Stimulated and spontaneous relaxation in glassy systems
F. Ritort
Abstract
Recent numerical simulations of a disordered system (Preprint arXiv:condmat/0307554) have shown the existence of two different relaxational processes (called stimulated and spontaneous) characterizing the relaxation observed in structural glasses. The existence of these two processes has been claimed to be at the roots of the intermittency phenomenon observed in recent experiments. Here we consider a generic system put in contact with a bath at temperature T and characterized by an adiabatic slow relaxation (i.e. by a negligible net heat flow from the system to the bath) in the aging state. We focus on a simplified scenario (termed as partial equilibration) characterized by the fact that $=0 (where only the spontaneous process is observable) and whose microscopic stochastic dynamics is ergodic when constrained to the constant energy surface. Three different effective temperatures can be defined: a) from the fluctuation-dissipation theorem (FDT), b) from a fluctuation theorem describing the statistical distribution of heat exchange events between system and bath and c) from a set of observable-dependent microcanonical relations in the aging state. In a partial equilibration scenario we show how all three temperatures coincide reinforcing the idea that a statistical (rather than thermometric) definition of a non-equilibrium temperature is physically meaningful in aging systems. These results are explicitly checked in a simple model system
Create a lesson
Related papers
Thermodynamics of Forgetting in a Bounded Hopfield Network
Andrea Lepre
On the critical value of void percolation in high dimensions
Patrick Charbonneau, Marcus Michelen
Nonequilibrium Spin-Glass Order in a Long-Range Quantum Ising Glass and Its Sensitivity to Noise
Giuseppe D'Auria, Alessandro Silva
Cell-type-specific modularity in E/I networks shapes dynamical regimes and computational capabilities
Emmanouil Giannakakis, Victor Buendía, Oleg Vinogradov et al.
Finite-width shift of the edge of chaos in deep neural networks
Arn Caesar
Neural Networks with Exciton-Polariton Waveguides
Huawen Xu, Ruiqi Bao, Lingyu Tian et al.