• Open Access

Improved Success Probability with Greater Circuit Depth for the Quantum Approximate Optimization Algorithm

Andreas Bengtsson, Pontus Vikstål, Christopher Warren, Marika Svensson, Xiu Gu, Anton Frisk Kockum, Philip Krantz, Christian Križan, Daryoush Shiri, Ida-Maria Svensson, Giovanna Tancredi, Göran Johansson, Per Delsing, Giulia Ferrini, and Jonas Bylander
Phys. Rev. Applied 14, 034010 – Published 3 September 2020

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.

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  • 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

Physics Subject Headings (PhySH)

Condensed Matter, Materials & Applied PhysicsQuantum Information, Science & Technology

Authors & Affiliations

Andreas Bengtsson1, Pontus Vikstål1, Christopher Warren1, Marika Svensson2,3, Xiu Gu1, Anton Frisk Kockum1, Philip Krantz1, Christian Križan1, Daryoush Shiri1, Ida-Maria Svensson1, Giovanna Tancredi1, Göran Johansson1, Per Delsing1, Giulia Ferrini1, and Jonas Bylander1,*

  • 1Microtechnology and Nanoscience, Chalmers University of Technology, Göteborg SE-412 96, Sweden
  • 2Computer Science and Engineering, Chalmers University of Technology, Göteborg SE-412 96, Sweden
  • 3Jeppesen, Göteborg SE-411 03, Sweden

  • *bylander@chalmers.se

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Vol. 14, Iss. 3 — September 2020

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