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

Author:

Hao Zhang, Kelly Boothby, Alex Kamenev

Keyword:

Condensed Matter, Disordered Systems and Neural Networks, Disordered Systems and Neural Networks (cond-mat.dis-nn), Statistical Mechanics (cond-mat.stat-mech), Quantum Physics (quant-ph)

journal:

date:

2024-03-01 00:00:00

Abstract

Quantum computers promise a qualitative speedup in solving a broad spectrum of real-life 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[1] 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.

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