Resetting mediated navigation of active Brownian searcher in a homogeneous topography
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arXiv
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| Format: | Preprint |
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2022
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| author | Sar, Gourab Kumar Ray, Arnob Ghosh, Dibakar Hens, Chittaranjan Pal, Arnab |
| author_facet | Sar, Gourab Kumar Ray, Arnob Ghosh, Dibakar Hens, Chittaranjan Pal, Arnab |
| contents | Designing navigation strategies for search time optimization remains of interest in various interdisciplinary branches in science. In here, we focus on microscopic self-propelled searchers namely active Brownian walkers in noisy and confined environment which are mediated by one such autonomous strategy namely resetting. As such, resetting stops the motion and compels the walkers to restart from the initial configuration intermittently according to an external timer that does not require control by the walkers. In particular, the resetting coordinates are either quenched (fixed) or annealed (fluctuating) over the entire topography. Although the strategy relies upon simple rules, it shows a significant ramification on the search time statistics in contrast to the original search. We show that the resetting driven protocols mitigate the performance of these active searchers based, robustly, on the inherent search time fluctuations. Notably, for the annealed condition, resetting is always found to expedite the search process. These features, as well as their applicability to more general optimization problems starting from queuing systems, computer science to living systems, make resetting based strategies universally promising. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2208_06850 |
| institution | arXiv |
| publishDate | 2022 |
| record_format | arxiv |
| spellingShingle | Resetting mediated navigation of active Brownian searcher in a homogeneous topography Sar, Gourab Kumar Ray, Arnob Ghosh, Dibakar Hens, Chittaranjan Pal, Arnab Soft Condensed Matter Statistical Mechanics Adaptation and Self-Organizing Systems Designing navigation strategies for search time optimization remains of interest in various interdisciplinary branches in science. In here, we focus on microscopic self-propelled searchers namely active Brownian walkers in noisy and confined environment which are mediated by one such autonomous strategy namely resetting. As such, resetting stops the motion and compels the walkers to restart from the initial configuration intermittently according to an external timer that does not require control by the walkers. In particular, the resetting coordinates are either quenched (fixed) or annealed (fluctuating) over the entire topography. Although the strategy relies upon simple rules, it shows a significant ramification on the search time statistics in contrast to the original search. We show that the resetting driven protocols mitigate the performance of these active searchers based, robustly, on the inherent search time fluctuations. Notably, for the annealed condition, resetting is always found to expedite the search process. These features, as well as their applicability to more general optimization problems starting from queuing systems, computer science to living systems, make resetting based strategies universally promising. |
| title | Resetting mediated navigation of active Brownian searcher in a homogeneous topography |
| topic | Soft Condensed Matter Statistical Mechanics Adaptation and Self-Organizing Systems |
| url | https://arxiv.org/abs/2208.06850 |