Get Started with Quantum Computing#
Learn to submit problems directly to quantum processing units (QPU) in the Leap quantum cloud service.
What quantum annealing is and how it works.
The gate-model architecture for quantum computing.
How quantum computers are used to solve problems.
Classical solvers for developing code.
Introduction to Ocean software’s quantum solvers.
Modeling problems as QUBOs and Ising Models.
Mapping arbitrary problems to QPU topology.
Introduction to setting QPU parameters.
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)