Cyclic Quantum Annealing: Searching for Deep Low-Energy States in 5000-Qubit Spin Glass

Abstract

Quantum computers promise a qualitative speedup in solving a broad spectrum of practical optimization problems. The latter can be mapped onto the task of finding low-energy states of spin glasses, which is known to be exceedingly difficult. Using D-Wave's 5000-qubit quantum processor, we demonstrate that a recently proposed iterative cyclic quantum annealing algorithm can find deep low-energy states in record time. We also find intricate structures in a low-energy landscape of spin glasses, such as a power-law distribution of connected clusters with a small surface energy. These observations offer guidance for further improvement of the optimization algorithms.

9 pages, 5 figures

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Cited by in corpus (7)

• Tricritical Kibble-Zurek scaling in Rydberg atom ladders
• Computational complexity of three-dimensional Ising spin glass: Lessons from D-Wave annealer
• Continuous-time quantum optimisation without the adiabatic principle
• Quantum Annealing with chaotic driver Hamiltonians
• Learning-Driven Annealing with Adaptive Hamiltonian Modification for Solving Large-Scale Problems on Quantum Devices
• Quantum-inspired dynamical models on quantum and classical annealers
• Quantum sequel of neural network training