QPU Hardware and Properties

Technical details on the QPU hardware and features.

QPU Solver Properties

Properties that characterize behaviors and features of QPU solvers.

QPU Solver Properties

Annealing Implementation and Controls

How quantum annealing is implemented and features to control it.

Annealing Implementation and Controls

Topologies

Layout of the QPU.

Topologies

Operation and Timing

Computation process of D-Wave quantum computers.

Operation and Timing

Errors and Error Correction

Errors sources and correction.

Errors and Error 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)