Quantum Speedup for Network Coordination via Fourier Sparsity

TL;DR

This paper introduces the Fourier Network Coordination problem, demonstrating quantum algorithms can achieve super-exponential speedups over classical methods for certain non-abelian group structures, with implications for complex network tasks.

Contribution

The paper formalizes Fourier-NC, analyzes quantum-classical complexity gaps, and identifies a structural invariant dictating the quantum advantage in network coordination problems.

Findings

Quantum algorithms outperform classical in symmetric group cases.

Identifies a structural invariant lpha(G) that governs quantum speedup.

Classifies complexity regimes based on group structure.

Abstract

Network coordination - synchronising traffic signals, scheduling trains, assigning communication slots requires minimising pairwise costs across coupled systems. These problems are NP-hard yet share a common Fourier-sparse structure exploitable by quantum algorithms. We introduce the Fourier Network Coordination problem (Fourier-NC),unifying eight application domains. For abelian and dihedral groups, classical sparse Fourier transforms match quantum in the same oracle model, limiting the advantage to at most polynomial. The genuine separation emerges for the symmetric group Sk: a conditional super-exponential speedup of k! -> poly(k) for class-function costs with non-trivial minimisers. When the minimising conjugacy class is structurally determined, the problem lies in NP (int) BQP and is conditionally outside P (Corollary 6.5), placing it in the intermediate complexity regime alongside integer factorisation and graph isomorphism. We formalise the abelian index \alpha(G) = [G : Amax] as the structural invariant governing the quantum-classical gap and identify a three-regime complexity trichotomy: abelian ({\alpha = 1, classical sFFT suffices), nearly abelian (\alpha= dmax, polynomial advantage), and strongly non-abelian (\alpha>>dmax, super-exponential advantage).