QPU Hardware and Properties

Technical details on the QPU hardware and features.

QPU Solver Properties

Properties that characterize behaviors and features of QPU solvers.

Annealing Implementation and Controls

How quantum annealing is implemented and features to control it.

Topologies

Layout of the QPU.

Operation and Timing

Computation process of D-Wave quantum computers.

Errors and Error Correction

Errors sources and correction.

Example

The following code solves the known “minimum vertex cover” graph problem using an annealing quantum computer.

>>> import networkx as nx
>>> import dwave_networkx as dnx
>>> from dwave.system import DWaveSampler, EmbeddingComposite
...
>>> s5 = nx.star_graph(4)
>>> sampler = EmbeddingComposite(DWaveSampler())
>>> min_cover = dnx.min_vertex_cover(s5, sampler)