To solve a problem with the D-Wave QPU, you formulate it as an Ising model or a QUBO (Quadratic Unconstrained Binary Optimization) model. Your model, formulated as a graph, then needs to be "minor embedded" onto the D-Wave QPU's graph.

In this webinar, we introduced D-Wave's embedding algorithm (Cai, Macready and Roy, 2014), and used examples to show several ways to apply it in D-Wave's Ocean Python API. We discussed the chain strength parameter and its importance for finding optimal solutions. Finally, we mentioned several recent papers which outline extensions and improvements to the embedding algorithm.