Classical shadows for sample-efficient measurements of gauge-invariant observables

Quantum Physics arXiv:2511.02904 (quant-ph) [Submitted on 4 Nov 2025] Title:Classical shadows for sample-efficient measurements of gauge-invariant observables Authors:Jacob Bringewatt, Henry Froland, Andreas Elben, Niklas Mueller View a PDF of the paper titled Classical shadows for sample-efficient measurements of gauge-invariant observables, by Jacob Bringewatt and 3 other authors View PDF HTML (experimental) Abstract:Classical shadows provide a versatile framework for estimating many properties of quantum states from repeated, randomly chosen measurements without requiring full quantum state tomography. When prior information is available, such as knowledge of symmetries of states and operators, this knowledge can be exploited to significantly improve sample efficiency. In this work, we develop three classical shadow protocols tailored to systems with local (or gauge) symmetries to enable efficient prediction of gauge-invariant observables in lattice gauge theory models which are currently at the forefront of quantum simulation efforts. For such models, our approaches can offer exponential improvements in sample complexity over symmetry-agnostic methods, albeit at the cost of increased circuit complexity. We demonstrate these trade-offs using a $\mathbb{Z}_2$ lattice gauge theory, where a dual formulation enables a rigorous analysis of resource requirements, including both circuit depth and sample complexity. Comments: Subjects: Quantum Physics (quant-ph); Statistical Mechanics (cond-mat.stat-mech); High Energy Physics - Lattice (hep-lat); Nuclear Theory (nucl-th) Cite as: arXiv:2511.02904 [quant-ph] (or arXiv:2511.02904v1 [quant-ph] for this version) https://doi.org/10.48550/arXiv.2511.02904 Focus to learn more arXiv-issued DOI via DataCite (pending registration) Submission history From: Henry Froland [view email] [v1] Tue, 4 Nov 2025 19:00:01 UTC (4,087 KB) Full-text links: Access Paper: View a PDF of the paper titled Classical shadows for sample-efficient measurements of gauge-invariant observables, by Jacob Bringewatt and 3 other authorsView PDFHTML (experimental)TeX Source view license Current browse context: quant-ph new | recent | 2025-11 Change to browse by: cond-mat cond-mat.stat-mech hep-lat nucl-th 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?) Links to Code Toggle Papers with Code (What is Papers with Code?) 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?)