Physics – Condensed Matter – Disordered Systems and Neural Networks
Scientific paper
2006-03-10
J. Stat. Mech. P04005 (2006)
Physics
Condensed Matter
Disordered Systems and Neural Networks
7 pages, 5 figures, 3 tables
Scientific paper
10.1088/1742-5468/2006/04/P04005
We propose a simple and general procedure based on a recently introduced approach that uses an importance-sampling Monte Carlo algorithm in the disorder to probe to high precision the tails of ground-state energy distributions of disordered systems. Our approach requires an estimate of the ground-state energy distribution as a guiding function which can be obtained from simple-sampling simulations. In order to illustrate the algorithm, we compute the ground-state energy distribution of the Sherrington-Kirkpatrick mean-field Ising spin glass to eighteen orders of magnitude. We find that the ground-state energy distribution in the thermodynamic limit is well fitted by a modified Gumbel distribution as previously predicted, but with a value of the slope parameter m which is clearly larger than 6 and of the order 11.
Hartmann Alexander K.
Katzgraber Helmut G.
Koerner Mathias
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