-
In recent years, the physics of systems with non-reciprocal interactions has become an increasing research focus. Systems with non-reciprocal interactions are ubiquitous across soft matter, active matter, as well as biological and artificial nanoscale systems. The directional transport of coupled Brownian particles with nonreciprocal interactions was investigated by establishing a nonreciprocal coupled Brownian ratchets model. The effects of parameters such as the coupling free length, thermal noise intensity, and the ratio of nonreciprocal coupling strength coefficients on the ratchet's directional transport were systematically examined.
Research reveals that the flow reversal of particles can be induced by adjusting the coupling free length. Meanwhile, there exists an optimal ratio of coupling strength coefficients that maximizes the directional transport of the nonreciprocally coupled Brownian particles. These findings demonstrate that nonreciprocal interactions indeed enhance directional transport of coupled systems. Additionally, directional transport control can be achieved by modulating parameters such as thermal noise intensity, asymmetry coefficient, and external potential barrier height. Future research may further explore the dynamical mechanisms of nonreciprocal interactions in complex environments, especially the swarm behaviors in many-particle systems. Furthermore, by combining relevant experimental and theoretical studies, deeper insights can be gained into the regularity and universality of non-reciprocal interactions across both natural and artificial nanoscale systems.-
Keywords:
- non-reciprocal interaction /
- coupled Brownian particles /
- center-of-mass mean velocity /
- current reversal
-
[1] Bowick M J, Fakhri N, Marchetti M C, Ramaswamy S 2022 Phys. Rev. X 12 010501
[2] You Z, Baskaran A, Marchetti M C 2020 Proc. Natl. Acad. Sci. 117 19767
[3] Scheibner C, Souslov A, Banerjee D, Surówka P, Irvine W T, Vitelli V 2020 Nat. Phys. 16 475
[4] Gupta R K, Kant R, Soni H, Sood A K, Ramaswamy S 2020 Phys. Rev. E 105 064602
[5] He Y, Ai B, Dai C, Song C, Wang R, Sun W, Liu F, Feng Y 2020 Phys. Rev. Lett. 124 075001
[6] Xiong L, Cao Y, Cooper R, Rappel W J, Hasty J, Tsimring L 2020 Elife 9 e48885
[7] Theveneau E, Steventon B, Scarpa E, Garcia S, Trepat X, Streit A, Mayor R 2013 Nat. Cell Biol. 15 763
[8] Saha S, Ramaswamy S, Golestanian R 2019 New. J. Phys. 21 063006
[9] Soto R, Golestanian R 2014 Phys. Rev. Lett. 112 068301
[10] Sompolinsky H, Kanter I 1986 Phys. Rev. Lett. 57 2861
[11] Brunel N 2000 J. Comput. Neurosci. 8 183
[12] Golomb D, Hansel D 2000 Neural Comput. 12 1095
[13] Boergers C, Kopell N 2003 Neural Comput. 15 509
[14] Loos S A, Klapp S H, Martynec T 2023 Phys. Rev. Lett. 19 130
[15] Fruchart M, Littlewood P B, Hanai R 2020 Nature 592 7854
[16] Poncet A, Bartolo D 2022 Phys. Rev. Let. 128 048002
[17] Fruchart M, Hanai R, Littlewood P B, Vitelli V 2021 Nature 592 363
[18] Lachance J, Suh K, Clausen J, Cohen D J 2022 Plos Comput. Biol. 18 e1009293
[19] Dzubiella J, Lowen H 2003 Phys. Rev. Lett. 24 91
[20] Lisin E A, Petrov O F, Sametov E A 2020 Sci. Rep. 10 13653
[21] Sabass B, Seifert U 2010 Phys. Rev. Lett. 105 218103
[22] Sriram I, Furst E M 2012 Soft Matter 8 3335
[23] Felipe J, Harmon K J, Nguyen T D 2020 Phys. Rev. Res. 2 043244
[24] Bhattacherjee, Hayakawa M, Shibata T 2024 Soft Matter 20 2739
[25] Kreienkamp K L, Klapp S H 2022 New J. Phys. 24 123009
[26] Li C P, Chen H B, Zheng Z G 2017 Front. Phys. 12 120507
[27] Archana G R, Barik D Physica A 2024 Physica. A 650 129992
[28] Ai B Q 2023 Phys. Rev. E 108 064409
Metrics
- Abstract views: 34
- PDF Downloads: 1
- Cited By: 0
下载:
