English

Tailoring the overlap distribution in driven mean-field spin models

Statistical Mechanics 2024-05-15 v2 Disordered Systems and Neural Networks

Abstract

In a statistical physics context, inverse problems consist in determining microscopic interactions such that a system reaches a predefined collective state. A complex collective state may be prescribed by specifying the overlap distribution between microscopic configurations, a notion originally introduced in the context of disordered systems like spin-glasses. We show that in spite of the absence of disorder, nonequilibrium spin models exhibiting spontaneous magnetization oscillations provide a benchmark to prescribe a non-trivial overlap distribution with continuous support, qualitatively analogous to the ones found in disordered systems with full replica symmetry breaking. The overlap distribution can be explicitly tailored to take a broad range of predefined shapes by monitoring the spin dynamics. The presence of a non-trivial overlap distribution is traced back to an average over infinitely many pure states, a feature shared with spin-glasses, although the structure of pure states is here much simpler.

Keywords

Cite

@article{arxiv.2312.07453,
  title  = {Tailoring the overlap distribution in driven mean-field spin models},
  author = {Laura Guislain and Eric Bertin},
  journal= {arXiv preprint arXiv:2312.07453},
  year   = {2024}
}
R2 v1 2026-06-28T13:48:39.368Z