science/py-dwave-samplers 1.3.0_1 DragonFly

Ocean software provides a variety of quantum, classical, and quantum-classical dimod samplers that run either remotely (for example, in D-Wave's Leap environment) or locally on your CPU.

dwave-samplers implements the following classical algorithms for solving binary quadratic models (BQM): * Random: a sampler that draws uniform random samples. * Simulated Annealing: a probabilistic heuristic for optimization and approximate Boltzmann sampling well suited to finding good solutions of large problems. * Steepest Descent: a discrete analogue of gradient descent, often used in machine learning, that quickly finds a local minimum. * Tabu: a heuristic that employs local search with methods to escape local minima. * Tree Decomposition: an exact solver for problems with low treewidth.