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This research establishes the first natural distributed quantum advantage in the LOCAL model, proving that specific graph problems like maximal independent sets can be solved in constant time on quantum networks versus logarithmic time classically. By moving beyond artificial benchmarks to practical network protocols such as 3-coloring cycles, this work bridges theoretical complexity with potential applications in decentralized quantum systems.
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Quantum Advantage for Distributed Symmetry Breaking

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arXiv:2609.26788v1 Announce Type: new Abstract: We present a distributed quantum algorithm that $3$-colors cycles in $O(1)$ rounds, with high probability. It follows that all locally checkable labeling problems (LCLs) that have round complexity $O(\log^* n)$ in the classical LOCAL model can be solved in $O(1)$ rounds in the quantum-LOCAL model, with high probability; this includes problems such as maximal independent set and maximal matching in bounded-degree graphs. This presents the first natural examples of graph problems with an asymptotic distributed quantum advantage for the LOCAL model; all prior examples that separate LOCAL and quantum-LOCAL are artificial problems constructed merely for the sake of demonstrating quantum advantage.

Abstract:We present a distributed quantum algorithm that $3$-colors cycles in $O(1)$ rounds, with high probability. It follows that all locally checkable labeling problems (LCLs) that have round complexity $O(\log^* n)$ in the classical LOCAL model can be solved in $O(1)$ rounds in the quantum-LOCAL model, with high probability; this includes problems such as maximal independent set and maximal matching in bounded-degree graphs. This presents the first natural examples of graph problems with an asymptotic distributed quantum advantage for the LOCAL model; all prior examples that separate LOCAL and quantum-LOCAL are artificial problems constructed merely for the sake of demonstrating quantum advantage.

Quantum Physics (quant-ph); Distributed, Parallel, and Cluster Computing (cs.DC)

arXiv:2609.26788 [quant-ph]

(or arXiv:2609.26788v1 [quant-ph] for this version)

https://doi.org/10.48550/arXiv.2609.26788 Focus to learn more arXiv-issued DOI via DataCite (pending registration)

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