A Reproducible Workflow for Extracting Quantum Hamiltonians from Surface-Adsorbate Models

A Reproducible Workflow for Extracting Quantum Hamiltonians from Surface-Adsorbate Models | 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 A Reproducible Workflow for Extracting Quantum Hamiltonians from Surface-Adsorbate Models Manisha Malhotra, Fabio Rinaldi, Neil Ramarapu This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9495573/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 Bridging the gap between realistic surface catalysis models from density functional theory (DFT) and the input requirements of quantum algorithms is a non-trivial task. Surface DFT calculations typically model extended slabs and yield total energies or reaction energetics, whereas quantum algorithms (such as variational quantum eigensolvers) require a many-body Hamiltonian (e.g. a list of fermionic or qubit operators) as input. We present an open-source, reproducible software workflow that takes an optimized DFT slab model of a catalyst surface and produces a few-body Hamiltonian suitable for quantum simulation. Starting from a DFT-optimized slab geometry, the workflow extracts a localized cluster around the active site, identifies an appropriate set of active orbitals, and constructs the corresponding fermionic and qubit Hamiltonians. Orbital selection is guided by manual cross-referencing of semiempirical orbital contributions across neutral and anionic cluster states, using localisation and energetic proximity to the HOMO as selection criteria. This end-to-end pipeline enables researchers to bridge surface science and quantum computing in a transparent and automated manner. We demonstrate the workflow on a representative electrochemical system: a hydrogen-based adsorbate (H* or OH*) on an IrO$_2$ catalyst surface. For this system, our software produces a 14-qubit Hamiltonian (derived from a 7-orbital active space) that can be directly used in quantum algorithms such as the Variational Quantum Eigensolver (VQE \cite{VQE}). This work provides a reproducible, end-to-end pipeline bridging periodic surface DFT models and quantum-ready Hamiltonians for heterogeneous catalytic systems, enabling direct integration of realistic surface chemistry with near-term quantum algorithms. Physical sciences/Chemistry Physical sciences/Materials science Physical sciences/Physics 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-9495573","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":636867005,"identity":"e9a2fd66-3d00-47d8-957e-0428d37d4718","order_by":0,"name":"Manisha Malhotra","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABA0lEQVRIiWNgGAWjYJCCA4wNDHIwDpANBDxEaDGGqSZOC0hZYgPRWnTbzx48+HOHXfqG4+3PH/PU3JNtYD/88MObim2JDTi0mJ3JSzjMeyY5d8OZM4bNPMeKjRt40owl55y5jVvLgRyDw4xtzLnbbuQwNuewJQBV5jBI87bh0XL+jcHBn2316Wb3nz9szvkH1ML/hvk37z88Wm7kGBzgbTucYHaDwbA5tw2oRSKHTZq3AZ+WNwaHeduOG+4/k2M4+29fgnGbxDMzyznHbhvjdliO8cefbdXyku3HH3yc8S1Btp8/+fGNNzW3ZXFpwQRsUNqReC0wYE+yjlEwCkbBKBiuAACpv2jjMpw0PQAAAABJRU5ErkJggg==","orcid":"","institution":"Westward Academy","correspondingAuthor":true,"prefix":"","firstName":"Manisha","middleName":"","lastName":"Malhotra","suffix":""},{"id":636867006,"identity":"42f78b3a-e326-4d71-9ca3-ae9901e48f16","order_by":1,"name":"Fabio Rinaldi","email":"","orcid":"","institution":"Google (Ireland)","correspondingAuthor":false,"prefix":"","firstName":"Fabio","middleName":"","lastName":"Rinaldi","suffix":""},{"id":636867007,"identity":"5237de80-18d0-4e16-a980-5e80f29a2603","order_by":2,"name":"Neil Ramarapu","email":"","orcid":"","institution":"Thomas Jefferson High School","correspondingAuthor":false,"prefix":"","firstName":"Neil","middleName":"","lastName":"Ramarapu","suffix":""}],"badges":[],"createdAt":"2026-04-22 11:24:44","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-9495573/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9495573/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":109417252,"identity":"2bdac785-366e-4b5b-81fa-b0af4d35f9e0","added_by":"auto","created_at":"2026-05-17 19:09:38","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":171690,"visible":true,"origin":"","legend":"","description":"","filename":"IridiumOxide1.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9495573/v1_covered_f348c236-850d-41da-aabb-408536406676.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"A Reproducible Workflow for Extracting Quantum Hamiltonians from Surface-Adsorbate Models","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"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":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-9495573/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9495573/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"Bridging the gap between realistic surface catalysis models from density functional theory (DFT) and the input requirements of quantum algorithms is a non-trivial task. Surface DFT calculations typically model extended slabs and yield total energies or reaction energetics, whereas quantum algorithms (such as variational quantum eigensolvers) require a many-body Hamiltonian (e.g. a list of fermionic or qubit operators) as input.\nWe present an open-source, reproducible software workflow that takes an optimized DFT slab model of a catalyst surface and produces a few-body Hamiltonian suitable for quantum simulation. Starting from a DFT-optimized slab geometry, the workflow extracts a localized cluster around the active site, identifies an appropriate set of active orbitals, and constructs the corresponding fermionic and qubit Hamiltonians. Orbital selection is guided by manual cross-referencing of semiempirical orbital contributions across neutral and anionic cluster states, using localisation and energetic proximity to the HOMO as selection criteria. This end-to-end pipeline enables researchers to bridge surface science and quantum computing in a transparent and automated manner.\nWe demonstrate the workflow on a representative electrochemical system: a hydrogen-based adsorbate (H* or OH*) on an IrO$_2$ catalyst surface. 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