Structured Quantum State Reconstruction via Physically Motivated Operator Selection
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Quantum Physics arXiv:2604.21272 (quant-ph) [Submitted on 23 Apr 2026] Title:Structured Quantum State Reconstruction via Physically Motivated Operator Selection Authors:Ayush Chambyal, Brijesh, Rakesh Sharma View a PDF of the paper titled Structured Quantum State Reconstruction via Physically Motivated Operator Selection, by Ayush Chambyal and 2 other authors View PDF HTML (experimental) Abstract:Quantum state tomography (QST) scales exponentially in both measurement and computational cost, making full reconstruction impractical for multi-qubit systems. Existing approaches attempt to reduce this complexity, but do not explicitly restrict the operator space based on physically relevant correlations. We develop a structured QST framework in which the density matrix is reconstructed using a restricted set of observables in a Gibbs representation.
The Structured Gibbs Quantum State Tomography (SG-QST) is built by progressively including local, nearest-neighbor, and global correlations. Benchmarking on three, four, and five-qubit. GHZ states shows that comparable fidelity can be achieved with significantly fewer parameters by restricting the operator space to physically relevant observables. These results demonstrate that physically motivated operator-space restriction enables efficient and interpretable quantum state reconstruction. Subjects: Quantum Physics (quant-ph) Cite as: arXiv:2604.21272 [quant-ph] (or arXiv:2604.21272v1 [quant-ph] for this version) https://doi.org/10.48550/arXiv.2604.21272 Focus to learn more arXiv-issued DOI via DataCite (pending registration) Submission history From: Ayush Chambyal [view email] [v1] Thu, 23 Apr 2026 04:30:39 UTC (53 KB) Full-text links: Access Paper: View a PDF of the paper titled Structured Quantum State Reconstruction via Physically Motivated Operator Selection, by Ayush Chambyal and 2 other authorsView PDFHTML (experimental)TeX Source view license Current browse context: quant-ph new | recent | 2026-04 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?)