Yielding and memory in a driven mean-field model of glasses

TL;DR

This paper investigates a mean-field model of glasses under oscillatory forces, revealing key dynamical phenomena like yielding, hysteresis, and memory effects, which mirror behaviors observed in real glassy materials.

Contribution

It introduces a driven mean-field model that reproduces universal glass behaviors, including yielding, hysteresis, and memory formation, providing a unified theoretical framework.

Findings

Identifies an oscillatory yielding transition with hysteresis.

Demonstrates dynamic slowing-down near the transition.

Shows non-equilibrium ensemble equivalence and memory effects.

Abstract

Glassy systems reveal a wide variety of generic behaviors, which lack a unified theoretical description. Here, we study a mean-field model, recently shown to reproduce the universal non-phononic vibrational spectra of glasses, under oscillatory driving forces. The driven mean-field model, featuring a disordered Hamiltonian structure, naturally predicts the salient dynamical phenomena in cyclically deformed glasses. Specifically, it features an oscillatory yielding transition, characterized by an absorbing-to-diffusive transition in the system's microscopic trajectories and large-scale hysteresis. The model also reveals dynamic slowing-down from both sides of the transition, as well as mechanical and thermal annealing effects that mirror their glass counterparts. Finally, we demonstrate a non-equilibrium ensemble equivalence between the driven post-yielding dynamics at fixed quenched disorder and quenched disorder averages of the non-driven system, along with memory formation.