Equilibration times in clean and noisy systems

TL;DR

This paper investigates how equilibration times scale with system size in both clean and noisy quantum systems, revealing conditions for rapid or slow equilibration depending on system properties and noise presence.

Contribution

It provides a comprehensive analysis of equilibration times, including general bounds for clean systems, scaling near critical points, and numerical and analytical results for noisy systems.

Findings

Clean systems equilibrate in constant time for clustering states.

Near critical points, equilibration time scales as a power law with system size.

Noisy systems can exhibit exponentially large equilibration times, but some noise models still equilibrate quickly.

Abstract

We study the equilibration dynamics of closed finite quantum systems and address the question of the time needed for the system to equilibrate. In particular we focus on the scaling of the equilibration time T_{\mathrm{eq}} with the system size L . For clean systems we give general arguments predicting T_{\mathrm{eq}}=O(L^{0}) for clustering initial states, while for small quenches around a critical point we find T_{\mathrm{eq}}=O(L^{\zeta}) where \zeta is the dynamical critical exponent. We then analyze noisy systems where exponentially large time scales are known to exist. Specifically we consider the tight-binding model with diagonal impurities and give numerical evidence that in this case T_{\mathrm{eq}}\sim Be^{CL^{\psi}} where B,C, \psi are observable dependent constants. Finally, we consider another noisy system whose evolution dynamics is randomly sampled from a circular unitary ensemble. Here, we are able to prove analytically that T_{\mathrm{eq}}=O(1), thus showing that noise alone is not sufficient for slow equilibration dynamics.