Sensitivity of Kinetic Monte Carlo Trajectories to the Entropy Source

Sensitivity of Kinetic Monte Carlo Trajectories to the Entropy Source | 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 Research Article Sensitivity of Kinetic Monte Carlo Trajectories to the Entropy Source Saurav Mittal This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8559247/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 Kinetic Monte Carlo (KMC) simulations are widely used to model non-equilibrium processes in which system evolution is governed by sequences of activated events. In such simulations, system evolution depends on the ordered sequence of events selected from a dynamically constructed event catalogue using random numbers at each step. In this work, we investigate the sensitivity of rare event KMC simulations to the underlying source of randomness. We then perform a controlled comparison of quantum and pseudo-random numbers in KMC simulations of two-dimensional hexagonal boron nitride growth, using identical physical models and a fixed deposition flux. Despite similar growth morphologies, the two entropy sources produce distinct growth trajectories, manifested in delayed growth and a systematically different entropy evolution of the system. These results demonstrate that the choice of entropy source can influence trajectory-level behavior in rare event KMC simulations. Computational Physics Kinetic Monte Carlo Rare-event simulations Quantum random numbers Random number generation Crystal growth Full Text Additional Declarations The authors declare no competing interests. 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-8559247","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":572943296,"identity":"6c9477bc-b343-4a58-bf3a-881570b80596","order_by":0,"name":"Saurav Mittal","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABBElEQVRIiWNgGAWjYBADHiBmPJDwQ0IOxDvwgBgtPGxAlQ97LIzBWhKIsgao5eADtorEBhAPnxb59jNmH362bZOxl29+cCCBRyJ9ftjhh0Bb7OR0G7BrMTiTYzyzt+020GFsBgcSLCRyN95OAzIYko3NDuDQwpBjzMBzBqSFwQBkS+7G2QkgLQcSt+HQIt//xpjxD1gL+4cDCWwS6Yaz0z/g1cJwI8eYmacCpIXHAKQlQV46B78tBjeeFTPLgLQcyyk4kNgjYbhBGshIMMDtF/n+5M2Mbwxu27M3H9/48MePOnn52embP3yosJPDpQWLvQcgwUICkG8gRfUoGAWjYBSMBAAAEeVgoagy5dwAAAAASUVORK5CYII=","orcid":"","institution":"","correspondingAuthor":true,"prefix":"","firstName":"Saurav","middleName":"","lastName":"Mittal","suffix":""}],"badges":[],"createdAt":"2026-01-09 09:25:35","currentVersionCode":1,"declarations":{"humanSubjects":false,"vertebrateSubjects":false,"conflictsOfInterestStatement":false,"humanSubjectEthicalGuidelines":false,"humanSubjectConsent":false,"humanSubjectClinicalTrial":false,"humanSubjectCaseReport":false,"vertebrateSubjectEthicalGuidelines":false},"doi":"10.21203/rs.3.rs-8559247/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8559247/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":100366179,"identity":"5a219591-be45-453d-8b62-14e9f26f1d05","added_by":"auto","created_at":"2026-01-16 07:56:04","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1896244,"visible":true,"origin":"","legend":"","description":"","filename":"ManuscriptQRNG3.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8559247/v1_covered_b42ec097-b403-4b77-b432-49d014903a69.pdf"}],"financialInterests":"The authors declare no competing interests.","formattedTitle":"\u003cp\u003eSensitivity of Kinetic Monte Carlo Trajectories to the Entropy Source\u003c/p\u003e","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"Centre for Development of Advanced Computing","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":"Kinetic Monte Carlo; Rare-event simulations; Quantum random numbers; Random number generation; Crystal growth","lastPublishedDoi":"10.21203/rs.3.rs-8559247/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8559247/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eKinetic Monte Carlo (KMC) simulations are widely used to model non-equilibrium processes in which system evolution is governed by sequences of activated events. 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