Improving Spectral Resolution from Real-time Evolution for Correlated Systems

Fuente: arXiv
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Main Authors: Tang, Ta, Jia, Chunjing, Moritz, Brian, Devereaux, Thomas P.
Format: Preprint
Published: 2025
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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