Towards asteroseismology of neutron stars with physics-informed neural networks
Fuente:
arXiv
Saved in:
| Main Authors: | , , |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1866918212897079296 |
|---|---|
| author | Tseneklidou, Dimitra Torres-Forne, Alejandro Cerda-Duran, Pablo |
| author_facet | Tseneklidou, Dimitra Torres-Forne, Alejandro Cerda-Duran, Pablo |
| contents | The study of the gravitational wave signatures of neutron star oscillations may provide important information of their interior structure and Equation of State (EoS) at high densities. We present a novel technique based on physically informed neural networks (PINNs) to solve the eigenvalue problem associated with normal oscillation modes of neutron stars. The procedure is tested in a simplified scenario, with an analytical solution, that can be used to test the performance and the accuracy of the method. We show that it is possible to get accurate results of both the eigenfrequencies and the eigenfunctions with this scheme. The flexibility of the method and its capability of adapting to complex scenarios may serve in the future as a path to include more physics into these systems. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2504_12183 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Towards asteroseismology of neutron stars with physics-informed neural networks Tseneklidou, Dimitra Torres-Forne, Alejandro Cerda-Duran, Pablo High Energy Astrophysical Phenomena General Relativity and Quantum Cosmology The study of the gravitational wave signatures of neutron star oscillations may provide important information of their interior structure and Equation of State (EoS) at high densities. We present a novel technique based on physically informed neural networks (PINNs) to solve the eigenvalue problem associated with normal oscillation modes of neutron stars. The procedure is tested in a simplified scenario, with an analytical solution, that can be used to test the performance and the accuracy of the method. We show that it is possible to get accurate results of both the eigenfrequencies and the eigenfunctions with this scheme. The flexibility of the method and its capability of adapting to complex scenarios may serve in the future as a path to include more physics into these systems. |
| title | Towards asteroseismology of neutron stars with physics-informed neural networks |
| topic | High Energy Astrophysical Phenomena General Relativity and Quantum Cosmology |
| url | https://arxiv.org/abs/2504.12183 |