Correlation Geometry of Quantum Sensor Networks: Local-Global Information Flow and Local Privacy

Quantum Physics arXiv:2608.06888 (quant-ph) [Submitted on 7 Aug 2026] Title:Correlation Geometry of Quantum Sensor Networks: Local-Global Information Flow and Local Privacy Authors:Gong-Chu Li, Lei Chen, Xu-Song Hong, Hua-Qing Xu, Yuancheng Liu, Si-Qi Zhang, Jia-Hao Zhao, Geng Chen, Chuan-Feng Li, Guang-Can Guo View a PDF of the paper titled Correlation Geometry of Quantum Sensor Networks: Local-Global Information Flow and Local Privacy, by Gong-Chu Li and 8 other authors View PDF HTML (experimental) Abstract:Quantum sensor networks typically encode N unknown parameters while targeting a single linear combination, rendering the N-1 remaining parameters as nuisance directions. To rigorously quantify estimation precision under such nuisances, we introduce the concept of effective quantum Fisher information (EQFI) and develop an exact EQFI-based phase map that systematically describes the allocation between local and global EQFI. Leveraging this geometric framework, we identify a fundamental bottleneck termed the "barrel effect": the global EQFI is strictly bounded by the weakest weighted local sensing capacity among all nodes. We further establish concrete conditions for saturating this bound. Crucially, this geometric map delineates how the trade-off between local and global EQFI depends dynamically on quantum correlations, and uncovers a counterintuitive "overcorrelated" regime where excessive correlations actively degrade both local and global performance. Finally, we apply the phase map to intrinsic local privacy and identify the condition under which every local parameter is inaccessible while the desired global combination remains estimable. Overall, our work provides a principled methodology for engineering optimal network states in quantum sensing architectures. Comments: Subjects: Quantum Physics (quant-ph) Cite as: arXiv:2608.06888 [quant-ph] (or arXiv:2608.06888v1 [quant-ph] for this version) https://doi.org/10.48550/arXiv.2608.06888 Focus to learn more arXiv-issued DOI via DataCite (pending registration) Submission history From: Gongchu Li [view email] [v1] Fri, 7 Aug 2026 07:21:39 UTC (6,751 KB) Full-text links: Access Paper: View a PDF of the paper titled Correlation Geometry of Quantum Sensor Networks: Local-Global Information Flow and Local Privacy, by Gong-Chu Li and 8 other authorsView 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?)