A PINNs approach for the computation of eigenvalues in elliptic problems
Fuente:
arXiv
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| Autores principales: | , |
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| Formato: | Preprint |
| Publicado: |
2025
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| Materias: | |
| Acceso en línea: | |
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| _version_ | 1866912937867739136 |
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| author | Bonder, Julian Fernandez Salort, Ariel M. |
| author_facet | Bonder, Julian Fernandez Salort, Ariel M. |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2507_03126 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | A PINNs approach for the computation of eigenvalues in elliptic problems Bonder, Julian Fernandez Salort, Ariel M. Numerical Analysis Analysis of PDEs 35P15, 68T07 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. |
| title | A PINNs approach for the computation of eigenvalues in elliptic problems |
| topic | Numerical Analysis Analysis of PDEs 35P15, 68T07 |
| url | https://arxiv.org/abs/2507.03126 |