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15.0 > Academic > dwave-greedy (0.2.5)

  An implementation of a steepest descent solver for binary quadratic
models.

  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