Assessing quantum and classical approaches to combinatorial optimization: Testing quadratic speed-ups for heuristic algorithms

Many recent investigations have concluded, based on asymptotic complexity analyses, that quantum computers could accelerate combinatorial optimization (CO) tasks relative to a purely classical computer. However, asymptotic analysis alone cannot support a credible claim of quantum advantage. Here, we highlight the challenges involved in benchmarking quantum and classical heuristics for CO, with a focus on the Sherrington-Kirkpatrick problem. Whereas hope remains that a quadratic quantum advantage is possible, our numerical analysis casts doubt on the idea that current methods exhibit any quantum advantage at all. This doubt arises because even a simple classical approach can match with quantum methods we investigated. We conclude that more careful numerical investigations are needed to evaluate the potential for quantum advantage in CO, and we give some possible future directions for such investigations.

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Journal
Physical review. A/Physical review, A
Published
2025-08-25
DOI
https://doi.org/10.1103/hm1z-z9p2
Primary Topic
Quantum Computing Algorithms and Architecture
Type
article
Field-Weighted Citation Impact
0.00

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article

Assessing quantum and classical approaches to combinatorial optimization: Testing quadratic speed-ups for heuristic algorithms

Dong An, Mauro E. S. Morales, Yuval R. Sanders, Pedro C. S. Costa
Physical review. A/Physical review, A
Quantum Computing Algorithms and Architecture
article

Assessing quantum and classical approaches to combinatorial optimization: Testing quadratic speed-ups for heuristic algorithms

Dong An, Mauro E. S. Morales, Yuval R. Sanders, Pedro C. S. Costa
article en

Abstract

Many recent investigations have concluded, based on asymptotic complexity analyses, that quantum computers could accelerate combinatorial optimization (CO) tasks relative to a purely classical computer. However, asymptotic analysis alone cannot support a credible claim of quantum advantage. Here, we highlight the challenges involved in benchmarking quantum and classical heuristics for CO, with a focus on the Sherrington-Kirkpatrick problem. Whereas hope remains that a quadratic quantum advantage is possible, our numerical analysis casts doubt on the idea that current methods exhibit any quantum advantage at all. This doubt arises because even a simple classical approach can match with quantum methods we investigated. We conclude that more careful numerical investigations are needed to evaluate the potential for quantum advantage in CO, and we give some possible future directions for such investigations.

Physical review. A/Physical review, AVol. 112(2)
University of Technology Sydney (AU), Peking University (CN), University of Maryland, College Park (US), Bose (United States) (US)
U.S. Department of Defense, NSW Defence Innovation Network
Openalex Percentile: Top 89%
Quantum Computing Algorithms and Architecture
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Assessing quantum and classical approaches to combinatorial optimization: Testing quadratic speed-ups for heuristic algorithms — Dong An, Mauro E. S. Morales, et al. · Physical review. A/Physical review, A (2025) | TGRS Research Map | TGRS