2019/02/28 by Bingtian Ye, Francisco Machado, Christopher D. White +3
Physics and Astronomy · #Classical mechanics #Computer science #Density matrix #Dynamics (music) #Floquet theory #Model Reduction and Neural Networks #Non-equilibrium thermodynamics #Physics #Physics of Superconductivity and Magnetism #Quantum #Quantum dynamics #Quantum many-body systems #Quantum mechanics #Scale (ratio) #Statistical physics #Truncation (statistics) #cond-mat.mes-hall #cond-mat.stat-mech #cond-mat.str-el #quant-ph
paper · pdf · doi:10.1103/physrevlett.125.030601
published as Phys. Rev. Lett. 125, 030601 (2020) · 6+21 pages, 4+23 figures
openalex publication_date 2020/07/15 · arxiv created 2021/02/22 · arxiv updated 2021/02/23 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/06
A tremendous amount of recent attention has focused on characterizing the dynamical properties of periodically driven many-body systems. Here, we use a novel numerical tool termed "density matrix truncation" (DMT) to investigate the late-time dynamics of large-scale Floquet systems. We find that DMT accurately captures two essential pieces of Floquet physics, namely, prethermalization and late-time heating to infinite temperature. Moreover, by implementing a spatially inhomogeneous drive, we demonstrate that an interplay between Floquet heating and diffusive transport is crucial to understanding the system's dynamics. Finally, we show that DMT also provides a powerful method for quantitatively capturing the emergence of hydrodynamics in static (undriven) Hamiltonians; in particular, by simulating the dynamics of generic, large-scale quantum spin chains (up to L=100), we are able to directly extract the energy diffusion coefficient.