REGRID-QAOA: A Resource-Efficient Graph-Reduced Hybrid QAOA Framework for Physics-Constrained Power System Islanding
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Quantum Physics arXiv:2606.15083 (quant-ph) [Submitted on 13 Jun 2026] Title:REGRID-QAOA: A Resource-Efficient Graph-Reduced Hybrid QAOA Framework for Physics-Constrained Power System Islanding Authors:Yuqi Jiang, Yuqi Zhang, Zhiding Liang, Qiang Guan, Yan Li, Ganesh Kumar Venayagamoorthy View a PDF of the paper titled REGRID-QAOA: A Resource-Efficient Graph-Reduced Hybrid QAOA Framework for Physics-Constrained Power System Islanding, by Yuqi Jiang and 5 other authors View PDF HTML (experimental) Abstract:Quantum computing has rapidly emerged as a powerful paradigm for tackling computationally demanding problems. In particular, quantum optimization shows strong promise for hard combinatorial problems in power systems, where increasing distributed energy penetration heightens the need for intentional islanding to maintain grid reliability and resilience. However, power system islanding is an NP-hard combinatorial optimization problem that becomes computationally prohibitive for classical solvers as network size grows, motivating the use of quantum computing as a promising alternative pipeline. This study develops a resource-efficient hybrid QAOA islanding framework that brings physics-constrained power-system partitioning into the quantum optimization workflow. The framework combines coherency-informed graph reduction, physics-aware constraint modeling, and structured post-processing to efficiently convert shallow-circuit QAOA samples into high-quality feasible islanding decisions without deep circuits or large shot budgets. The proposed framework is validated on the standard IEEE benchmark systems (9-, 14-, 24-, 30-, 39-, and 57-bus), demonstrating that the hybrid workflow achieves Gurobi-optimal solution quality with a clear quantum resource advantage over vanilla QAOA, while the resulting islanding solutions satisfy all physical feasibility requirements after network separation. This study establishes QAOA-based islanding as a viable quantum approach for critical infrastructure, with structured post-processing as the key enabler of quantum resource efficiency. Subjects: Quantum Physics (quant-ph); Systems and Control (eess.SY) Cite as: arXiv:2606.15083 [quant-ph] (or arXiv:2606.15083v1 [quant-ph] for this version) https://doi.org/10.48550/arXiv.2606.15083 Focus to learn more arXiv-issued DOI via DataCite (pending registration) Submission history From: Yuqi Jiang [view email] [v1] Sat, 13 Jun 2026 03:30:50 UTC (19,021 KB) Full-text links: Access Paper: View a PDF of the paper titled REGRID-QAOA: A Resource-Efficient Graph-Reduced Hybrid QAOA Framework for Physics-Constrained Power System Islanding, by Yuqi Jiang and 5 other authorsView PDFHTML (experimental)TeX Source view license Current browse context: quant-ph new | recent | 2026-06 Change to browse by: cs cs.SY eess eess.SY References & Citations INSPIRE HEP NASA ADSGoogle Scholar Semantic Scholar export BibTeX citation Loading... BibTeX formatted citation × loading... Data provided by: Bookmark Bibliographic Tools Bibliographic and Citation Tools Bibliographic Explorer Toggle Bibliographic Explorer (What is the Explorer?) Connected Papers Toggle Connected Papers (What is Connected Papers?) Litmaps Toggle Litmaps (What is Litmaps?) scite.ai Toggle scite Smart Citations (What are Smart Citations?) Code, Data, Media Code, Data and Media Associated with this Article alphaXiv Toggle alphaXiv (What is alphaXiv?) Links to Code Toggle CatalyzeX Code Finder for Papers (What is CatalyzeX?) DagsHub Toggle DagsHub (What is DagsHub?) GotitPub Toggle Gotit.pub (What is GotitPub?) Huggingface Toggle Hugging Face (What is Huggingface?) ScienceCast Toggle ScienceCast (What is ScienceCast?) Demos Demos Replicate Toggle Replicate (What is Replicate?) Spaces Toggle Hugging Face Spaces (What is Spaces?) Spaces Toggle TXYZ.AI (What is TXYZ.AI?) Related Papers Recommenders and Search Tools Link to Influence Flower Influence Flower (What are Influence Flowers?) Core recommender toggle CORE Recommender (What is CORE?) Author Venue Institution Topic About arXivLabs arXivLabs: experimental projects with community collaborators arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website. Both individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy. arXiv is committed to these values and only works with partners that adhere to them. Have an idea for a project that will add value for arXiv's community? Learn more about arXivLabs. Which authors of this paper are endorsers? | Disable MathJax (What is MathJax?)