QCORE: A Quantum-Control-Oriented Real-Time Execution Architecture with Extensible Closed-Loop Services and Shared AI Acceleration

Quantum Physics arXiv:2608.06875 (quant-ph) [Submitted on 7 Aug 2026] Title:QCORE: A Quantum-Control-Oriented Real-Time Execution Architecture with Extensible Closed-Loop Services and Shared AI Acceleration Authors:Heyue Li, Yanshu Guo, Qichun Liu, Tiefu Li, Zhihua Wang, Hanjun Jiang View a PDF of the paper titled QCORE: A Quantum-Control-Oriented Real-Time Execution Architecture with Extensible Closed-Loop Services and Shared AI Acceleration, by Heyue Li and 5 other authors View PDF Abstract:Scalable quantum processors require control, readout, feedback, calibration, and error correction to coexist under bounded latency and shared-resource constraints, whereas existing platforms typically optimize only a subset of these capabilities. This article presents QCORE (Quantum-Control-Oriented Real-Time Execution), a QPU-side digital control reference architecture positioned between the Host and a platform-specific analog/mixed-signal front end. QCORE separates task management, shared resources, hard-real-time execution, and long-timescale services into four hardware partitions. A fast-result sideband closes same-round feedback, a Measurement Packet provides a traceable measurement and service interface, and a common service-control skeleton, Tile-local QEC, and versioned safe-point commit organize calibration, error correction, and long-term state updates. Transaction-level, event-driven, and quantum-behavioral models are used for evaluation. At a background load of 0.8, the $P_{99}$ latency of the shared Measurement Packet/Event feedback path is $(1.984\pm0.004)L_{\max}$. Closed-loop operation reduces the mean frequency error by $83.2\%\pm0.8\%$ and lowers the state-assignment error at maximum readout drift from $10.39\%\pm0.54\%$ to $5.37\%\pm0.29\%$. No unsafe acceptance or mixed-version observation is observed in 100,000 configuration transactions, and Tile-local QEC reduces modeled global-boundary demand and yields a $2.08\times$ capacity-normalized scaling estimate. Comments: Subjects: Quantum Physics (quant-ph); Hardware Architecture (cs.AR) Cite as: arXiv:2608.06875 [quant-ph] (or arXiv:2608.06875v1 [quant-ph] for this version) https://doi.org/10.48550/arXiv.2608.06875 Focus to learn more arXiv-issued DOI via DataCite (pending registration) Submission history From: Yanshu Guo [view email] [v1] Fri, 7 Aug 2026 07:01:14 UTC (3,800 KB) Full-text links: Access Paper: View a PDF of the paper titled QCORE: A Quantum-Control-Oriented Real-Time Execution Architecture with Extensible Closed-Loop Services and Shared AI Acceleration, by Heyue Li and 5 other authorsView PDF view license Current browse context: quant-ph new | recent | 2026-08 Change to browse by: cs cs.AR 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?)