A PINNs approach for the computation of eigenvalues in elliptic problems
Numerical Analysis
2026-03-04 v2 Numerical Analysis
Analysis of PDEs
Abstract
In this paper, we propose a method for computing eigenvalues of elliptic problems using Deep Learning techniques. A key feature of our approach is that it is independent of the space dimension and can compute arbitrary eigenvalues without requiring the prior computation of lower ones. Moreover, the method can be easily adapted to handle nonlinear eigenvalue problems.
Cite
@article{arxiv.2507.03126,
title = {A PINNs approach for the computation of eigenvalues in elliptic problems},
author = {Julian Fernandez Bonder and Ariel M. Salort},
journal= {arXiv preprint arXiv:2507.03126},
year = {2026}
}
Comments
7 pages, 12 figures. Submitted