Deep learning optimal quantum annealing schedules for random Ising models
Deep learning optimal quantum annealing schedules for random Ising models
Abstract A crucial step in the race towards quantum advantage is optimizing quantum annealing using ad-hoc annealing schedules. Motivated by recent progress in the field, we propose to employ long-short term memory neural networks to automate the search for optimal annealing schedules for random Ising models on regular graphs. By …