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15.0 > Academic > dwave-neal (0.5.9)

  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.

This requires: dimod, python3-wheel

Maintained by: William PC
Keywords: quantum,quantum annealing,boltzmann sampling,heuristic optimization,annealing sampler,dwave,d-wave
ChangeLog: dwave-neal


Source Downloads:
dwave-neal-0.5.9.tar.gz (f01bae63001966835a0677e8b9b07ea8)

Download SlackBuild:
dwave-neal.tar.gz.asc (FAQ)

(the SlackBuild does not include the source)

Individual Files:

Validated for Slackware 15.0

See our HOWTO for instructions on how to use the contents of this repository.

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