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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)
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