2018/06/28 by Juan I. Adame, Peter L. McMahon, Adame, Juan I. +1 · 4 citations
Computer Science · Physics and Astronomy · #Artificial intelligence #Computer science #Condensed matter physics #FOS: Physical sciences #Ground state #Heuristic #Ising model #Parallel computing #Physics #Quantum #Quantum Computing Algorithms and Architecture #Quantum Information and Cryptography #Quantum Physics (quant-ph) #Quantum and electron transport phenomena #Quantum annealing #Quantum computer #Quantum mechanics #Speedup #Spin (aerodynamics) #Spins #Statistical physics #quant-ph
paper · pdf · doi:10.48550/arxiv.1806.11091
published in arXiv (Cornell University) (Cornell University)
openalex publication_date 2018/06/28 · arxiv created 2018/11/16 · arxiv updated 2018/11/20 · openalex created_date 2022/09/27 · openalex updated_date 2026/08/06
Quantum annealers are special-purpose quantum computers that primarily target\nsolving Ising optimization problems. Theoretical work has predicted that the\nprobability of a quantum annealer ending in a ground state can be dramatically\nimproved if the spin driving terms, which play a crucial role in the\nfunctioning of a quantum annealer, have different strengths for different\nspins; that is, they are inhomogeneous. In this paper we describe a\ntime-shift-based protocol for inhomogeneous driving and demonstrate, using an\nexperimental quantum annealer, the performance of our protocol on a range of\nhard Ising problems that have been well-studied in the literature. Compared to\nthe homogeneous-driving case, we find that we are able to increase the\nprobability of finding a ground state by up to 108 \× for some\nWeak-Strong-Cluster problem instances, and by up to 103 \× for more\ngeneral spin-glass problem instances. In addition to being of practical\ninterest as a heuristic speedup method, inhomogeneous driving may also serve as\na useful tool for investigations into the physics of experimental quantum\nannealers.\n