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Linear response theory for long-range interacting systems in quasistationary states

Patelli, A.
•
Gupta, S.
•
Nardini, C.
•
Ruffo, S.
2012
  • journal article

Periodico
PHYSICAL REVIEW E, STATISTICAL, NONLINEAR, AND SOFT MATTER PHYSICS
Abstract
Long-range interacting systems, while relaxing to equilibrium, often get trapped in long-lived quasistationary states which have lifetimes that diverge with the system size. In this work, we address the question of how a long-range system in a quasistationary state (QSS) responds to an external perturbation. We consider a long-range system that evolves under deterministic Hamilton dynamics. The perturbation is taken to couple to the canonical coordinates of the individual constituents. Our study is based on analyzing the Vlasov equation for the single-particle phase space distribution. The QSS represents stable stationary solution of the Vlasov equation in the absence of the external perturbation. In the presence of small perturbation, we linearize the perturbed Vlasov equation about the QSS to obtain a formal expression for the response observed in a single-particle dynamical quantity. For a QSS that is homogeneous in the coordinate, we obtain an explicit formula for the response. We apply our analysis to a paradigmatic model, the Hamiltonian mean-field model, that involves particles moving on a circle under Hamilton dynamics. Our prediction for the response of three representative QSSs in this model (the water-bag QSS, the Fermi-Dirac QSS, and the Gaussian QSS) is found to be in good agreement with N-particle simulations for large N. We also show the long-time relaxation of the water-bag QSS to the Boltzmann-Gibbs equilibrium state.
DOI
10.1103/PhysRevE.85.021133
WOS
WOS:000300671500004
Archivio
http://hdl.handle.net/20.500.11767/16720
info:eu-repo/semantics/altIdentifier/scopus/2-s2.0-84863230563
http://pre.aps.org/abstract/PRE/v85/i2/e021133
https://arxiv.org/abs/1112.1079
Diritti
closed access
Soggetti
  • Long-range interactio...

  • Quasistationary state...

  • Linear response theor...

Scopus© citazioni
21
Data di acquisizione
Jun 2, 2022
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Web of Science© citazioni
22
Data di acquisizione
Mar 20, 2024
Visualizzazioni
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Data di acquisizione
Apr 19, 2024
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