Collective Behavior in Active Swarms: Dynamics at the Edge of Disorder

Collective Behavior in Active Swarms: Dynamics at the Edge of Disorder | 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 Collective Behavior in Active Swarms: Dynamics at the Edge of Disorder Priyanka Iyer, Dmitry Fedosov, Gerhard Gompper This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7075333/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 10 Jan, 2026 Read the published version in Communications Physics → Version 1 posted You are reading this latest preprint version Abstract We propose a minimal flocking model based on the inertial spin model for agents with vision-based steering interactions -- alignment, group cohesion and local collision avoidance. Numerical simulations in two-dimensions show that the local avoidance interaction induces a transition from polar order to disorder, triggered by the fast response of the flock to local changes in direction, thus acting as a source for emergent noise. Near this transition, vision-based cohesion interactions create a feedback loop between local density, alignment, and motion, leading to significant shape fluctuations of the flock, along with a change in the collective motion of the flock from ballistic to diffusive. In the overdamped regime, deep in the ordered phase, the vision-based cohesion interaction is shown to act similar to a surface tension, driving the flocks toward circular configurations. The universality class of the avoidance induced transition is different from the Vicsek-type transition. Notably, the emergence of large vortices and an exponential scaling of the correlation length, suggest some similarities to the Berezinskii-Kosterlitz-Thouless transition. The strong dependence of flock behavior on parameters like local avoidance can enable rapid responses to external cues, aiding predator evasion and foraging in biological systems. Physical sciences/Physics/Biological physics Physical sciences/Physics/Statistical physics, thermodynamics and nonlinear dynamics/Statistical physics active Brownian particles flocking visual perception self-steering cognitive motion Full Text Additional Declarations There is NO Competing Interest. Supplementary Files SI.pdf Supplementary Information Cite Share Download PDF Status: Published Journal Publication published 10 Jan, 2026 Read the published version in Communications Physics → 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. 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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-7075333","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":483523782,"identity":"e4a12373-08fa-4637-a247-efd70fc6cca6","order_by":0,"name":"Priyanka Iyer","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA7klEQVRIie2RvwrCMBCHr0TaJeB6pUNfIS7WgvgsFaGz0MVJAoW6+AA+ho6Cw4GDm66FLro469ahg+mfOXUUzEdIIOS7+yUBMBh+EkuqaTpUUwSwRBBQj34ldmWjiK+UhnOtAHTn9UoALMP36Ya+hCe+xMRXO4e7Tgmllbm7Z4EqX+zuBI6O0k60bQRZmcepWDP/HntcYCSIj7FXqeiKtnoDr2qVoOxVgAh5rUDXRWdAmFppuKUFqiyLcKvusj/biTZY4GweeUkz9WJ8npertS8u6eGlDcZg0NXkUbsybazm11hX06GeswaDwfCvfADNiUEh2yVYCQAAAABJRU5ErkJggg==","orcid":"https://orcid.org/0000-0001-7978-6234","institution":"Forschungszentrum Jülich GmbH","correspondingAuthor":true,"prefix":"","firstName":"Priyanka","middleName":"","lastName":"Iyer","suffix":""},{"id":483523783,"identity":"66095a54-e650-4238-a8f5-c6a7bf96b697","order_by":1,"name":"Dmitry Fedosov","email":"","orcid":"https://orcid.org/0000-0001-7469-9844","institution":"Forschungszentrum Jülich","correspondingAuthor":false,"prefix":"","firstName":"Dmitry","middleName":"","lastName":"Fedosov","suffix":""},{"id":483523784,"identity":"6d3ef736-1159-4d90-8ff6-00b400875f19","order_by":2,"name":"Gerhard Gompper","email":"","orcid":"https://orcid.org/0000-0002-8904-0986","institution":"Forschungszentrum Jülich GmbH","correspondingAuthor":false,"prefix":"","firstName":"Gerhard","middleName":"","lastName":"Gompper","suffix":""}],"badges":[],"createdAt":"2025-07-08 13:25:19","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7075333/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7075333/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1038/s42005-025-02466-7","type":"published","date":"2026-01-10T05:00:00+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":101739857,"identity":"16c158cb-f479-4291-ac24-2e4dfdfba303","added_by":"auto","created_at":"2026-02-03 08:07:33","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":6440478,"visible":true,"origin":"","legend":"Article File","description":"","filename":"manu.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7075333/v1_covered_19b2c91d-d3ee-419c-ac05-2d17be283bfc.pdf"},{"id":87766681,"identity":"8f19441f-dafc-46e4-a612-e2f724595971","added_by":"auto","created_at":"2025-07-28 18:15:44","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":532967,"visible":true,"origin":"","legend":"Supplementary Information","description":"","filename":"SI.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7075333/v1/a979b16ffb47596b9685d05c.pdf"}],"financialInterests":"There is \u003cb\u003eNO\u003c/b\u003e Competing Interest.","formattedTitle":"Collective Behavior in Active Swarms: Dynamics at the Edge of Disorder","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":true,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":true,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"nature-portfolio","isNatureJournal":true,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"","title":"Nature Portfolio","twitterHandle":"","acdcEnabled":false,"dfaEnabled":false,"editorialSystem":"ejp","reportingPortfolio":"","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"active Brownian particles, flocking, visual perception, self-steering, cognitive motion","lastPublishedDoi":"10.21203/rs.3.rs-7075333/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7075333/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"We propose a minimal flocking model based on the inertial spin model for agents with vision-based steering interactions -- alignment, group cohesion and local collision avoidance. 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