Georgii Gennadievich Novikov (1942–2007)

Павлов, Д. С.; Шатуновский, М И; Kasumyan, A. O.; Stroganov, A. N.; Махотин, В. В.; Belova, N. V.; Emel’yanova, N. G.; Savvaitova, K. A.; Kriksunov, E. A.; Девицина, Г. В.

doi:10.1134/s0032945208050068

Cited by 5 publications

(6 citation statements)

References 1 publication

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“…Both ABPs and AOUPs have been originally developed to model the overdamped dynamics of microscopic active particles. However, also macroscopic active 'particles' are rather common in the animal world, such as birds [54], fish [55] and insects [56,57], as well as in the inanimate world, such as walking droplets [58], flying whirling fruits [59] and active granular particles [60][61][62][63][64][65][66]. The recent significant increase of interest in these systems generates the need to develop manageable generalized theoretical descriptions including inertial effects [67].…”

Section: Introductionmentioning

confidence: 99%

Dynamics of active particles with translational and rotational inertia

Sprenger

Caprini

Löwen

et al. 2023

J. Phys.: Condens. Matter

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Inertial eﬀects aﬀecting both the translational and rotational dynamics are inherent to a broad range of active systems at the macroscopic scale. Thus, there is a pivotal need for proper models in the framework of active matter to correctly reproduce experimental results, hopefully achieving theoretical insights. For this purpose, we propose an inertial version of the active Ornstein-Uhlenbeck particle (AOUP) model accounting for particle mass (translational inertia) as well as its moment of inertia (rotational inertia) and derive the full expression for its steady-state properties. The inertial AOUP dynamics introduced in this paper is designed to capture the basic features of the well-established inertial active Brownian particle (ABP) model, i.e., the persistence time of the active motion and the long-time diﬀusion coeﬃcient. For a small or moderate rotational inertia, these two models predict similar dynamics at all timescales and, in general, our inertial AOUP model consistently yields the same trend upon changing the moment of inertia for various dynamical correlation functions.

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Section: Introductionmentioning

confidence: 99%

Dynamics of active particles with translational and rotational inertia

Sprenger

Caprini

Löwen

et al. 2023

J. Phys.: Condens. Matter

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“…This type of escape pattern is prevalent in the school of fishes defending the predator attack. 28,41 As the predator mass is increased to M pd = 100, the predator initially chases the prey swarm and moves in the same direction as the prey move, as in Fig. 4(i).…”

Section: Resultsmentioning

confidence: 96%

“…This widespread predator avoidance has been observed in the school of fishes, and it is called F-maneuver or Fountain effect. 41 We have presented an overview of various escape routes that emerge with increasing predator mass and predator strength (while keeping the prey mass constant) in Fig. S4 of the ESI.…”

Section: Resultsmentioning

confidence: 99%

“…Prey swarms exhibit a variety of escape routes such as circling, Fmanoeuvring, splitting up into subgroups, and merging again into one group in order to survive. [36][37][38][39][40][41] In this paper, we investigate how inertia influences the survival dynamics and the emergence of diverse escape trajectories of a prey swarm when chased by a predator. We consider standard Newtonian mass as a measure of inertia in our study.…”

Section: Introductionmentioning

confidence: 99%

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Inertial effect on evasion and pursuit dynamics of prey swarms: the emergence of a favourable mass ratio for the predator–prey arms race

Chakraborty,

Laha,

2023

Soft Matter

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“…Awe-inspiring examples of organized collective motions abound in a number of biological problems [1,2] from simple microorganisms such as bacteria [3], to insects and higher animals which display deliberate social behaviors such as insect swarming [4,5] bird flocking [6,7], and fish schooling or shoaling [8,9]. Most impressively, large and dense groups of animals can organize themselves in complex coordinated motions avoiding collisions while flying or swimming at close distance.…”

Section: Introductionmentioning

confidence: 99%

Optimal collision avoidance in swarms of active Brownian particles

2021

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The effectiveness of collective navigation of biological or artificial agents requires to accommodate for contrasting requirements, such as staying in a group while avoiding close encounters and at the same time limiting the energy expenditure for maneuvering. Here, we address this problem by considering a system of active Brownian particles in a finite two-dimensional domain and ask what is the control that realizes the optimal tradeoff between collision avoidance and control expenditure. We couch this problem in the language of optimal stochastic control theory and by means of a mean-field game approach we derive an analytic mean-field solution, characterized by a second-order phase transition in the alignment order parameter. We find that a mean-field version of a classical model for collective motion based on alignment interactions (Vicsek model) performs remarkably close to the optimal control. Our results substantiate the view that observed group behaviors may be explained as the result of optimizing multiple objectives and offer a theoretical ground for biomimetic algorithms used for artificial agents.

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Georgii Gennadievich Novikov (1942–2007)

Cited by 5 publications

References 1 publication

Dynamics of active particles with translational and rotational inertia

Dynamics of active particles with translational and rotational inertia

Inertial effect on evasion and pursuit dynamics of prey swarms: the emergence of a favourable mass ratio for the predator–prey arms race

Optimal collision avoidance in swarms of active Brownian particles

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