Literature DB >> 25526161

Finite-size scaling as a way to probe near-criticality in natural swarms.

Alessandro Attanasi1, Andrea Cavagna2, Lorenzo Del Castello1, Irene Giardina2, Stefania Melillo1, Leonardo Parisi3, Oliver Pohl1, Bruno Rossaro4, Edward Shen1, Edmondo Silvestri5, Massimiliano Viale1.   

Abstract

Collective behavior in biological systems is often accompanied by strong correlations. The question has therefore arisen of whether correlation is amplified by the vicinity to some critical point in the parameters space. Biological systems, though, are typically quite far from the thermodynamic limit, so that the value of the control parameter at which correlation and susceptibility peak depend on size. Hence, a system would need to readjust its control parameter according to its size in order to be maximally correlated. This readjustment, though, has never been observed experimentally. By gathering three-dimensional data on swarms of midges in the field we find that swarms tune their control parameter and size so as to maintain a scaling behavior of the correlation function. As a consequence, correlation length and susceptibility scale with the system's size and swarms exhibit a near-maximal degree of correlation at all sizes.

Entities:  

Mesh:

Year:  2014        PMID: 25526161     DOI: 10.1103/PhysRevLett.113.238102

Source DB:  PubMed          Journal:  Phys Rev Lett        ISSN: 0031-9007            Impact factor:   9.161


  38 in total

1.  Self-phoretic active particles interacting by diffusiophoresis: A numerical study of the collapsed state and dynamic clustering.

Authors:  Oliver Pohl; Holger Stark
Journal:  Eur Phys J E Soft Matter       Date:  2015-08-31       Impact factor: 1.890

2.  Intermittent collective dynamics emerge from conflicting imperatives in sheep herds.

Authors:  Francesco Ginelli; Fernando Peruani; Marie-Helène Pillot; Hugues Chaté; Guy Theraulaz; Richard Bon
Journal:  Proc Natl Acad Sci U S A       Date:  2015-09-28       Impact factor: 11.205

3.  Collective response to perturbations in a data-driven fish school model.

Authors:  Daniel S Calovi; Ugo Lopez; Paul Schuhmacher; Hugues Chaté; Clément Sire; Guy Theraulaz
Journal:  J R Soc Interface       Date:  2015-03-06       Impact factor: 4.118

4.  Multi-scale analysis and modelling of collective migration in biological systems.

Authors:  Andreas Deutsch; Peter Friedl; Luigi Preziosi; Guy Theraulaz
Journal:  Philos Trans R Soc Lond B Biol Sci       Date:  2020-07-27       Impact factor: 6.237

5.  Geometric decompositions of collective motion.

Authors:  Matteo Mischiati; P S Krishnaprasad
Journal:  Proc Math Phys Eng Sci       Date:  2017-04-26       Impact factor: 2.704

6.  Environmental perturbations induce correlations in midge swarms.

Authors:  Kasper van der Vaart; Michael Sinhuber; Andrew M Reynolds; Nicholas T Ouellette
Journal:  J R Soc Interface       Date:  2020-03-25       Impact factor: 4.118

7.  Pair formation in insect swarms driven by adaptive long-range interactions.

Authors:  Dan Gorbonos; James G Puckett; Kasper van der Vaart; Michael Sinhuber; Nicholas T Ouellette; Nir S Gov
Journal:  J R Soc Interface       Date:  2020-10-07       Impact factor: 4.118

Review 8.  Scale invariance in natural and artificial collective systems: a review.

Authors:  Yara Khaluf; Eliseo Ferrante; Pieter Simoens; Cristián Huepe
Journal:  J R Soc Interface       Date:  2017-11       Impact factor: 4.118

9.  Life as an emergent phenomenon: studies from a large-scale boid simulation and web data.

Authors:  Takashi Ikegami; Yoh-Ichi Mototake; Shintaro Kobori; Mizuki Oka; Yasuhiro Hashimoto
Journal:  Philos Trans A Math Phys Eng Sci       Date:  2017-12-28       Impact factor: 4.226

10.  Simulating Flying Insects Using Dynamics and Data-Driven Noise Modeling to Generate Diverse Collective Behaviors.

Authors:  Jiaping Ren; Xinjie Wang; Xiaogang Jin; Dinesh Manocha
Journal:  PLoS One       Date:  2016-05-17       Impact factor: 3.240

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.