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Real-Time Quantum Error Correction System Stack: Architecture, Algorithms, and Engineering Practice

arXiv Quantum Physics
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⚡ Quantum Brief
A May 2026 study identifies the shift in quantum error correction (QEC) from theoretical proofs to engineering hurdles, with Google, Riverlane, and Rigetti demonstrating key milestones in low-latency feedback and surface code performance. Real-time QEC’s critical bottlenecks extend beyond decoder speed, pinpointing QEC round time, tail latency, and end-to-end data coordination as the primary obstacles to scalable fault-tolerant quantum computing. The paper benchmarks mainstream decoders for surface and qLDPC codes, revealing gaps between current performance and real-time demands, particularly in latency and throughput under operational conditions. Researchers propose a six-layer system architecture—spanning syndrome acquisition to logical operations—with defined interfaces and latency budgets to bridge the gap between lab prototypes and practical FTQC systems. Findings underscore urgent need for co-designed hardware-software solutions to meet strict real-time constraints, marking a pivotal step toward engineering viable quantum error correction frameworks.
Real-Time Quantum Error Correction System Stack: Architecture, Algorithms, and Engineering Practice

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Quantum Physics arXiv:2605.30765 (quant-ph) [Submitted on 29 May 2026] Title:Real-Time Quantum Error Correction System Stack: Architecture, Algorithms, and Engineering Practice Authors:Yaojian Chen, Chun-Yang Luan, Peilin Zheng, Xianghong Zeng, Jia-Yi Hou, Zhuo Fu, Yirong Jin, Fei Wang, Guangwen Yang, Dingshun Lv View a PDF of the paper titled Real-Time Quantum Error Correction System Stack: Architecture, Algorithms, and Engineering Practice, by Yaojian Chen and 8 other authors View PDF HTML (experimental) Abstract:Quantum error correction (QEC) is transitioning from physical feasibility demonstrations to systems engineering challenges. Google has achieved below-threshold performance on distance-5/7 surface codes, while Riverlane and Rigetti have demonstrated hardware-integrated low-latency feedback loops. These milestones indicate that the core challenge of real-time decoding has shifted from algorithmic capability to system-level engineering. However, a substantial engineering gap remains between laboratory demonstrations and scalable fault-tolerant quantum computing (FTQC). This white paper addresses three questions: (1) Where are the real bottlenecks in real-time QEC: beyond average decoder speed, the constraints lie in QEC round time, tail latency, and end-to-end data path coordination; (2) How mature are mainstream decoder algorithms: we benchmark the major decoders for both surface codes and quantum low-density parity-check (qLDPC) codes, evaluating their real-time readiness; (3) What system stack do we propose: a six-layer reference architecture from syndrome acquisition to logical operations, with interface definitions and latency budget models. Our results quantify the gap between current decoder performance and real-time requirements, and identify the architectural choices needed to close it. Comments: Subjects: Quantum Physics (quant-ph) Cite as: arXiv:2605.30765 [quant-ph] (or arXiv:2605.30765v1 [quant-ph] for this version) https://doi.org/10.48550/arXiv.2605.30765 Focus to learn more arXiv-issued DOI via DataCite (pending registration) Submission history From: Yaojian Chen [view email] [v1] Fri, 29 May 2026 02:51:46 UTC (136 KB) Full-text links: Access Paper: View a PDF of the paper titled Real-Time Quantum Error Correction System Stack: Architecture, Algorithms, and Engineering Practice, by Yaojian Chen and 8 other authorsView PDFHTML (experimental)TeX Source view license Current browse context: quant-ph new | recent | 2026-05 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?)

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Source: arXiv Quantum Physics