Analytic continuation from limited noisy Matsubara data
This note proposes new algorithms for estimating spectral distribution from limited noisy Matsubara data. We consider both the cases of the spectral distribution with a sparse or a continuous support. In both cases, the proposed algorithm first constructs an accurate approximation of the Matsubara d...
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| Veröffentlicht in: | Journal of computational physics Jg. 469; S. 111549 |
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| 1. Verfasser: | |
| Format: | Journal Article |
| Sprache: | Englisch |
| Veröffentlicht: |
Cambridge
Elsevier Inc
15.11.2022
Elsevier Science Ltd |
| Schlagworte: | |
| ISSN: | 0021-9991, 1090-2716 |
| Online-Zugang: | Volltext |
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| Zusammenfassung: | This note proposes new algorithms for estimating spectral distribution from limited noisy Matsubara data. We consider both the cases of the spectral distribution with a sparse or a continuous support. In both cases, the proposed algorithm first constructs an accurate approximation of the Matsubara data, uses a novel conformal map to transform the domain, and applies Prony's method to estimate the spectral distribution. Numerical results are provided to demonstrate the performance of the algorithms. |
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| Bibliographie: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 |
| ISSN: | 0021-9991 1090-2716 |
| DOI: | 10.1016/j.jcp.2022.111549 |