dwave_networkx.algorithms.max_cut.weighted_maximum_cut

weighted_maximum_cut(G, sampler=None, **sampler_args)

Returns an approximate weighted maximum cut.

Defines an Ising problem with ground states corresponding to a weighted maximum cut and uses the sampler to sample from it.

A weighted maximum cut is a subset S of the vertices of G that maximizes the sum of the edge weights between S and its complementary subset.

Parameters

• G (NetworkX graph) – The graph on which to find a weighted maximum cut. Each edge in G should have a numeric weight attribute.

• sampler – A binary quadratic model sampler. A sampler is a process that samples from low energy states in models defined by an Ising equation or a Quadratic Unconstrained Binary Optimization Problem (QUBO). A sampler is expected to have a ‘sample_qubo’ and ‘sample_ising’ method. A sampler is expected to return an iterable of samples, in order of increasing energy. If no sampler is provided, one must be provided using the set_default_sampler function.

• sampler_args – Additional keyword parameters are passed to the sampler.

Returns

S – A maximum cut of G.

Return type

set

Notes

Samplers by their nature may not return the optimal solution. This function does not attempt to confirm the quality of the returned sample.