Cited by 19Quantum Computing Algorithms and ArchitectureComplexity and Algorithms in GraphsQuantum many-body systems

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Classical Algorithms and Quantum Limitations for Maximum Cut on High-Girth Graphs

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Barak, Boaz, Marwaha, Kunal·2022·Schloss Dagstuhl – Leibniz-Zentrum für Informatik

Abstract

We study the performance of local quantum algorithms such as the Quantum Approximate Optimization Algorithm (QAOA) for the maximum cut problem, and their relationship to that of randomized classical algorithms. 1) We prove that every (quantum or classical) one-local algorithm (where the value of a vertex only depends on its and its neighbors' state) achieves on D-regular graphs of girth > 5 a maximum cut of at most 1/2 + C/√D for C = 1/√2 ≈ 0.7071. This is the first such result showing that one-local algorithms achieve a value that is bounded away from the true optimum for random graphs, which is 1/2 + P_*/√D + o(1/√D) for P_* ≈ 0.7632 [Dembo et al., 2017]. 2) We show that there is a classical k-local algorithm that achieves a value of 1/2 + C/√D - O(1/√k) for D-regular graphs of girth > 2k+1, where C = 2/π ≈ 0.6366. This is an algorithmic version of the existential bound of [Lyons, 2017] and is related to the algorithm of [Aizenman et al., 1987] (ALR) for the Sherrington-Kirkpatrick model. This bound is better than that achieved by the one-local and two-local versions of QAOA on high-girth graphs [M. B. Hastings, 2019; Marwaha, 2021]. 3) Through computational experiments, we give evidence that the ALR algorithm achieves better performance than constant-locality QAOA for random D-regular graphs, as well as other natural instances, including graphs that do have short cycles. While our theoretical bounds require the locality and girth assumptions, our experimental work suggests that it could be possible to extend them beyond these constraints. This points at the tantalizing possibility that O(1)-local quantum maximum-cut algorithms might be pointwise dominated by polynomial-time classical algorithms, in the sense that there is a classical algorithm outputting cuts of equal or better quality on every possible instance. This is in contrast to the evidence that polynomial-time algorithms cannot simulate the probability distributions induced by local quantum algorithms.

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Metadata

Authors
Barak, B., & Marwaha, K.
Affiliations
  • Harvard University (US)
  • University of California, Berkeley (US)
Venue
Schloss Dagstuhl – Leibniz-Zentrum für Informatik
Publisher
Schloss Dagstuhl – Leibniz-Zentrum für Informatik
Published
2022
ISSN
2331-8422 (ISSN-L)
OpenAlex
W3171066440
Cited by
19
References
3
Citations by year
2025: 1 · 2024: 3 · 2023: 8 · 2022: 4
Type
posted content
Language
en
Open access
Locations
  • arXiv (Cornell University) (submittedVersion)
  • DROPS (Schloss Dagstuhl – Leibniz Center for Informatics) (submittedVersion, cc-by)
  • arXiv (Cornell University) (cc-by)
  • Leibniz international proceedings in informatics (cc-by)
Funders
  • National Science Foundation (1565264)
  • Defense Advanced Research Projects Agency (W911NF2010021)
Topics
  • Physical Sciences › Computer Science › Artificial Intelligence › Quantum Computing Algorithms and Architecture
  • Physical Sciences › Computer Science › Computational Theory and Mathematics › Complexity and Algorithms in Graphs
  • Physical Sciences › Physics and Astronomy › Atomic and Molecular Physics, and Optics › Quantum many-body systems
Keywords
MaxCut, quantum approximate optimization algorithm, d-regular graphs, Sherrington-Kirkpatrick model, quantum-classical comparison, random graphs

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