Anomalous diffusion, Localization, Aging and Sub-aging effects in trap models at very low temperature

TL;DR

This paper analyzes the dynamics of the one-dimensional symmetric trap model at very low temperatures, revealing out-of-equilibrium localization phenomena, aging effects, and extending the renormalization approach to include temperature corrections.

Contribution

It provides explicit results for observables in the zero-temperature limit, extends the renormalization method to finite temperatures, and generalizes the trap model to higher dimensions and parameters.

Findings

Diffusion front consists of two delta peaks out of equilibrium.

Aging and sub-aging exponents are explicitly derived.

Low-temperature effective model is independent of the parameter $\alpha$ in the generalized trap model.

Abstract

We study in details the dynamics of the one dimensional symmetric trap model, via a real-space renormalization procedure which becomes exact in the limit of zero temperature. In this limit, the diffusion front in each sample consists in two delta peaks, which are completely out of equilibrium with each other. The statistics of the positions and weights of these delta peaks over the samples allows to obtain explicit results for all observables in the limit $T \to 0$. We first compute disorder averages of one-time observables, such as the diffusion front, the thermal width, the localization parameters, the two-particle correlation function, and the generating function of thermal cumulants of the position. We then study aging and sub-aging effects : our approach reproduces very simply the two different aging exponents and yields explicit forms for scaling functions of the various two-time correlations. We also extend the RSRG method to include systematic corrections to the previous zero temperature procedure via a series expansion in $T$. We then consider the generalized trap model with parameter $\alpha \in [0,1]$ and obtain that the large scale effective model at low temperature does not depend on $\alpha$ in any dimension, so that the only observables sensitive to $\alpha$ are those that measure the `local persistence', such as the probability to remain exactly in the same trap during a time interval. Finally, we extend our approach at a scaling level for the trap model in $d=2$ and obtain the two relevant time scales for aging properties.