Directional information transfer between interacting Brownian particles

[2603.10475] Directional information transfer between interacting Brownian particles Skip to main content Search Submit Donate Log in Condensed Matter > Statistical Mechanics arXiv:2603.10475 (cond-mat) [Submitted on 11 Mar 2026 ( v1 ), last revised 23 Aug 2026 (this version, v2)] Title: Directional information transfer between interacting Brownian particles Authors: Tenta Tani View PDF HTML (experimental) Abstract: We theoretically investigate how information flows when two particles interact with each other. Understanding the physical mechanisms of directional information flow is crucial for advancing information thermodynamics and stochastic computing. However, the fundamental connection between mechanical motion and causal information transfer remains elusive. To focus only on essential effects of physical dynamics, we examine two interacting Brownian particles confined in a one-dimensional potential. By simulating their Langevin dynamics, we quantify the causal information exchange using transfer entropy. We demonstrate that a mass asymmetry inherently breaks the symmetry of information flow, inducing a net directional transfer from the heavier to the lighter particle. Physically, the heavier particle, possessing larger inertia and higher active information storage, retains the memory of its trajectory longer against thermal fluctuations, thereby acting as a source of information. We analytically clarify that this net transfer is governed by a competition between the difference in memory capacity and the predictability of the particle trajectories. Furthermore, we reveal that the net information flow scales logarithmically with the mass ratio. These findings provide essential insights into the physical significance of transfer entropy and the nature of information flow in general physical systems. Comments: 11 pages, 9 figures Subjects: Statistical Mechanics (cond-mat.stat-mech) ; Mesoscale and Nanoscale Physics (cond-mat.mes-hall); Soft Condensed Matter (cond-mat.soft) Cite as: arXiv:2603.10475 [cond-mat.stat-mech] (or arXiv:2603.10475v2 [cond-mat.stat-mech] for this version) https://doi.org/10.48550/arXiv.2603.10475 Focus to learn more arXiv-issued DOI via DataCite Journal reference: Phys. Rev. E 114, 024147 (2026) Related DOI : https://doi.org/10.1103/bz5z-dz7t Focus to learn more DOI(s) linking to related resources Submission history From: Tenta Tani [ view email ] [v1] Wed, 11 Mar 2026 06:52:05 UTC (787 KB) [v2] Sun, 23 Aug 2026 05:44:10 UTC (1,096 KB) Full-text links: Access Paper: View PDF HTML (experimental) TeX Source view license Current browse context: cond-mat.stat-mech < prev | next > new | recent | 2026-03 Change to browse by: cond-mat cond-mat.mes-hall cond-mat.soft References & Citations NASA ADS 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? ) IArxiv recommender toggle IArxiv Recommender ( What is IArxiv? ) 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) Major funding support from

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