Improved success probability with greater circuit depth for the quantum approximate optimization algorithm
Quantum Physics
2020-09-09 v2 Mesoscale and Nanoscale Physics
Superconductivity
Abstract
Present-day, noisy, small or intermediate-scale quantum processors---although far from fault-tolerant---support the execution of heuristic quantum algorithms, which might enable a quantum advantage, for example, when applied to combinatorial optimization problems. On small-scale quantum processors, validations of such algorithms serve as important technology demonstrators. We implement the quantum approximate optimization algorithm (QAOA) on our hardware platform, consisting of two superconducting transmon qubits and one parametrically modulated coupler. We solve small instances of the NP-complete exact-cover problem, with 96.6% success probability, by iterating the algorithm up to level two.
Cite
@article{arxiv.1912.10495,
title = {Improved success probability with greater circuit depth for the quantum approximate optimization algorithm},
author = {Andreas Bengtsson and Pontus Vikstål and Christopher Warren and Marika Svensson and Xiu Gu and Anton Frisk Kockum and Philip Krantz and Christian Križan and Daryoush Shiri and Ida-Maria Svensson and Giovanna Tancredi and Göran Johansson and Per Delsing and Giulia Ferrini and Jonas Bylander},
journal= {arXiv preprint arXiv:1912.10495},
year = {2020}
}
Comments
9 pages, 7 figures