  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.
