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This study leverages transformer-based Neural-Network Quantum States to simulate real-time dynamics in the 2D Hubbard model, successfully identifying a critical interaction threshold where ergodic relaxation breaks down. By accurately capturing long-time behavior in regimes previously inaccessible to numerical methods, the work provides a robust framework for probing nonequilibrium phenomena in strongly correlated fermionic systems. The findings offer significant insights for researchers investigating high-temperature superconductivity and the fundamental limits of thermalization in quantum many-body physics.
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Breakdown of Thermalization from Real-Time Dynamics in the Two-Dimensional Hubbard Model

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arXiv:2606.05293v1 Announce Type: cross Abstract: Thermalization in strongly correlated fermionic systems remains a central open problem in quantum many-body physics. In this work, we investigate the real-time dynamics and the approach to thermalization in the two-dimensional Hubbard model, a paradigmatic framework for correlated electrons, relevant to high-temperature superconductivity and ultracold quantum simulation. Focusing on the half-filled square lattice, we monitor the time evolution of the double occupancy following a quench in the on-site interaction $U$, and assess whether its long-time value is captured by a canonical thermal ensemble. We employ time-dependent variational Monte Carlo methods combined with transformer-based Neural-Network Quantum States to accurately describe the nonequilibrium dynamics of fermions, especially for the behavior at long times, thereby accessing regimes that were previously inaccessible to numerical simulations. Our results reveal two distinct dynamical behaviors: for weak to intermediate interactions, the long-time double occupancy agrees with the thermal prediction, consistent with ergodic relaxation; beyond a critical interaction $U_{C}$, the dynamics deviate markedly from the thermal expectation, revealing clear signatures of thermalization breaking. These results establish numerical simulation as a powerful tool to probe nonequilibrium quantum phenomena in correlated fermionic matter.

Abstract:Thermalization in strongly correlated fermionic systems remains a central open problem in quantum many-body physics. In this work, we investigate the real-time dynamics and the approach to thermalization in the two-dimensional Hubbard model, a paradigmatic framework for correlated electrons, relevant to high-temperature superconductivity and ultracold quantum simulation. Focusing on the half-filled square lattice, we monitor the time evolution of the double occupancy following a quench in the on-site interaction $U$, and assess whether its long-time value is captured by a canonical thermal ensemble. We employ time-dependent variational Monte Carlo methods combined with transformer-based Neural-Network Quantum States to accurately describe the nonequilibrium dynamics of fermions, especially for the behavior at long times, thereby accessing regimes that were previously inaccessible to numerical simulations. Our results reveal two distinct dynamical behaviors: for weak to intermediate interactions, the long-time double occupancy agrees with the thermal prediction, consistent with ergodic relaxation; beyond a critical interaction $U_{C}$, the dynamics deviate markedly from the thermal expectation, revealing clear signatures of thermalization breaking. These results establish numerical simulation as a powerful tool to probe nonequilibrium quantum phenomena in correlated fermionic matter.

Strongly Correlated Electrons (cond-mat.str-el); Disordered Systems and Neural Networks (cond-mat.dis-nn); Quantum Physics (quant-ph)

arXiv:2606.05293 [cond-mat.str-el]

(or arXiv:2606.05293v1 [cond-mat.str-el] for this version)

https://doi.org/10.48550/arXiv.2606.05293 Focus to learn more arXiv-issued DOI via DataCite (pending registration)

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