English

Eigenvalue method to compute the largest relaxation time of disordered systems

Disordered Systems and Neural Networks 2010-01-03 v2

Abstract

We consider the dynamics of finite-size disordered systems as defined by a master equation satisfying detailed balance. The master equation can be mapped onto a Schr\"odinger equation in configuration space, where the quantum Hamiltonian HH has the generic form of an Anderson localization tight-binding model. The largest relaxation time teqt_{eq} governing the convergence towards Boltzmann equilibrium is determined by the lowest non-vanishing eigenvalue E1=1/teqE_1=1/t_{eq} of HH (the lowest eigenvalue being E0=0E_0=0). So the relaxation time teqt_{eq} can be computed {\it without simulating the dynamics} by any eigenvalue method able to compute the first excited energy E1E_1. Here we use the 'conjugate gradient' method to determine E1E_1 in each disordered sample and present numerical results on the statistics of the relaxation time teqt_{eq} over the disordered samples of a given size for two models : (i) for the random walk in a self-affine potential of Hurst exponent HH on a two-dimensional square of size L×LL \times L, we find the activated scaling lnteq(L)Lψ\ln t_{eq}(L) \sim L^{\psi} with ψ=H\psi=H as expected; (ii) for the dynamics of the Sherrington-Kirkpatrick spin-glass model of NN spins, we find the growth lnteq(N)Nψ\ln t_{eq}(N) \sim N^{\psi} with ψ=1/3\psi=1/3 in agreement with most previous Monte-Carlo measures. In addition, we find that the rescaled distribution of (lnteq)(\ln t_{eq}) decays as euηe^{- u^{\eta}} for large uu with a tail exponent of order η1.36\eta \simeq 1.36. We give a rare-event interpretation of this value, that points towards a sample-to-sample fluctuation exponent of order ψwidth0.26\psi_{width} \simeq 0.26 for the barrier.

Keywords

Cite

@article{arxiv.0910.4833,
  title  = {Eigenvalue method to compute the largest relaxation time of disordered systems},
  author = {Cecile Monthus and Thomas Garel},
  journal= {arXiv preprint arXiv:0910.4833},
  year   = {2010}
}

Comments

10 pages, 4 figures ; in v2, new rare-event interpretation of the tail exponent $\eta$ in relation with the sample-to-sample fluctuation exponent

R2 v1 2026-06-21T14:03:14.562Z