Dynamical phase transition in the activity-biased fully-connected random field Ising model: connection with glass-forming systems
Journal of Statistical Mechanics: Theory and Experiment
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Guioth, J., & Jack, R. (2021). Dynamical phase transition in the activity-biased fully-connected random field Ising model: connection with glass-forming systems. Journal of Statistical Mechanics: Theory and Experiment, 2021 (10. 103206) https://doi.org/10.1088/1742-5468/ac2895
We analyse biased ensembles of trajectories for the random-field Ising model on a fully-connected lattice, which is described exactly by mean-field theory. By coupling the activity of the system to a dynamical biasing field, we find a range of dynamical phase transitions, including spontaneous symmetry breaking into ordered states. For weak bias, the phase behaviour is controlled by extrema of the free energy, which may be local minima or saddle points. For large bias, the system tends to states of extremal activity, which may differ strongly from free energy minima. We discuss connections of these results to random first- order transition theory of glasses, which motivates an extension of the analysis to random-field Ising models where the dynamical activity is not symmetric under magnetisation reversal.
kinetic Ising models, large deviations in non-equilibrium systems, slow relaxation, glassy dynamics, ageing
Royal Society grant RP17002. ERC : EU Horizon 2020 Programme, Grant No. 740269.
European Research Council (740269)
External DOI: https://doi.org/10.1088/1742-5468/ac2895
This record's URL: https://www.repository.cam.ac.uk/handle/1810/330576
Attribution 4.0 International
Licence URL: https://creativecommons.org/licenses/by/4.0/