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.

Model Construction (Quadratic Models)

Constructing quadratic models.

Model Construction (Nonlinear Models)

Constructing nonlinear models.

Sampling with Hybrid Solvers

Hybrid solvers.

Basic Hybrid Examples

Beginner-level end-to-end examples.

Example

The following code creates a constrained quadratic model (CQM) representing a knapsack problem and solves it using a quantum-classical hybrid solver in the Leap service.

>>> from dimod.generators import random_knapsack
>>> from dwave.system import LeapHybridCQMSampler
...
>>> cqm = random_knapsack(10)
>>> sampler = LeapHybridCQMSampler()        
>>> sampleset = sampler.sample_cqm(cqm,
...                                time_limit=180,
...                                label="SDK Examples - Bin Packing")