aiqbench analysis
This research introduces QIPS, a method leveraging localized quantum interference patterns to generate efficient proposal distributions for combinatorial optimization problems like QUBO/Ising models. By combining fixed-depth gate-based circuits with classical scoring and frontier updates, the approach demonstrates competitive performance against matched classical controls across various benchmark families without requiring exponential scaling of proposals relative to problem size. The study establishes localized quantum interference as a resource-efficient mechanism specifically for computational quantum optimization tasks.
Quantum Interference as a Proposal Mechanism for Combinatorial Optimization
arXiv:2607.27509v1 Announce Type: new Abstract: Quantum Interference Proposal Search (QIPS) uses seed-conditioned quantum circuits to generate localized interference patterns as finite-shot proposal distributions for QUBO/Ising optimization. Candidate $n_b$-bit strings are sampled from these distributions, scored classically and used to update an elite frontier of low-energy solutions. QIPS uses a fixed two-layer gate-based circuit architecture with 100 shots per circuit while the Hilbert-space dimension grows as $2^{n_b}$. Across six benchmark families with $18 \le n_b \le 29$, QIPS maintains competitive progress relative to a matched classical control that preserves the same search loop, frontier update rule and proposal budget, with total proposals proportional to $n_b$. Performance is assessed using top-$K$ coverage, hit rate, multiplicity, Hilbert-space coverage and dyadic-rank metrics. The results identify localized quantum interference as a resource-efficient proposal mechanism for computational quantum optimization.
Abstract:Quantum Interference Proposal Search (QIPS) uses seed-conditioned quantum circuits to generate localized interference patterns as finite-shot proposal distributions for QUBO/Ising optimization. Candidate $n_b$-bit strings are sampled from these distributions, scored classically and used to update an elite frontier of low-energy solutions. QIPS uses a fixed two-layer gate-based circuit architecture with 100 shots per circuit while the Hilbert-space dimension grows as $2^{n_b}$. Across six benchmark families with $18 \le n_b \le 29$, QIPS maintains competitive progress relative to a matched classical control that preserves the same search loop, frontier update rule and proposal budget, with total proposals proportional to $n_b$. Performance is assessed using top-$K$ coverage, hit rate, multiplicity, Hilbert-space coverage and dyadic-rank metrics. The results identify localized quantum interference as a resource-efficient proposal mechanism for computational quantum optimization.
arXiv:2607.27509 [quant-ph]
(or arXiv:2607.27509v1 [quant-ph] for this version)
https://doi.org/10.48550/arXiv.2607.27509 Focus to learn more arXiv-issued DOI via DataCite (pending registration)
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