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.