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Off-equilibrium response function in the one-dimensional random-field Ising model.

F Corberi1, A de Candia, E Lippiello

  • 1Istituto Nazionale di Fisica della Materia, Unità di Salerno and Dipartimento di Fisica E. Caianiello, Università di Salerno, 84081 Baronissi, Salerno, Italy. corberi@na.infn.it

Physical Review. E, Statistical, Nonlinear, and Soft Matter Physics
|May 15, 2002
PubMed
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This study numerically investigates slow dynamics in the 1D random-field Ising model. It reveals crossovers between pure and Sinai regimes for domain size and magnetization, with vanishing response functions in the asymptotic limit.

Area of Science:

  • Statistical Mechanics
  • Condensed Matter Physics
  • Computational Physics

Background:

  • The random-field Ising model describes systems with quenched disorder.
  • Understanding slow dynamics is crucial for characterizing phase transitions and equilibrium properties.
  • Infinite ferromagnetic coupling simplifies the model, focusing on disorder effects.

Purpose of the Study:

  • To numerically investigate the slow dynamics of the d=1 random-field Ising model.
  • To analyze crossovers between preasymptotic (pure) and asymptotic (Sinai) regimes.
  • To examine the linear off-equilibrium response function.

Main Methods:

  • Thorough numerical simulations.
  • Analysis of average domain size, autocorrelation function, and staggered magnetization.

Related Experiment Videos

  • Perturbation by an additional small random field at time t(w).

    • Main Results:

    • Observed crossovers from pure to Sinai regimes for key dynamic quantities.
    • The linear off-equilibrium response function exhibits similar crossover behavior.
    • The response function vanishes identically in the asymptotic regime.

    Conclusions:

    • The study elucidates the crossover phenomena in the slow dynamics of the 1D random-field Ising model.
    • Numerical results highlight the transition from non-trivial pure Ising model behavior to vanishing asymptotic dynamics.
    • The findings contribute to a deeper understanding of disordered systems far from equilibrium.