Efficient Soft-Output Guessing for Enhanced Quantum Tanner Code Decoding

[2603.18318] Efficient Soft-Output Guessing for Enhanced Quantum Tanner Code Decoding Skip to main content Search Submit Donate Log in Quantum Physics arXiv:2603.18318 (quant-ph) [Submitted on 18 Mar 2026 ( v1 ), last revised 24 Aug 2026 (this version, v2)] Title: Efficient Soft-Output Guessing for Enhanced Quantum Tanner Code Decoding Authors: Lukas Rapp , Muriel Médard , Eugene Tang , Ken R. Duffy View PDF HTML (experimental) Abstract: We introduce a generalized low-density parity-check decoding framework for quantum Tanner codes utilizing soft-output guessing random additive noise decoding (SOGRAND). By soft-output decoding entire component codes rather than individual parity checks, we mitigate the effects of trapping sets and cycles, resulting in improved convergence. Because our decoder preserves the message passing structure of standard belief propagation (BP), it is compatible with many BP enhancements. We demonstrate this with OSD postprocessing, quaternary BP, and RelayBP, each yielding further gains. Standalone SOGRAND outperforms the standard BP+OSD baseline by over two orders of magnitude in logical error rate. In combination with the Relay principle, SOGRAND outperforms RelayBP by over one order of magnitude, providing a way forward for scalable decoding of the emerging class of Tanner-code-based quantum codes. Subjects: Quantum Physics (quant-ph) ; Information Theory (cs.IT) Cite as: arXiv:2603.18318 [quant-ph] (or arXiv:2603.18318v2 [quant-ph] for this version) https://doi.org/10.48550/arXiv.2603.18318 Focus to learn more arXiv-issued DOI via DataCite Submission history From: Lukas Rapp [ view email ] [v1] Wed, 18 Mar 2026 22:00:57 UTC (200 KB) [v2] Mon, 24 Aug 2026 18:06:19 UTC (462 KB) Full-text links: Access Paper: View PDF HTML (experimental) TeX Source view license Current browse context: quant-ph < prev | next > new | recent | 2026-03 Change to browse by: cs cs.IT math math.IT References & Citations INSPIRE HEP SciX Google Scholar Semantic Scholar export BibTeX citation 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? ) We gratefully acknowledge support from our major funders , member institutions , and all contributors. About · Help · Contact · Subscribe · Copyright · Privacy · Accessibility · Operational Status (opens in new tab)

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