Get Started with Optimization

Learn to solve hard optimization problems using quantum-classical hybrid solvers hosted in the Leap™ quantum cloud service.

Basic Workflow: Models and Sampling

How hybrid solvers are used to solve optimization problems.

Basic Workflow: Models and Sampling

Model Construction

Constructing models.

Model Construction

Sampling with Hybrid Solvers

Hybrid solvers.

Sampling with Hybrid Solvers

Basic Hybrid Examples

Beginner-level end-to-end examples.

Basic Hybrid Examples

Example

The following code solves an illustrative traveling-salesperson problem using a quantum-classical hybrid solver in the Leap service.

>>> from dwave.optimization.generators import traveling_salesperson
>>> from dwave.system import LeapHybridNLSampler
...
>>> DISTANCE_MATRIX = [
...     [0, 656, 227, 578, 489],
...     [656, 0, 889, 141, 170],
...     [227, 889, 0, 773, 705],
...     [578, 141, 773, 0, 161],
...     [489, 170, 705, 161, 0]]
...
>>> model = traveling_salesperson(distance_matrix=DISTANCE_MATRIX)
>>> with LeapHybridNLSampler() as sampler:
...     results = sampler.sample(
...         model,
...         label='SDK Examples - TSP')