Graph-Aware Exact Branch-and-Bound with Device Profiles for Static Qubit Allocation

Quantum Physics arXiv:2608.04058 (quant-ph) [Submitted on 4 Aug 2026] Title:Graph-Aware Exact Branch-and-Bound with Device Profiles for Static Qubit Allocation Authors:Kamer Kaya View a PDF of the paper titled Graph-Aware Exact Branch-and-Bound with Device Profiles for Static Qubit Allocation, by Kamer Kaya View PDF HTML (experimental) Abstract:Static qubit allocation maps a circuit's logical qubits to a sparse physical device while minimising an interaction-weighted physical-distance cost function, yielding a rectangular quadratic assignment problem. Existing work combines strong lower bounds with distributed branch-and-bound. We integrate graph-aware exact reductions with an engineering bundle for a lightweight assignment-bound path: unavoidable assigned-cost filtering, incrementally maintained root-orbit and prefix-stabilizer symmetry pruning, conditioned parent-LAP screening, and circuit-independent physical device profiles. On 21 relatively easy Melbourne instances and six Boeblingen instances completed by the GLB baseline, the final single-thread configuration provides geometric-mean speedups of 2.98x and 13.27x, respectively. With 60 threads on one shared-memory server, all instances in the final Boeblingen--Cairo experiment are certified optimal within half an hour, excluding one-time device-artifact construction. These results show that graph-aware node processing and engineering the search process substantially reduce the resources required for exact allocation. Subjects: Quantum Physics (quant-ph) Cite as: arXiv:2608.04058 [quant-ph] (or arXiv:2608.04058v1 [quant-ph] for this version) https://doi.org/10.48550/arXiv.2608.04058 Focus to learn more arXiv-issued DOI via DataCite Submission history From: Kamer Kaya [view email] [v1] Tue, 4 Aug 2026 12:36:54 UTC (55 KB) Full-text links: Access Paper: View a PDF of the paper titled Graph-Aware Exact Branch-and-Bound with Device Profiles for Static Qubit Allocation, by Kamer KayaView PDFHTML (experimental)TeX Source view license Current browse context: quant-ph new | recent | 2026-08 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?)