From entropic to energetic barriers in glassy dynamics: The Barrat-Mézard trap model on sparse networks

Diego Tapias, Eva Paprotzki, Peter Sollich

Research output: Contribution to journalArticlepeer-review

5 Citations (Scopus)
37 Downloads (Pure)

Abstract

Trap models describe glassy dynamics as a stochastic process on a network of configurations representing local energy minima. We study within this class the paradigmatic Barrat–Mézard model, which has Glauber transition rates. Our focus is on the effects of the network connectivity, where we go beyond the usual mean field (fully connected) approximation and consider sparse networks, specifically random regular graphs (RRG). We obtain the spectral density of relaxation rates of the master operator using the cavity method, revealing very rich behaviour as a function of network connectivity c and temperature T. We trace this back to a crossover from initially entropic barriers, resulting from a paucity of downhill directions, to energy barriers that govern the escape from local minima at long times. The insights gained are used to rationalize the relaxation of the energy after a quench from high T, as well as the corresponding correlation and persistence functions.

Original languageEnglish
Article number093302
JournalJournal of Statistical Mechanics: Theory and Experiment
Volume2020
Issue number9
DOIs
Publication statusPublished - 23 Sept 2020

Keywords

  • Ageing
  • Cavity and replica method
  • Energy landscapes
  • Glassy dynamics
  • Slow relaxation

Fingerprint

Dive into the research topics of 'From entropic to energetic barriers in glassy dynamics: The Barrat-Mézard trap model on sparse networks'. Together they form a unique fingerprint.

Cite this