dwave_networkx.maximum_independent_set¶

maximum_independent_set
(G, sampler=None, lagrange=2.0, **sampler_args)[source]¶ Returns an approximate maximum independent set.
Defines a QUBO with ground states corresponding to a maximum independent set and uses the sampler to sample from it.
An independent set is a set of nodes such that the subgraph of G induced by these nodes contains no edges. A maximum independent set is an independent set of largest possible size.
 Parameters
G (NetworkX graph) – The graph on which to find a maximum cut independent set.
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.
lagrange (optional (default 2)) – Lagrange parameter to weight constraints (no edges within set) versus objective (largest set possible).
sampler_args – Additional keyword parameters are passed to the sampler.
 Returns
indep_nodes – List of nodes that form a maximum independent set, as determined by the given sampler.
 Return type
Example
This example uses a sampler from dimod to find a maximum independent set 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) >>> indep_nodes = dnx.maximum_independent_set(G, sampler)
Notes
Samplers by their nature may not return the optimal solution. This function does not attempt to confirm the quality of the returned sample.
References
 AL
Lucas, A. (2014). Ising formulations of many NP problems. Frontiers in Physics, Volume 2, Article 5.