slackbuilds/academic/dwave-neal/README

  An implementation of a simulated annealing sampler.

  A simulated annealing sampler can be used for approximate Boltzmann
sampling or heuristic optimization. This implementation approaches
the equilibrium distribution by performing updates at a sequence of
increasing beta values, beta_schedule, terminating at the target
beta. Each spin is updated once in a fixed order per point in the
beta_schedule according to a Metropolis- Hastings update. When beta
is large the target distribution concentrates, at equilibrium,
over ground states of the model. Samples are guaranteed to match
the equilibrium for long 'smooth' beta schedules.