Parameter Optimization and Noise Resilience Analysis for QAOA on NISQ Devices: A Comprehensive Study from 3 to 40 Qubits

Parameter Optimization and Noise Resilience Analysis for QAOA on NISQ Devices: A Comprehensive Study from 3 to 40 Qubits | 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 Parameter Optimization and Noise Resilience Analysis for QAOA on NISQ Devices: A Comprehensive Study from 3 to 40 Qubits Matthias Christian Wurm This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7900824/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Quantum algorithms on Noisy Intermediate-Scale Quantum (NISQ) devices require optimization strategies matched to circuit structure. We present two complementary approaches: VERMICULAR, achieving 93.0% success rates for Grover’s algorithm through strategic dynamical decoupling (DD) placement (vs. 18.3% baseline), and systematic QAOA parameter optimization achieving 94.5% approximation ratios for MaxCut (vs. 39.6% with theoretical parameters). Through >15,000 circuit executions across IQM Garnet, Rigetti Ankaa-3, and IonQ Forte-1 (total cost: €70), we demonstrate that circuit structure determines which strategy succeeds: DD helps algorithms with substantial idle time (Grover: 34% idle → 5× improvement) but degrades continuously-active circuits (QAOA: 2.4% idle → 50% degradation with DD). We systematically characterize algorithm noise resilience via critical noise thresholds (σc), finding Bell states achieve 4× higher σc than product states (0.200 vs 0.050, p < 0.001) and that σc predicts hardware performance (r = 0.94, p = 0.006). QAOA scaling studies (3-40 qubits) reveal exponential decay with 56% plateau beyond 20 qubits. Simulator-optimized parameters transfer effectively to hardware (85-98% efficiency), but hardware-to-hardware transfer requires architecture-specific tuning. We provide SigmaCSuite, an open-source validation framework, and complete experimental protocols. These findings establish that optimization strategy must match circuit structure: idle-time protection for search algorithms, parameter tuning for variational algorithms—achieving 2.5-5× improvements through targeted approaches. Physical sciences/Engineering Physical sciences/Mathematics and computing Physical sciences/Physics quantum computing QAOA parameter optimization NISQ devices noise resilience Max- Cut critical noise threshold cross-platform validation Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted 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. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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-7900824","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":544764820,"identity":"9fbbf3d9-1eb2-4274-90c3-5ca506ca1097","order_by":0,"name":"Matthias Christian 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