Julian M. A1 - Plock, Matthias A1 - Turan, Tim A1 - Pieplow, Gregor A1 - Burger, Sven A1 - Schröder, Tim T1 - ‘Sawfish’ Spin-Photon Interface for Near-Unity Emitter-to-Waveguide Coupling T2 - Conference on Lasers and Electro-Optics (CLEO) Y1 - 2023 U6 - https://doi.org/10.1364/CLEO_SI.2023.SF1O.6 SP - SF1O.6 ER - TY - CHAP A1 - Plock, Matthias A1 - Burger, Sven A1 - Schneider, Philipp-Immanuel T1 - Efficient reconstruction of model parameters using Bayesian target-vector optimization T2 - Proc. SPIE Y1 - 2023 U6 - https://doi.org/10.1117/12.2673590 VL - PC12619 SP - PC1261905 ER - TY - JOUR A1 - Plock, Matthias A1 - Hammerschmidt, Martin A1 - Burger, Sven A1 - Schneider, Philipp-Immanuel A1 - Schütte, Christof T1 - Impact Study of Numerical Discretization Accuracy on Parameter Reconstructions and Model Parameter Distributions JF - Metrologia N2 - In optical nano metrology numerical models are used widely for parameter reconstructions. Using the Bayesian target vector optimization method we fit a finite element numerical model to a Grazing Incidence x-ray fluorescence data set in order to obtain the geometrical parameters of a nano structured line grating. Gaussian process, stochastic machine learning surrogate models, were trained during the reconstruction and afterwards sampled with a Markov chain Monte Carlo sampler to determine the distribution of the reconstructed model parameters. The numerical discretization parameters of the used finite element model impact the numerical discretization error of the forward model. We investigated the impact of the polynomial order of the finite element ansatz functions on the reconstructed parameters as well as on the model parameter distributions. We showed that such a convergence study allows to determine numerical parameters which allows for efficient and accurate reconstruction results. Y1 - 2023 U6 - https://doi.org/10.1088/1681-7575/ace4cd VL - 60 SP - 054001 ER - TY - JOUR A1 - Rickert, Lucas A1 - Betz, Fridtjof A1 - Plock, Matthias A1 - Burger, Sven A1 - Heindel, Tobias T1 - High-performance designs for fiber-pigtailed quantum-light sources based on quantum dots in electrically-controlled circular Bragg gratings JF - Opt. Express Y1 - 2023 U6 - https://doi.org/10.1364/OE.486060 VL - 31 SP - 14750 ER - TY - GEN A1 - Rickert, Lucas A1 - Betz, Fridtjof A1 - Plock, Matthias A1 - Burger, Sven A1 - Heindel, Tobias T1 - Data publication for "High-performance designs for fiber-pigtailed quantum-light sources based on quantum dots in electrically-controlled circular Bragg gratings" T2 - Zenodo Y1 - 2022 U6 - https://doi.org/10.5281/zenodo.7360516 SP - 7360516 ER - TY - GEN A1 - Plock, Matthias A1 - Andrle, Kas A1 - Burger, Sven A1 - Schneider, Philipp-Immanuel T1 - Research data and example scripts for the paper "Bayesian Target-Vector Optimization for Efficient Parameter Reconstruction" T2 - Zenodo Y1 - 2022 U6 - https://doi.org/10.5281/zenodo.6359594 ER - TY - JOUR A1 - Plock, Matthias A1 - Andrle, Kas A1 - Burger, Sven A1 - Schneider, Philipp-Immanuel T1 - Bayesian Target-Vector Optimization for Efficient Parameter Reconstruction JF - Adv. Theory Simul. Y1 - 2022 U6 - https://doi.org/10.1002/adts.202200112 VL - 5 SP - 2200112 ER - TY - JOUR A1 - Plock, Matthias A1 - Burger, Sven A1 - Schneider, Philipp-Immanuel T1 - Recent advances in Bayesian optimization with applications to parameter reconstruction in optical nano-metrology JF - Proc. SPIE Y1 - 2021 U6 - https://doi.org/10.1117/12.2592266 VL - 11783 SP - 117830J ER -