Noise-robust navigation from an adaptive run-and-tumble policy

[2608.27751] Noise-robust navigation from an adaptive run-and-tumble policy Skip to main content Search Submit Donate Log in Physics > Biological Physics arXiv:2608.27751 (physics) [Submitted on 27 Aug 2026] Title: Noise-robust navigation from an adaptive run-and-tumble policy Authors: Aniruddha Datta , Shiladitya Banerjee View PDF HTML (experimental) Abstract: How do organisms navigate when the signals guiding them are noisy? Variance adaptation, the rescaling of sensitivity to noise, is common in sensory systems, but its role in navigation is unexplored. We introduce a minimal active Brownian particle whose run-and-tumble policy follows from an optimality principle. Variance adaptation emerges as part of this policy. Adaptation keeps chemotactic drift finite as noise grows, while a non-adaptive particle's collapses exponentially. Adaptation also carries a cost, degrading performance in quiet environments and requiring a tuned adaptation sensitivity. Comments: 5 pages, 4 figures, 4 supplemental files Subjects: Biological Physics (physics.bio-ph) ; Statistical Mechanics (cond-mat.stat-mech); Adaptation and Self-Organizing Systems (nlin.AO) Cite as: arXiv:2608.27751 [physics.bio-ph] (or arXiv:2608.27751v1 [physics.bio-ph] for this version) https://doi.org/10.48550/arXiv.2608.27751 Focus to learn more arXiv-issued DOI via DataCite Submission history From: Shiladitya Banerjee [ view email ] [v1] Thu, 27 Aug 2026 22:29:05 UTC (10,090 KB) Full-text links: Access Paper: View PDF HTML (experimental) TeX Source view license Ancillary-file links: Ancillary files ( details ) : Movie1.mp4 Movie2.mp4 Movie3.mp4 Supplemental_Materials.pdf Current browse context: physics.bio-ph < prev | next > new | recent | 2026-08 Change to browse by: cond-mat cond-mat.stat-mech nlin nlin.AO physics References & Citations SciX Google Scholar Semantic Scholar export BibTeX citation Bookmark Bibliographic Tools Bibliographic and Citation Tools Bibliographic Explorer Toggle Bibliographic Explorer ( What is the Explorer? ) Connected Papers Toggle Connected Papers ( What is Connected Papers? ) Litmaps Toggle Litmaps ( What is Litmaps? ) scite.ai Toggle scite Smart Citations ( What are Smart Citations? ) Code, Data, Media Code, Data and Media Associated with this Article alphaXiv Toggle alphaXiv ( What is alphaXiv? ) Links to Code Toggle CatalyzeX Code Finder for Papers ( What is CatalyzeX? ) DagsHub Toggle DagsHub ( What is DagsHub? ) GotitPub Toggle Gotit.pub ( What is GotitPub? ) Huggingface Toggle Hugging Face ( What is Huggingface? ) ScienceCast Toggle ScienceCast ( What is ScienceCast? ) Demos Demos Replicate Toggle Replicate ( What is Replicate? ) Spaces Toggle Hugging Face Spaces ( What is Spaces? ) Spaces Toggle TXYZ.AI ( What is TXYZ.AI? ) Related Papers Recommenders and Search Tools Link to Influence Flower Influence Flower ( What are Influence Flowers? ) Core recommender toggle CORE Recommender ( What is CORE? ) Author Venue Institution Topic About arXivLabs arXivLabs: experimental projects with community collaborators arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website. Both individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy. arXiv is committed to these values and only works with partners that adhere to them. Have an idea for a project that will add value for arXiv's community? Learn more about arXivLabs . Which authors of this paper are endorsers? | Disable MathJax ( What is MathJax? ) We gratefully acknowledge support from our major funders , member institutions , and all contributors. About · Help · Contact · Subscribe · Copyright · Privacy · Accessibility · Operational Status (opens in new tab)

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