Learning quantum annealing

Understand

We propose and develop a new procedure, whereby a quantum system can learn to anneal to a desired ground state.

• We demonstrate successful learning to produce an entangled state for a two-qubit system, then demonstrate generalizability to larger systems.
• The amount of additional learning necessary decreases as the size of the system increases.
• Because current technologies limit measurement of the states of quantum annealing machines to determination of the average spin at each site, we then construct a "broken pathway" between the initial and desired states, at each step of which the average spins are nonzero, and show successful learning of that pathway.