TY - JOUR A1 - Torun, Cem Güney A1 - Schneider, Philipp-Immanuel A1 - Hammerschmidt, Martin A1 - Burger, Sven A1 - Munns, Joseph H.D. A1 - Schröder, Tim T1 - Optimized diamond inverted nanocones for enhanced color center to fiber coupling JF - Appl. Phys. Lett. Y1 - 2021 U6 - https://doi.org/10.1063/5.0050338 VL - 118 SP - 234002 ER - TY - CHAP A1 - Schneider, Philipp-Immanuel A1 - Garcia-Santiago, Xavier A1 - Wiegand, Benjamin A1 - Anton, Oliver A1 - Krutzik, Markus A1 - Rockstuhl, Carsten A1 - Burger, Sven T1 - Advances in Bayesian optimization for photonics and quantum atom optics applications T2 - OSA Advanced Photonics Congress Y1 - 2021 U6 - https://doi.org/10.1364/IPRSN.2021.JTh1E.2 SP - JTh1E.2 ER - TY - CHAP A1 - Musial, Anna A1 - Zolnacz, Kinga A1 - Srocka, Nicole A1 - Kravets, Oleh A1 - Große, Jan A1 - Schneider, Philipp-Immanuel A1 - Olszewski, Jacek A1 - Poturaj, Krzystof A1 - Wojcik, Grzegorz A1 - Mergo, Pawel A1 - Dybka, Kamil A1 - Dyrkacz, Mariusz A1 - Dlubek, Michal A1 - Rodt, Sven A1 - Burger, Sven A1 - Zschiedrich, Lin A1 - Urbanczyk, Waclaw A1 - Sek, Grzegorz A1 - Reitzenstein, Stephan T1 - Stand-alone quantum dot-based single-photon source operating at telecommunication wavelengths T2 - 10th International Conference on Spontaneous Coherence in Excitonic Systems ICSCE10 Y1 - 2020 SP - 39 ER - TY - CHAP A1 - Hammerschmidt, Martin A1 - Zschiedrich, Lin A1 - Siaudinyté, Lauryna A1 - Manley, Phillip A1 - Schneider, Philipp-Immanuel A1 - Burger, Sven T1 - Forward simulation of coherent beams on grating structures for coherent scatterometry T2 - Proc. SPIE Y1 - 2023 U6 - https://doi.org/10.1117/12.2673231 VL - PC12619 SP - PC1261907 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 - Anton, Oliver A1 - Henderson, Victoria A. A1 - Da Ros, Elisa A1 - Sekulic, Ivan A1 - Burger, Sven A1 - Schneider, Philipp-Immanuel A1 - Krutzik, Markus T1 - Review and experimental benchmarking of machine learning algorithms for efficient optimization of cold atom experiments JF - Mach. Learn. Sci. Technol. Y1 - 2024 U6 - https://doi.org/10.1088/2632-2153/ad3cb6 VL - 5 SP - 025022 ER - TY - CHAP A1 - Sekulic, Ivan A1 - Schneider, Philipp-Immanuel A1 - Anton, Oliver A1 - Da Ros, Elisa A1 - Henderson, Victoria A1 - Krutzik, Markus T1 - Efficient machine-learning approach to optimize trapped cold atom ensembles for quantum memory applications T2 - Proc. SPIE Y1 - 2023 U6 - https://doi.org/10.1117/12.2684406 VL - 12740 SP - 127400F ER - TY - CHAP A1 - Krüger, Jan A1 - Bodermann, Bernd A1 - Köning, Rainer A1 - Manley, Phillip A1 - Zschiedrich, Lin A1 - Schneider, Philipp-Immanuel A1 - Heinrich, Andreas A1 - Eder, Christian A1 - Zeiser, Ulrike A1 - Goehnermeier, Aksel T1 - On aberration retrieval for optical microscopes in length metrology T2 - Proc. SPIE Y1 - 2023 U6 - https://doi.org/10.1117/12.2672294 VL - PC12619 SP - PC126190A ER - TY - CHAP A1 - Manley, Phillip A1 - Krüger, Jan A1 - Bodermann, Bernd A1 - Köning, Rainer A1 - Heinrich, Andreas A1 - Eder, Christian A1 - Goehnermeier, Aksel A1 - Zeiser, Ulrike A1 - Hammerschmidt, Martin A1 - Zschiedrich, Lin A1 - Schneider, Philipp-Immanuel T1 - Efficient simulation of microscopic imaging for reconstruction of nanostructures T2 - Proc. SPIE Y1 - 2023 U6 - https://doi.org/10.1117/12.2673077 VL - PC12619 SP - PC126190B ER - 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 - 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 - GEN A1 - Sekulic, Ivan A1 - Schneider, Philipp-Immanuel A1 - Hammerschmidt, Martin A1 - Burger, Sven T1 - Machine-learning driven design of metasurfaces: learn the physics and not the objective function T2 - Proc. SPIE Y1 - 2024 U6 - https://doi.org/10.1117/12.3022119 VL - PC13017 SP - PC130170X ER - TY - JOUR A1 - Krüger, Jan A1 - Manley, Phillip A1 - Bergmann, Detlef A1 - Köning, Rainer A1 - Bodermann, Bernd A1 - Eder, Christian A1 - Heinrich, Andreas A1 - Schneider, Philipp-Immanuel A1 - Hammerschmidt, Martin A1 - Zschiedrich, Lin A1 - Manske, Eberhard T1 - Introduction and application of a new approach for model-based optical bidirectional measurements JF - Meas. Sci. Technol. Y1 - 2024 U6 - https://doi.org/10.1088/1361-6501/ad4b53 VL - 35 SP - 085014 ER - TY - JOUR A1 - Müller, Gabriel A1 - Martínez-Lahuerta, Victor J. A1 - Sekulic, Ivan A1 - Burger, Sven A1 - Schneider, Philipp-Immanuel A1 - Gaaloul, Naceur T1 - Bayesian optimization for state engineering of quantum gases JF - Quantum Sci. Technol. Y1 - 2025 U6 - https://doi.org/10.1088/2058-9565/ad9050 VL - 10 SP - 015033 ER - TY - JOUR A1 - Schaible, Jonas A1 - Winarto, Hanifah A1 - Škorjanc, Viktor A1 - Yoo, Danbi A1 - Zimmermann, Lea A1 - Jäger, Klaus A1 - Sekulic, Ivan A1 - Schneider, Philipp‐Immanuel A1 - Burger, Sven A1 - Wessels, Andreas A1 - Bläsi, Benedikt A1 - Becker, Christiane T1 - Optimizing Aesthetic Appearance of Perovskite Solar Cells Using Color Filters JF - Solar RRL N2 - The significance of color aesthetics in photovoltaic (PV) modules gains importance, especially in design‐centric applications like building‐integrated PVs. Color filters based on distributed Bragg reflectors, consisting of alternating thin‐film layers of different refractive indices, can modify the appearance of standard silicon modules. This approach is also extended to optimize the color appearance of emerging PV technologies such as perovskite solar cells, which typically exhibit a less appealing gray–brownish appearance. In this contribution, perovskite solar‐cell stacks combined with MorphoColor color filters are presented. Angular‐resolved reflectance simulations based on wave optics and ray tracing with experimental data are validated, and the color appearance from various viewing angles is evaluated. Additionally, the impact of individual layers on color appearance and the maximum achievable short‐circuit current density in the perovskite solar cell is investigated. By applying Bayesian optimization, the color distance is minimized to the targeted appearance. Tailoring the bridging layers between the color filter and the perovskite solar cell is found to strongly influence the color impression due to the coherently combined color filter and perovskite solar cell. The presented color optimization concept allows to customize the aesthetics of emerging PV thin‐film technologies such as perovskite solar cells. Y1 - 2025 U6 - https://doi.org/10.1002/solr.202400627 VL - 9 SP - 2400627 PB - Wiley ER - TY - CHAP A1 - Schaible, Jonas A1 - Winarto, Hanifah A1 - Skorjanc, Victor A1 - Yoo, Danbi A1 - Zimmermann, Lea A1 - Wessels, Andreas A1 - Jäger, Klaus A1 - Sekulic, Ivan A1 - Schneider, Philipp-Immanuel A1 - Bläsi, Benedikt A1 - Burger, Sven A1 - Becker, Christiane T1 - Optimization strategies for colorful thin film solar cells T2 - Proc. SPIE Y1 - 2025 U6 - https://doi.org/10.1117/12.3041408 VL - PC13361 SP - PC133610E ER - TY - CHAP A1 - Kuen, Lilli A1 - Betz, Fridtjof A1 - Binkowski, Felix A1 - Schneider, Philipp-Immanuel A1 - Hammerschmidt, Martin A1 - Heermeier, Niels A1 - Rodt, Sven A1 - Reitzenstein, Stephan A1 - Burger, Sven T1 - Applying a Riesz-projection-based contour integral eigenvalue solver to compute resonance modes of a VCSEL T2 - Proc. SPIE Y1 - 2023 U6 - https://doi.org/10.1117/12.2665490 VL - 12575 SP - 125750J 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 - CHAP A1 - Sekulic, Ivan A1 - Schneider, Philipp-Immanuel A1 - Hammerschmidt, Martin A1 - Schaible, Jonas A1 - Burger, Sven T1 - Physics informed Bayesian optimization for inverse design of diffractive optical elements T2 - Proc. SPIE Y1 - 2025 U6 - https://doi.org/10.1117/12.3064372 VL - PC13573 SP - PC135730R 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 -