Interferometric Quantum Polynomial Chaos Expansion as a Generative Model for Calorimeter Shower Simulation

Quantum Physics arXiv:2608.05405 (quant-ph) [Submitted on 5 Aug 2026] Title:Interferometric Quantum Polynomial Chaos Expansion as a Generative Model for Calorimeter Shower Simulation Authors:Jamal Slim, Saverio Monaco, Florian Rehm, Dirk Kruecker, Frank Gaede, Kerstin Borras View a PDF of the paper titled Interferometric Quantum Polynomial Chaos Expansion as a Generative Model for Calorimeter Shower Simulation, by Jamal Slim and Saverio Monaco and Florian Rehm and Dirk Kruecker and Frank Gaede and Kerstin Borras View PDF Abstract:We present the quantum polynomial chaos expansion, a generative algorithm in which a single circuit is the entire model, and we use it to learn calorimeter images. In a classical chaos expansion the randomness is the input and the coefficients are fitted. Here the randomness is still the only input, entering the circuit as rotation angles and re-uploaded at every block, so that each measured observable is a chaos expansion of the latent variables whose order equals the circuit depth, and what is fitted are the gate angles themselves. Expressivity therefore grows with depth rather than with classical coefficients, correlations between outputs arise only from entangling gates, and a single latent wire read by all qubits carries the collective mode of the data. Nothing fitted stands between the circuit and the sample, so switching the entanglers off is a setting of the model itself and provably yields independent outputs, and attribution of the learned correlations to individual gates becomes a measurement. Choosing between two measurement bases shot by shot sharpens attribution into certification, and the trained model violates the Bell bound obeyed by every classical generative model with local response, whatever its size. We train the model on Geant4 shower data, execute the identical circuit on a superconducting processor with its accuracy loss predicted in advance, prove a no-go theorem for the tail dependence of every smooth generator read out through expectation values, and identify the circuit primitive that removes this limit. Subjects: Quantum Physics (quant-ph) Cite as: arXiv:2608.05405 [quant-ph] (or arXiv:2608.05405v1 [quant-ph] for this version) https://doi.org/10.48550/arXiv.2608.05405 Focus to learn more arXiv-issued DOI via DataCite (pending registration) Submission history From: Jamal Slim [view email] [v1] Wed, 5 Aug 2026 20:59:39 UTC (215 KB) Full-text links: Access Paper: View a PDF of the paper titled Interferometric Quantum Polynomial Chaos Expansion as a Generative Model for Calorimeter Shower Simulation, by Jamal Slim and Saverio Monaco and Florian Rehm and Dirk Kruecker and Frank Gaede and Kerstin BorrasView PDFTeX 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?)