maximum_cut(G, sampler=None, **sampler_args)¶
Returns an approximate maximum cut.
Defines an Ising problem with ground states corresponding to a maximum cut and uses the sampler to sample from it.
A maximum cut is a subset S of the vertices of G such that the number of edges between S and the complementary subset is as large as possible.
- G (NetworkX graph) – The graph on which to find a maximum cut.
- 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.
S – A maximum cut of G.
This example uses a sampler from dimod to find a maximum cut for a graph of a Chimera unit cell created using the chimera_graph() function.
>>> import dimod ... >>> sampler = dimod.SimulatedAnnealingSampler() >>> G = dnx.chimera_graph(1, 1, 4) >>> cut = dnx.maximum_cut(G, sampler)
Samplers by their nature may not return the optimal solution. This function does not attempt to confirm the quality of the returned sample.