Microscopic parametrizations for gate set tomography  under coloured  noise

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Abstract Gate set tomography (GST) allows for a self-consistent characterization of noisy quantum information processors (QIPs). The standard device-agnostic approach treats the QIPs as black boxes that are only constrained by the laws of physics, attaining full generality at aconsiderable resource cost: numerous circuits built from the gate set must be run in order to amplify each of the gate set parameters. In this work, we show that a microscopic parametrization of quantum gates under time-correlated noise on the driving phase, motivated by recent experiments with trapped-ion gates, reduces the required resources enabling a more efficient version of GST. By making use of the formalism of filter functions over the noise spectral densities, we discuss the minimal parametrizations of the gate set that include the effect of finite correlation times and non-Markovian quantum evolutions during the individual gates. We compare the estimated gate sets obtained by our method and the standard long-sequence GST, discussing their accuracies in terms of established metrics, as well as showcasing the advantages of the parametrized approach in terms of the sampling complexity for specific examples.
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Microscopic parametrizations for gate set tomography under coloured noise | 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 Microscopic parametrizations for gate set tomography under coloured noise Pablo Viñas, Alejandro Bermudez This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5288478/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 06 Feb, 2025 Read the published version in npj Quantum Information → Version 1 posted 10 You are reading this latest preprint version Abstract Gate set tomography (GST) allows for a self-consistent characterization of noisy quantum information processors (QIPs). The standard device-agnostic approach treats the QIPs as black boxes that are only constrained by the laws of physics, attaining full generality at aconsiderable resource cost: numerous circuits built from the gate set must be run in order to amplify each of the gate set parameters. In this work, we show that a microscopic parametrization of quantum gates under time-correlated noise on the driving phase, motivated by recent experiments with trapped-ion gates, reduces the required resources enabling a more efficient version of GST. By making use of the formalism of filter functions over the noise spectral densities, we discuss the minimal parametrizations of the gate set that include the effect of finite correlation times and non-Markovian quantum evolutions during the individual gates. We compare the estimated gate sets obtained by our method and the standard long-sequence GST, discussing their accuracies in terms of established metrics, as well as showcasing the advantages of the parametrized approach in terms of the sampling complexity for specific examples. Physical sciences/Physics/Quantum physics/Quantum information Physical sciences/Physics/Information theory and computation Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 06 Feb, 2025 Read the published version in npj Quantum Information → Version 1 posted Editorial decision: Revision requested 09 Dec, 2024 Reviews received at journal 06 Dec, 2024 Reviews received at journal 02 Dec, 2024 Reviewers agreed at journal 17 Nov, 2024 Reviewers agreed at journal 15 Nov, 2024 Reviewers agreed at journal 13 Nov, 2024 Reviewers invited by journal 29 Oct, 2024 Editor assigned by journal 29 Oct, 2024 Submission checks completed at journal 22 Oct, 2024 First submitted to journal 18 Oct, 2024 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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