Auditing Structured Randomness for Quantum Error Correction under a Bounded Cloud Fault Model

Quantum Physics arXiv:2608.26600 (quant-ph) [Submitted on 27 Aug 2026] Title:Auditing Structured Randomness for Quantum Error Correction under a Bounded Cloud Fault Model Authors:Ziqing Guo, Anthony Lawrence, Renyu Wang, Randy Kuang, Ziwen Pan View a PDF of the paper titled Auditing Structured Randomness for Quantum Error Correction under a Bounded Cloud Fault Model, by Ziqing Guo and 4 other authors View PDF HTML (experimental) Abstract:Cloud quantum processors compile submitted quantum error correction circuits and may colocate them with untrusted workloads. A fixed public encoder gives a fault-injection adversary a reusable target. Per-run reseeding changes the physical-to-logical fault map. Exact Haar-random encoders have exponential circuit cost. Efficient random ensembles provide average-moment guarantees and leave worst-case accepted corruption uncharacterized. We define accepted logical disturbance, an acceptance-weighted measure of harmful logical action in accepted results, and derive its exact Haar expectation. We evaluate a polynomial-cost seeded Clifford encoder family using dense linear algebra and gate-level stabilizer simulation against faults chosen before or after the encoder is known. Reseeding reduces mean accepted logical disturbance from 0.150 for faults chosen after learning each encoder to 0.020 for one fault chosen before it is known. The 86.7% reduction results from rejection. The fixed distance-three \([[5,1,3]]\) code corrects every tested weight-one Pauli, while 18.5% of sampled encoders in the selected ensemble satisfy exact quantum error correction. The measured reduction quantifies the integrity gain from reseeding and separates postselected detection from exact correction under explicit fault and attacker-knowledge models. Subjects: Quantum Physics (quant-ph) Cite as: arXiv:2608.26600 [quant-ph] (or arXiv:2608.26600v1 [quant-ph] for this version) https://doi.org/10.48550/arXiv.2608.26600 Focus to learn more arXiv-issued DOI via DataCite (pending registration) Submission history From: Ziqing Guo [view email] [v1] Thu, 27 Aug 2026 04:31:19 UTC (89 KB) Full-text links: Access Paper: View a PDF of the paper titled Auditing Structured Randomness for Quantum Error Correction under a Bounded Cloud Fault Model, by Ziqing Guo and 4 other authorsView PDFHTML (experimental)TeX 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?)