Physics – Condensed Matter – Disordered Systems and Neural Networks
Scientific paper
2001-08-20
Phys. Rev. B 66, 224419 (2002)
Physics
Condensed Matter
Disordered Systems and Neural Networks
9 pages, 7 figures, revtex (one sentence changed compared to v2)
Scientific paper
10.1103/PhysRevB.66.224419
A method is presented, which allows to sample directly low-temperature configurations of glassy systems, like spin glasses. The basic idea is to generate ground states and low lying excited configurations using a heuristic algorithm. Then, with the help of microcanonical Monte Carlo simulations, more configurations are found, clusters of configurations are determined and entropies evaluated. Finally equilibrium configuration are randomly sampled with proper Gibbs-Boltzmann weights. The method is applied to three-dimensional Ising spin glasses with +- J interactions and temperatures T<=0.5. The low-temperature behavior of this model is characterized by evaluating different overlap quantities, exhibiting a complex low-energy landscape for T>0, while the T=0 behavior appears to be less complex.
Hartmann Alexander K.
Ricci-Tersenghi Federico
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