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physics.optics2026
Gradient-Informed Bayesian and Interior Point Optimization for Efficient Inverse Design in Nanophotonics
Yannik Mahlau, Yannick Augenstein, Tyler W. Hughes +2
Inverse design, particularly geometric shape optimization, provides a systematic approach for developing high-performance nanophotonic devices. While numerous optimization algorith…
physics.optics2024
A flexible framework for large-scale FDTD simulations: open-source inverse design for 3D nanostructures
Yannik Mahlau, Frederik Schubert, Konrad Bethmann +5
We introduce an efficient open-source python package for the inverse design of three-dimensional photonic nanostructures using the Finite-Difference Time-Domain (FDTD) method. Leve…
physics.optics2024
Quantized Inverse Design for Photonic Integrated Circuits
Frederik Schubert, Yannik Mahlau, Konrad Bethmann +5
The inverse design of photonic integrated circuits (PICs) presents distinctive computational challenges, including their large memory requirements. Advancements in the two-photon p…