Introduction

Samplers are processes that sample from low energy states of a problem’s objective function. A binary quadratic model (BQM) sampler samples from low energy states in models such as those defined by an Ising equation or a Quadratic Unconstrained Binary Optimization (QUBO) problem and returns an iterable of samples, in order of increasing energy. A dimod sampler provides ‘sample_qubo’ and ‘sample_ising’ methods as well as the generic BQM sampler method.

The SimulatedAnnealingSampler sampler implements the simulated annealing algorithm, based on the technique of cooling metal from a high temperature to improve its structure (annealing). This algorithm often finds good solutions to hard optimization problems.