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 on our hardware platform, consisting of two superconducting transmon qubits and one parametrically modulated coupler. We solve small instances of the NP (nondeterministic polynomial time)-complete exact-cover problem, with 96.6% success probability, by iterating the algorithm up to level two.
- Received 30 December 2019
- Revised 11 May 2020
- Accepted 10 August 2020
DOI:https://doi.org/10.1103/PhysRevApplied.14.034010
Published by the American Physical Society under the terms of the Creative Commons Attribution 4.0 International license. Further distribution of this work must maintain attribution to the author(s) and the published article's title, journal citation, and DOI. Funded by Bibsam.
Published by the American Physical Society