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15.0 > Academic > dwave-greedy (0.2.5)

  An implementation of a steepest descent solver for binary quadratic

Steepest descent is the discrete analogue of gradient descent, but
the best move is computed using a local minimization rather rather
than computing a gradient. At each step, we determine the dimension
along which to descend based on the highest energy drop caused by a
variable flip.

Optional building mode set with environment variables:
- TESTS=yes (performs tests, requires dimod)

This requires: python3-numpy

Maintained by: William PC
Keywords: quantum,quantum annealing,binary quadratic model,binary quadratic model solvers,dwave,d-wave
ChangeLog: dwave-greedy


Source Downloads:
dwave-greedy-0.2.5.tar.gz (8805c6bfa59c9b33d1e00e713e62fb98)

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

(the SlackBuild does not include the source)

Validated for Slackware 15.0

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

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