Hammerstein equations for sparse random matrices
Fuente:
arXiv
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| Autori principali: | , |
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| Natura: | Preprint |
| Pubblicazione: |
2024
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| _version_ | 1866929684898381824 |
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| author | Akara-pipattana, Pawat Evnin, Oleg |
| author_facet | Akara-pipattana, Pawat Evnin, Oleg |
| contents | Finding eigenvalue distributions for a number of sparse random matrix ensembles can be reduced to solving nonlinear integral equations of the Hammerstein type. While a systematic mathematical theory of such equations exists, it has not been previously applied to sparse matrix problems. We close this gap in the literature by showing how one can employ numerical solutions of Hammerstein equations to accurately recover the spectra of adjacency matrices and Laplacians of random graphs. While our treatment focuses on random graphs for concreteness, the methodology has broad applications to more general sparse random matrices. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2410_00355 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Hammerstein equations for sparse random matrices Akara-pipattana, Pawat Evnin, Oleg Disordered Systems and Neural Networks Numerical Analysis Mathematical Physics Functional Analysis Probability Finding eigenvalue distributions for a number of sparse random matrix ensembles can be reduced to solving nonlinear integral equations of the Hammerstein type. While a systematic mathematical theory of such equations exists, it has not been previously applied to sparse matrix problems. We close this gap in the literature by showing how one can employ numerical solutions of Hammerstein equations to accurately recover the spectra of adjacency matrices and Laplacians of random graphs. While our treatment focuses on random graphs for concreteness, the methodology has broad applications to more general sparse random matrices. |
| title | Hammerstein equations for sparse random matrices |
| topic | Disordered Systems and Neural Networks Numerical Analysis Mathematical Physics Functional Analysis Probability |
| url | https://arxiv.org/abs/2410.00355 |