D-Wave Ocean tools are documented on Read the Docs. Click on a link below for the documentation for each tool (or the link in parentheses for the tool repository located at D-Wave on GitHub).
Shared API for binary quadratic samplers.
dimod provides a binary quadratic model (BQM) class that contains Ising and quadratic unconstrained binary optimization (QUBO) models used by samplers such as the D-Wave system. It also provides utilities for constructing new samplers and composed samplers.
|dwavebinarycsp (repo)||Library to construct a binary quadratic model from a constraint satisfaction problem with small constraints over binary variables.|
|dwave-cloud-client (repo)||Minimal implementation of the REST interface used to communicate with D-Wave Sampler API (SAPI) servers.|
|dwave_neal (repo)||An implementation of a simulated annealing sampler.|
Extension of NetworkX—a Python language package for exploration and analysis of networks and network algorithms—for users of D-Wave Systems.
|dwave-ocean-sdk (repo)||Installer for D-Wave’s Ocean Tools.|
Basic API for easily incorporating the D-Wave system as a sampler in the D-Wave Ocean software stack.
It includes DWaveSampler, a dimod sampler that accepts and passes system parameters such as system identification and authentication down the stack. It also includes several useful composites—layers of pre- and post-processing—that can be used with DWaveSampler to handle minor-embedding, optimize chain strength, etc.
|dwave-tabu (repo)||An implementation of the MST2 multistart tabu search algorithm for quadratic unconstrained binary optimization (QUBO) problems with a dimod Python wrapper.|
Includes a local cache for penalty models and a factory that generates penalty models using SMT solvers.
While it can be used to find minors in arbitrary graphs, it is particularly geared towards the state of the art in QA: problem graphs of a few to a few hundred variables, and hardware graphs of a few thousand qubits.
|qbsolv (repo)||A decomposing solver that finds a minimum value of a large quadratic unconstrained binary optimization (QUBO) problem by splitting it into pieces. The pieces are solved using a classical solver running the tabu algorithm. qbsolv also enables configuring a D-Wave system as the solver.|