4 papers
Physics-Informed PointNets for Modeling Electromagnetic Scattering from All-Dielectric Metasurfaces with Inclined Nanopillars
Leon Armbruster, Vlad Medvedev, Andreas Rosskopf
Metasurfaces are innovative planar optical structures capable of manipulating incident light properties. Accurate and computationally efficient modeling of such metasurfaces, parti…
CleanQRL: Lightweight Single-file Implementations of Quantum Reinforcement Learning Algorithms
Georg Kruse, Rodrigo Coelho, Andreas Rosskopf +2
At the interception between quantum computing and machine learning, Quantum Reinforcement Learning (QRL) has emerged as a promising research field. Due to its novelty, a standardiz…
Hard-constraining Neumann boundary conditions in physics-informed neural networks via Fourier feature embeddings
Christopher Straub, Philipp Brendel, Vlad Medvedev +1
We present a novel approach to hard-constrain Neumann boundary conditions in physics-informed neural networks (PINNs) using Fourier feature embeddings. Neumann boundary conditions…
Quantum-Efficient Kernel Target Alignment
Rodrigo Coelho, Georg Kruse, Andreas Rosskopf
In recent years, quantum computers have emerged as promising candidates for implementing kernels. Quantum Embedding Kernels embed data points into quantum states and calculate thei…