Abstract:We present a classical algorithm to find approximate solutions to instances of quadratic unconstrained binary optimisation. The algorithm can be seen as an analogue of quantum annealing under the restriction of a product state space, where the dynamical evolution in quantum annealing is replaced with a gradient-descent based method. This formulation is able to quickly find highquality solutions to large-scale problem instances, and can naturally be accelerated by dedicated hardware such as graphics processing … Show more
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