2 papers
math.NA2025
Neural Network Acceleration of Iterative Methods for Nonlinear Schrödinger Eigenvalue Problems
Daniel Peterseim, Jan-F. Pietschmann, Jonas Püschel +1
We present a novel approach to accelerate iterative methods to solve nonlinear Schrödinger eigenvalue problems using neural networks. Nonlinear eigenvector problems are fundamental…
math.NA2025
Energy-Adaptive Riemannian Conjugate Gradient Method for Density Functional Theory
Daniel Peterseim, Jonas Püschel, Tatjana Stykel
This paper presents a novel Riemannian conjugate gradient method for the Kohn-Sham energy minimization problem in density functional theory (DFT), with a focus on non-metallic crys…