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Quantum reservoir computing with classical and nonclassical states in an integrated optical circuit

arXiv Quantum Physics
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⚡ Quantum Brief
An international team led by Polish and Singaporean researchers demonstrated quantum reservoir computing (QRC) using integrated optical circuits, achieving a 9-fold error reduction over classical systems with minimal quantum resources. The breakthrough relies on a single nonclassical "kitten" state combined with classical coherent states, proving significant quantum advantage even when only one input mode carries quantumness. Researchers used an extended positive-P phase space method to simulate the bosonic system without Hilbert space limitations, enabling exact correlation function calculations in silicon-chip hardware. This work validates QRC as a hardware-efficient quantum machine learning approach, requiring only linear optical components and accessible photonic technology. Published in March 2026, the study offers a practical pathway toward near-term quantum-enhanced computation using existing optical infrastructure.
Quantum reservoir computing with classical and nonclassical states in an integrated optical circuit

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Quantum Physics arXiv:2603.17103 (quant-ph) [Submitted on 17 Mar 2026] Title:Quantum reservoir computing with classical and nonclassical states in an integrated optical circuit Authors:S. Świerczewski (1), W. Verstraelen (2 and 3), P. Deuar (4), T. C. H. Liew (2 and 3), A. Opala (5,4), M. Matuszewski (1,4) ((1) Center for Quantum Enabled-Computing, Center for Theoretical Physics of the Polish Academy of Sciences, (2) Division of Physics and Applied Physics, School of Physical and Mathematical Sciences, Nanyang Technological University, Singapore, (3) Majulab, International Joint Research Unit, (4) Institute of Physics, Polish Academy of Sciences, (5) Institute of Experimental Physics, Faculty of Physics, University of Warsaw) View a PDF of the paper titled Quantum reservoir computing with classical and nonclassical states in an integrated optical circuit, by S. \'Swierczewski (1) and 18 other authors View PDF HTML (experimental) Abstract:Quantum reservoir computing (QRC) is a hardware-implementation-friendly quantum neural network scheme with minimal physical system requirements and a proven advantage over classical counterparts. We use an extension of the positive-P phase space method to efficiently simulate a bosonic, linear silicon-chip based QRC system excited with a single nonclassical state, a "kitten" state. In combination with input-encoding coherent states, our method allows to obtain exact results for all correlation functions without Hilbert space cutoff. Surprisingly, we find that such a setting - where the only "quantumness'' derives from a single input mode, is sufficient to obtain significant (over 9-fold) reduction of classification error over the classical counterpart. Our work provides a promising direction toward efficient quantum computation with accessible optical hardware. Comments: Subjects: Quantum Physics (quant-ph); Optics (physics.optics) Cite as: arXiv:2603.17103 [quant-ph] (or arXiv:2603.17103v1 [quant-ph] for this version) https://doi.org/10.48550/arXiv.2603.17103 Focus to learn more arXiv-issued DOI via DataCite (pending registration) Submission history From: Stanisław Świerczewski [view email] [v1] Tue, 17 Mar 2026 19:49:59 UTC (2,060 KB) Full-text links: Access Paper: View a PDF of the paper titled Quantum reservoir computing with classical and nonclassical states in an integrated optical circuit, by S. \'Swierczewski (1) and 18 other authorsView PDFHTML (experimental)TeX Source view license Current browse context: quant-ph new | recent | 2026-03 Change to browse by: physics physics.optics 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?)

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Source: arXiv Quantum Physics