Target search by active particles
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arXiv
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| Main Authors: | , , |
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| Format: | Preprint |
| Published: |
2023
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| _version_ | 1866915190214230016 |
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| author | Basu, Urna Sabhapandit, Sanjib Santra, Ion |
| author_facet | Basu, Urna Sabhapandit, Sanjib Santra, Ion |
| contents | Active particles, which are self-propelled nonequilibrium systems, are modelled by overdamped Langevin equations with colored noise, emulating the self-propulsion. In this chapter, we present a review of the theoretical results for the target search problem of these particles. We focus on three most well-known models, namely, run-and-tumble particles, active Brownian particles, and direction reversing active Brownian particles, which differ in their self-propulsion dynamics. For each of these models, we discuss the first-passage and survival probabilities in the presence of an absorbing target. We also discuss how resetting helps the active particles find targets in a finite time. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2311_17854 |
| institution | arXiv |
| publishDate | 2023 |
| record_format | arxiv |
| spellingShingle | Target search by active particles Basu, Urna Sabhapandit, Sanjib Santra, Ion Statistical Mechanics Active particles, which are self-propelled nonequilibrium systems, are modelled by overdamped Langevin equations with colored noise, emulating the self-propulsion. In this chapter, we present a review of the theoretical results for the target search problem of these particles. We focus on three most well-known models, namely, run-and-tumble particles, active Brownian particles, and direction reversing active Brownian particles, which differ in their self-propulsion dynamics. For each of these models, we discuss the first-passage and survival probabilities in the presence of an absorbing target. We also discuss how resetting helps the active particles find targets in a finite time. |
| title | Target search by active particles |
| topic | Statistical Mechanics |
| url | https://arxiv.org/abs/2311.17854 |