PAEMS: Precise and Adaptive Error Model for Superconducting Quantum Processors

PAEMS: Precise and Adaptive Error Model for Superconducting Quantum Processors | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article PAEMS: Precise and Adaptive Error Model for Superconducting Quantum Processors Songhuan He, Yifei Cui, Cheng Wang This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8731876/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 4 You are reading this latest preprint version Abstract Superconducting quantum processor units (QPUs) are incapable of producing massive datasets for quantum error correction (QEC) because of hardware limitations. Thus, QEC decoders heavily depend on synthetic data from qubit error models. Classic depolarizing error models with polynomial complexity present limited accuracy. Coherent density matrix methods suffer from exponential complexity ∝ O(4 n) where n represents the number of qubits. This paper introduces PAEMS: a precise and adaptive qubit error model. Its qubit-wise separation framework, incorporating leakage propagation, captures error evolvements crossing spatial and temporal domains. Utilizing repetition-code experiment datasets, PAEMS effectively identifies the intrinsic qubit errors through an end-to-end optimization pipeline. Experiments on IBM’s QPUs have demonstrated a 19.5×, 9.3×, and 5.2× reduction in timelike, spacelike, and spacetime error correlation, respectively, surpassing all of the previous works. It also outperforms the accuracy of Google’s SI1000 error model by 58∼73% on multiple quantum platforms, including IBM’s Brisbane, Sherbrooke, and Torino, as well as China Mobile’s Wuyue and QuantumCTek’s Tianyan. Physical sciences/Mathematics and computing Physical sciences/Physics Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Reviewers invited by journal 11 May, 2026 Editor assigned by journal 05 Feb, 2026 Submission checks completed at journal 05 Feb, 2026 First submitted to journal 29 Jan, 2026 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-8731876","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":639223829,"identity":"6cf90a9d-2f82-4c3d-a7c2-c219be0ca541","order_by":0,"name":"Songhuan He","email":"","orcid":"","institution":"University of Electronic Science and Technology of China","correspondingAuthor":false,"prefix":"","firstName":"Songhuan","middleName":"","lastName":"He","suffix":""},{"id":639223831,"identity":"7f5ace93-c016-451f-8f76-f791601c4e25","order_by":1,"name":"Yifei Cui","email":"","orcid":"","institution":"University of California, Los Angeles","correspondingAuthor":false,"prefix":"","firstName":"Yifei","middleName":"","lastName":"Cui","suffix":""},{"id":639223832,"identity":"8a6efc4c-e8e3-469c-9061-3fb0caf3cbbb","order_by":2,"name":"Cheng Wang","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA5klEQVRIie3LsQrCMBSF4RsKnUTXiKCvUAkEhIKvEilkCuroIFgQ6lRc7Vt0dKwUdIm4ZhVBHBwCndysg+KUdhTMP90L5wOw2X41FPqL9efL6hGOkvC9rklylGZ1iXc45rfHljtEBXmh59BtKoaKqYnIMR/E0nep4hxneyBtxZzOxkBoJihBEW9QJSjsQhilirlOw0RO9xfJMdlMCl2SRTVRglxK4nlYAC4J86rIUN0piiPOsLxSLPe4n8jzsmMi7bUg+hH5rLUKLno293vNQ7ArTKTMxV/P60ahGQA4umphs9lsf94T1R1TG16w4CUAAAAASUVORK5CYII=","orcid":"","institution":"University of Electronic Science and Technology of China","correspondingAuthor":true,"prefix":"","firstName":"Cheng","middleName":"","lastName":"Wang","suffix":""}],"badges":[],"createdAt":"2026-01-29 13:08:30","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8731876/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8731876/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":109186735,"identity":"4b078217-c6a7-4e47-bbfe-c26f4f513bd1","added_by":"auto","created_at":"2026-05-13 11:15:34","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2154703,"visible":true,"origin":"","legend":"","description":"","filename":"PAEMSPreciseandAdaptiveErrorModelforSuperconductingQuantumProcessorsV2.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8731876/v1_covered_fc0855c5-8db4-49f9-9ec1-218fee32040f.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"PAEMS: Precise and Adaptive Error Model for Superconducting Quantum Processors","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":true,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":true,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"npj-quantum-information","isNatureJournal":false,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"npjqi","sideBox":"Learn more about [npj Quantum Information](http://www.nature.com/npjqi/)","snPcode":"41534","submissionUrl":"https://mts-npjqi.nature.com/","title":"npj Quantum Information","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"ejp","reportingPortfolio":"NPJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-8731876/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8731876/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eSuperconducting quantum processor units (QPUs) are incapable of producing massive datasets for quantum error correction (QEC) because of hardware limitations. 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