Stochastic Model and Optimal Control of an Active Tracking Particle with Information Processing
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arXiv
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| Format: | Preprint |
| Published: |
2025
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| _version_ | 1866912930601107456 |
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| author | Han, Tai Meng, Fanlong |
| author_facet | Han, Tai Meng, Fanlong |
| contents | Living systems often function with regulatory interactions, but the question of how activity, stochasticity and regulations work together for achieving different goals still remains puzzling. We propose a stochastic model of an active tracking particle with information processing, where the entropy production and information flow are discussed, with the generalised fluctuation theorem serving as a benchmark for verifying the probability setup. Based on the model, the system performance, in terms of the first passage steps and the total energy consumption, are analysed in the variable space of (measurement error, control field), leading to discussions on optimal controls of the system. Not only elucidating the basic concepts involved in a stochastic active system with information processing, this prototypical model could also inspire more elaborated modelings of natural smart organisms and industrial designs of controllable active systems with desired physical performances in the future. |
| format | Preprint |
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arxiv_https___arxiv_org_abs_2508_21487 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Stochastic Model and Optimal Control of an Active Tracking Particle with Information Processing Han, Tai Meng, Fanlong Soft Condensed Matter Statistical Mechanics Biological Physics Living systems often function with regulatory interactions, but the question of how activity, stochasticity and regulations work together for achieving different goals still remains puzzling. We propose a stochastic model of an active tracking particle with information processing, where the entropy production and information flow are discussed, with the generalised fluctuation theorem serving as a benchmark for verifying the probability setup. Based on the model, the system performance, in terms of the first passage steps and the total energy consumption, are analysed in the variable space of (measurement error, control field), leading to discussions on optimal controls of the system. Not only elucidating the basic concepts involved in a stochastic active system with information processing, this prototypical model could also inspire more elaborated modelings of natural smart organisms and industrial designs of controllable active systems with desired physical performances in the future. |
| title | Stochastic Model and Optimal Control of an Active Tracking Particle with Information Processing |
| topic | Soft Condensed Matter Statistical Mechanics Biological Physics |
| url | https://arxiv.org/abs/2508.21487 |