Two early stage inverse power-law relaxations in the far from equilibrium dynamics in semi-classical percolative composites
Somnath Bhattacharya, Partha Pratim Roy, Asok Kumar Sen

TL;DR
This paper investigates the non-equilibrium relaxation dynamics in a semi-classical percolative composite model, revealing two distinct early-stage inverse-power-law relaxations followed by exponential decay, which are richer than previously observed single power-law behaviors.
Contribution
It reports the novel observation of two early-stage inverse-power-law relaxations in a semi-classical percolative model, expanding understanding of relaxation dynamics in far-from-equilibrium systems.
Findings
Two initial power-laws observed, each lasting more than a decade
Followed by an exponential relaxation at large times
Results suggest a connection to non-extensive entropy concepts
Abstract
In several experiments for measuring various classes of responses, performed at least some four decades ago, on driven physical systems in a far-from-equilibrium (or, from a steady-state) situation, early stage inverse-power-law relaxation dynamics had been observed. Since then, this intriguing behavior raised its head off and on until it regained its central role in the mainstream physical sciences about a decade ago with a breakdown and/or avalanche type (also called self-organized critical) behavior of the sand-pile model and a host of other similar problems. In this communication, we report on the non-equilibrium dynamics in our Random Resistor cum Tunneling-bond Network (RRTN) model. Previously, this semi-classical, or semi-quantum percolative model has been highly successful in explaining the static behavior for various random composite systems. In our dynamic studies for the last…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsTheoretical and Computational Physics · Complex Network Analysis Techniques · Statistical Mechanics and Entropy
