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Color code thresholds under circuit-level noise beyond the Pauli framework

Francesco Pio Barone, Daniel Jaschke, Ilaria Siloi, Simone Montangero
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⚡ Quantum Brief
Researchers from the University of Ulm and other institutions demonstrate that Pauli noise models—commonly used in quantum error correction simulations—underestimate real-world error rates by failing to capture non-Pauli noise mechanisms. The study introduces two non-Pauli noise models: systematic X-rotation errors (coherent over-rotations) and amplitude damping (relaxation processes), both simulated in color code circuits using tree tensor networks. Results show coherent over-rotations produce significantly higher error rates than Pauli-twirled approximations, with discrepancies growing as code distance increases, challenging prior assumptions about error thresholds. Tensor network simulations enabled accurate threshold estimations for color codes up to distance 7 (73 qubits), proving scalability for non-Pauli noise analysis in near-term quantum devices. The findings highlight the need for beyond-Pauli noise models in quantum error correction to improve fault-tolerance predictions for real-world quantum hardware.
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Quantum Physics arXiv:2511.05719 (quant-ph) [Submitted on 7 Nov 2025] Title:Color code thresholds under circuit-level noise beyond the Pauli framework Authors:Francesco Pio Barone, Daniel Jaschke, Ilaria Siloi, Simone Montangero View a PDF of the paper titled Color code thresholds under circuit-level noise beyond the Pauli framework, by Francesco Pio Barone and 3 other authors View PDF HTML (experimental) Abstract:A quantum error correction code is assessed over its ability to correct errors in noisy quantum circuits. This task requires extensive simulations of faulty quantum circuits, which are often made tractable by considering stochastic Pauli noise models, as they are compatible with efficient classical simulation techniques. However, such noise models do not fully capture the variety of physical error mechanisms encountered in realistic quantum platforms. In this work, we extend circuit-level noise modeling beyond the Pauli framework by estimating the threshold of the color code under more general noise models. Specifically, we consider two representative non-Pauli error channels: a systematic $X$-rotation model that introduces coherent over-rotations, and an amplitude damping channel that captures relaxation processes. These models are incorporated at the circuit level into color code circuits using a Tree Tensor Network ansatz. Our simulations demonstrate that tensor network simulations enable accurate threshold estimation under non-Pauli noise for color codes up to distance $d=7$ (73 qubits). Comparing our results with the Pauli twirling approximations of the noise models, we find that coherent over-rotations yield systematically higher error rates, deviating from the Pauli twirling approximation as the code distance increases. Subjects: Quantum Physics (quant-ph) Cite as: arXiv:2511.05719 [quant-ph] (or arXiv:2511.05719v1 [quant-ph] for this version) https://doi.org/10.48550/arXiv.2511.05719 Focus to learn more arXiv-issued DOI via DataCite (pending registration) Submission history From: Francesco Pio Barone [view email] [v1] Fri, 7 Nov 2025 21:24:51 UTC (1,169 KB) Full-text links: Access Paper: View a PDF of the paper titled Color code thresholds under circuit-level noise beyond the Pauli framework, by Francesco Pio Barone and 3 other authorsView PDFHTML (experimental)TeX Source view license Current browse context: quant-ph new | recent | 2025-11 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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quantum-error-correction

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