Improving Spectral Resolution from Real-time Evolution for Correlated Systems
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arXiv
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| Main Authors: | , , , |
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| Format: | Preprint |
| Published: |
2025
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| _version_ | 1866915502632206336 |
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| author | Tang, Ta Jia, Chunjing Moritz, Brian Devereaux, Thomas P. |
| author_facet | Tang, Ta Jia, Chunjing Moritz, Brian Devereaux, Thomas P. |
| contents | The quality of numerically simulated spectra using real-time evolution methods for strongly correlated systems is affected by both the length of simulation time and the system size, limiting resolution in both frequency and momentum. In this work, we propose a computationally cheap, linear autoregressive machine learning-based framework to extend short-time and distance results over a wider range. We demonstrate the proposed method to extend the lesser Green's function for both the Hubbard model and the much more computationally challenging Hubbard-extended Holstein model. This technique significantly improves both the frequency and momentum resolution of the single-particle removal spectrum $\mathcal{A}(k,ω)$, allowing observation of otherwise obscured spectral features due to electron-phonon coupling. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2509_15539 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Improving Spectral Resolution from Real-time Evolution for Correlated Systems Tang, Ta Jia, Chunjing Moritz, Brian Devereaux, Thomas P. Strongly Correlated Electrons Disordered Systems and Neural Networks The quality of numerically simulated spectra using real-time evolution methods for strongly correlated systems is affected by both the length of simulation time and the system size, limiting resolution in both frequency and momentum. In this work, we propose a computationally cheap, linear autoregressive machine learning-based framework to extend short-time and distance results over a wider range. We demonstrate the proposed method to extend the lesser Green's function for both the Hubbard model and the much more computationally challenging Hubbard-extended Holstein model. This technique significantly improves both the frequency and momentum resolution of the single-particle removal spectrum $\mathcal{A}(k,ω)$, allowing observation of otherwise obscured spectral features due to electron-phonon coupling. |
| title | Improving Spectral Resolution from Real-time Evolution for Correlated Systems |
| topic | Strongly Correlated Electrons Disordered Systems and Neural Networks |
| url | https://arxiv.org/abs/2509.15539 |