Modeling collective motion: variations on the Vicsek model

New experimental evidence of self-motion of a confined active suspension is presented. Depositing fresh semen sample in an annular shaped microfluidic chip leads to a spontaneous vortex state of the fluid at sufficiently large sperm concentration. The rotation occurs unpredictably clockwise or counterclockwise and is robust and stable. Furthermore, for highly active and concentrated semen, richer dynamics can occur such as self-sustained or damped rotation oscillations. Experimental results obtained with systematic dilution provide a clear evidence of a phase transition towards collective motion associated with local alignment of spermatozoa akin to the Vicsek model. A macroscopic theory based on previously derived self-organized hydrodynamics models is adapted to this context and provides predictions consistent with the observed stationary motion.

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Scaling behavior of non-equilibrium phase transitions in spontaneously ordered motion of self-propelled particles

Modern Physics Letters B ◽

10.1142/s0217984916503048 ◽

2016 ◽

Vol 30 (24) ◽

pp. 1650304 ◽

Cited By ~ 5

Author(s):

R. Bakir ◽

I. Tarras ◽

A. Hader ◽

H. Sbiaai ◽

M. Mazroui ◽

...

Keyword(s):

Phase Transitions ◽

Collective Motion ◽

Equilibrium Phase ◽

Deposition Process ◽

Scaling Behavior ◽

Scaling Exponents ◽

Vicsek Model ◽

Self Similar ◽

Ordered Motion ◽

Non Equilibrium

Many animal groups, such as bird flocks, clearly present structural order and appear to move as a single coherent entity. In interest to understand the complex behavior of these systems, many models have been proposed and tested so far. The aim of this work is to study and discuss numerically the scaling behavior in the 2D non-equilibrium phase transitions in spontaneously ordered motion of self-propelled particles in the framework of Vicsek model. This model is an important tool to study the behavior of collective motion of live biological and physical organisms. The calculation of the scaling exponents is effected by using the scaling dynamic method. However, the time evolution of the particles velocity present two different regimes separated by a cross-over time which increases linearly with both applied noise and radius of repulsive zone, but it decreases exponentially with the radius of orientation zone. The results show that the obtained exponents are similar to the growth and roughness ones used in the interfaces growth and to the submonolayer deposition process. The obtained values of these exponents are not dependent on the noises value, which proves their universality characters. Hence the kinetic evolution of the spontaneously ordered motion of self-propelled particles is self-similar. Implications of these findings are discussed.

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The combined effect of attraction and orientation zones in 2D flocking models

International Journal of Modern Physics B ◽

10.1142/s0217979216500028 ◽

2016 ◽

Vol 30 (04) ◽

pp. 1650002 ◽

Cited By ~ 8

Author(s):

Tarras Iliass ◽

Dorilson Cambui

Keyword(s):

Collective Motion ◽

Numerical Study ◽

Biological Behavior ◽

Behavior Patterns ◽

Vicsek Model ◽

Agent Based ◽

Fish Schools ◽

Behavioral Rules ◽

Parallel Group ◽

Kinetic Phase Transition

In nature, many animal groups, such as fish schools or bird flocks, clearly display structural order and appear to move as a single coherent entity. In order to understand the complex motion of these systems, we study the Vicsek model of self-propelled particles (SPP) which is an important tool to investigate the behavior of collective motion of live organisms. This model reproduces the biological behavior patterns in the two-dimensional (2D) space. Within the framework of this model, the particles move with the same absolute velocity and interact locally in the zone of orientation by trying to align their direction with that of the neighbors. In this paper, we model the collective movement of SPP using an agent-based model which follows biologically motivated behavioral rules, by adding a second region called the attraction zone, where each particles move towards each other avoiding being isolated. Our main goal is to present a detailed numerical study on the effect of the zone of attraction on the kinetic phase transition of our system. In our study, the consideration of this zone seems to play an important role in the cohesion. Consequently, in the directional orientation, the zone that we added forms the compact particle group. In our simulation, we show clearly that the model proposed here can produce two collective behavior patterns: torus and dynamic parallel group. Implications of these findings are discussed.

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Collective Movement and Collective Information Acquisition With Signaling

Frontiers in Physics ◽

10.3389/fphy.2021.668283 ◽

2021 ◽

Vol 9 ◽

Author(s):

Mohammad Salahshour ◽

Shahin Rouhani

Keyword(s):

Information Acquisition ◽

Collective Motion ◽

Large Fraction ◽

Finite Size ◽

Density Fluctuations ◽

Movement Direction ◽

Vicsek Model ◽

High Fraction ◽

Two Phases ◽

Collective Information

We consider a population of mobile agents able to make noisy observations of the environment and communicate their observation by production and comprehension of signals. Individuals try to align their movement direction with their neighbors. Besides, they try to collectively find and travel towards an environmental direction. We show that, when the fraction of informed individuals is small, by increasing the noise in communication, similarly to the Vicsek model, the model shows a discontinuous order-disorder transition with strong finite-size effects. In contrast, for a large fraction of informed individuals, it is possible to go from the ordered phase to the disordered phase without passing any phase transition. The ordered phase is composed of two phases separated by a discontinuous transition. Informed collective motion, in which the population collectively infers the correct environmental direction, occurs for a high fraction of informed individuals. When the fraction of informed individuals is low, the misinformed collective motion, where the population fails to find the environmental direction, becomes stable as well. Besides, we show that an amount of noise in the production of signals is more detrimental for the inference capability of the population and increases temporal fluctuations, the density fluctuations, and the probability of group fragmentation, compared to the same amount of noise in the comprehension.

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Small Noise May Diversify Collective Motion in Vicsek Model

IEEE Transactions on Automatic Control ◽

10.1109/tac.2016.2560144 ◽

2017 ◽

Vol 62 (2) ◽

pp. 636-651 ◽

Cited By ~ 7

Author(s):

Ge Chen

Keyword(s):

Collective Motion ◽

Small Noise ◽

Vicsek Model

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Interaction network effects on position- and velocity-based models of collective motion

Journal of The Royal Society Interface ◽

10.1098/rsif.2020.0165 ◽

2020 ◽

Vol 17 (169) ◽

pp. 20200165

Author(s):

Ali Emre Turgut ◽

İhsan Caner Boz ◽

İlkin Ege Okay ◽

Eliseo Ferrante ◽

Cristián Huepe

Keyword(s):

Power Law ◽

Degree Distribution ◽

Network Effects ◽

Collective Motion ◽

Interaction Network ◽

Small World ◽

Minimal Models ◽

Vicsek Model ◽

Law Degree ◽

Interaction Topology

We study how the structure of the interaction network affects self-organized collective motion in two minimal models of self-propelled agents: the Vicsek model and the Active-Elastic (AE) model. We perform simulations with topologies that interpolate between a nearest-neighbour network and random networks with different degree distributions to analyse the relationship between the interaction topology and the resilience to noise of the ordered state. For the Vicsek case, we find that a higher fraction of random connections with homogeneous or power-law degree distribution increases the critical noise, and thus the resilience to noise, as expected due to small-world effects. Surprisingly, for the AE model, a higher fraction of random links with power-law degree distribution can decrease this resilience, despite most links being long-range. We explain this effect through a simple mechanical analogy, arguing that the larger presence of agents with few connections contributes localized low-energy modes that are easily excited by noise, thus hindering the collective dynamics. These results demonstrate the strong effects of the interaction topology on self-organization. Our work suggests potential roles of the interaction network structure in biological collective behaviour and could also help improve decentralized swarm robotics control and other distributed consensus systems.

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