Unravelling the Flow of Information in a Nonequilibrium Process in the Presence of Hydrodynamic Interactions
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arXiv
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| Format: | Preprint |
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2025
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| _version_ | 1866913956831952896 |
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| author | Das, Biswajit Manikandan, Sreekanth K Banerjee, Ayan |
| author_facet | Das, Biswajit Manikandan, Sreekanth K Banerjee, Ayan |
| contents | Identifying the origin of nonequilibrium characteristics in a generic interacting system having multiple degrees of freedom is a challenging task. In this context, information theoretic measures such as mutual information and related polymorphs offer valuable insights. Here, we explore these measures in a minimal experimental model consisting of two hydrodynamically coupled colloidal particles, where a nonequilibrium drive is introduced via an exponentially correlated noise acting on one of the particles. We show that the information-theoretic tools considered enable a systematic, data-driven dissection of information flow within the system. These measures allow us to identify the driving node and reconstruct the directional dependencies between particles. Notably, they help explain a recently observed, counterintuitive trend in the dependence of irreversibility on interaction strength under coarse-graining (B. Das et.al., arXiv:2405.00800 (2024)). Finally, our results demonstrate how directional information measures can uncover the hidden structure of nonequilibrium dynamics and provide a framework for studying similar effects in more complex systems. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2504_10124 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Unravelling the Flow of Information in a Nonequilibrium Process in the Presence of Hydrodynamic Interactions Das, Biswajit Manikandan, Sreekanth K Banerjee, Ayan Statistical Mechanics Identifying the origin of nonequilibrium characteristics in a generic interacting system having multiple degrees of freedom is a challenging task. In this context, information theoretic measures such as mutual information and related polymorphs offer valuable insights. Here, we explore these measures in a minimal experimental model consisting of two hydrodynamically coupled colloidal particles, where a nonequilibrium drive is introduced via an exponentially correlated noise acting on one of the particles. We show that the information-theoretic tools considered enable a systematic, data-driven dissection of information flow within the system. These measures allow us to identify the driving node and reconstruct the directional dependencies between particles. Notably, they help explain a recently observed, counterintuitive trend in the dependence of irreversibility on interaction strength under coarse-graining (B. Das et.al., arXiv:2405.00800 (2024)). Finally, our results demonstrate how directional information measures can uncover the hidden structure of nonequilibrium dynamics and provide a framework for studying similar effects in more complex systems. |
| title | Unravelling the Flow of Information in a Nonequilibrium Process in the Presence of Hydrodynamic Interactions |
| topic | Statistical Mechanics |
| url | https://arxiv.org/abs/2504.10124 |