High-performance Energy Minimization with Applications to Adiabatic Quantum Computing

TL;DR

This paper develops new algorithms to simulate energy minimization in Ising spin-glasses, enabling large-scale studies relevant to quantum adiabatic computing and surpassing previous limitations in topology and size.

Contribution

It introduces scalable algorithms for simulating spin-glass energy minimization, applicable to non-planar topologies and large systems, aiding quantum computing research.

Findings

Ground states found for 100 spins in one CPU-day

Approximate ground states for 1,000,000 spins

Insights into hyper-couplings in quantum adiabatic computers

Abstract

Energy minimization of Ising spin-glasses has played a central role in statistical and solid-state physics, facilitating studies of phase transitions and magnetism. Recent proposals suggest using Ising spin-glasses for non-traditional computing as a way to harness the nature's ability to find min-energy configurations, and to take advantage of quantum tunneling to boost combinatorial optimization. Laboratory demonstrations have been unconvincing so far and lack a non-quantum baseline for definitive comparisons. In this work we (i) design and evaluate new computational techniques to simulate natural energy minimization in spin glasses and (ii) explore their application to study design alternatives in quantum adiabatic computers. Unlike previous work, our algorithms are not limited to planar Ising topologies. In one CPU-day, our branch-and-bound algorithm finds ground states on 100 spins, while our local search approximates ground states on 1, 000, 000 spins. We use this computational tool as a simulator to study the significance of hyper-couplings in the context of recently implemented adiabatic quantum computers.