# 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 `TabuSampler`

sampler implements the MST2 multistart tabu search algorithm
for quadratic unconstrained binary optimization (QUBO) problems
with a dimod Python wrapper.

For a description of the tabu search algorithm, see tabu search.

## Example¶

This example solves a two-variable Ising model.

```
>>> from tabu import TabuSampler
>>> response = TabuSampler().sample_ising({'a': -0.5, 'b': 1.0}, {('a', 'b'): -1})
```