2 citations · 2 across the 2 of their papers we have counts for
2 papers
physics.optics2026
Physics-constrained neural networks for surrogate modeling of lossless periodic structures
Eric Prehn, Peter Jung
We introduce a physics-constrained neural network for the rapid prediction of rigorous coupled-wave analysis outputs in the form of Jones matrices. Starting from energy conservatio…
quant-ph2024★ 2 cited
Learning Density Functionals from Noisy Quantum Data
Emiel Koridon, Felix Frohnert, Eric Prehn +3
The search for useful applications of noisy intermediate-scale quantum (NISQ) devices in quantum simulation has been hindered by their intrinsic noise and the high costs associated…