Get Started with Quantum Computing

Learn to submit problems directly to quantum processing units (QPU) in the Leap quantum cloud service.

What is Quantum Annealing?

What quantum annealing is and how it works.

What is Gate Model?

The gate-model architecture for quantum computing.

Basic Workflow: Formulation and Sampling

How quantum computers are used to solve problems.

Classical Solvers

Classical solvers for developing code.

Quantum Solvers

Introduction to Ocean software’s quantum solvers.

QUBOs and Ising Models

Modeling problems as QUBOs and Ising Models.

Minor Embedding

Mapping arbitrary problems to QPU topology.

Basic QPU Configuration

Introduction to setting QPU parameters.

Basic QPU Examples

Beginner-level end-to-end examples.

Example

The following code solves the known “minimum vertex cover” graph problem using an annealing quantum computer.

>>> import networkx as nx
>>> import dwave_networkx as dnx
>>> from dwave.system import DWaveSampler, EmbeddingComposite
...
>>> s5 = nx.star_graph(4)
>>> sampler = EmbeddingComposite(DWaveSampler())
>>> min_cover = dnx.min_vertex_cover(s5, sampler)