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

Turgut, Ali Emre
Okay, Ilkin Ege
Ferrante, Eliseo
Huepe, Cristian
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.


Computational modeling of passive myocardium
Göktepe, Serdar; Wong, Jonathan; Kuhl, Ellen (Wiley, 2011-01-01)
This work deals with the computational modeling of passive myocardial tissue within the framework ofmixed, non-linear finite element methods. We consider a recently proposed, convex, anisotropic hyperelastic model that accounts for the locally orthotropic micro-structure of cardiac muscle. A coordinate-free representation of anisotropy is incorporated through physically relevant invariants of the Cauchy-Green deformation tensors and structural tensors of the corresponding material symmetry group. This model...
Hybrid wavelet-neural network models for time series data
Kılıç, Deniz Kenan; Uğur, Ömür; Department of Financial Mathematics (2021-3-3)
The thesis aims to combine wavelet theory with nonlinear models, particularly neural networks, to find an appropriate time series model structure. Data like financial time series are nonstationary, noisy, and chaotic. Therefore using wavelet analysis helps better modeling in the sense of both frequency and time. S&P500 (∧GSPC) and NASDAQ (∧ IXIC) data are divided into several components by using multiresolution analysis (MRA). Subsequently, each part is modeled by using a suitable neural network structure. ...
Comparison of two inference approaches in Gaussian graphical models
Purutçuoğlu Gazi, Vilda; Wit, Ernst (Walter de Gruyter GmbH, 2017-04-01)
Introduction: The Gaussian Graphical Model (GGM) is one of the well-known probabilistic models which is based on the conditional independency of nodes in the biological system. Here, we compare the estimates of the GGM parameters by the graphical lasso (glasso) method and the threshold gradient descent (TGD) algorithm.
Analyses of extracellular protein production in Bacillus subtilis - I: Genome-scale metabolic model reconstruction based on updated gene-enzyme-reaction data
KOCABAŞ, PINAR; Çalık, Pınar; ÇALIK GARCİA, GÜZİDE; Ozdamar, Tuncer H. (Elsevier BV, 2017-11-15)
Bacillus subtilis genome-scale model (GEM) reconstruction was stimulated by the recent sequencing and consequent re-annotations. The updated gene-enzyme-reaction data were collected from databases to reconstruct B. subtilis reaction network BsRN-2016 containing 1144 genes linked to 1955 reactions and 1103 metabolites. Thermodynamic analysis was conducted to identify reversibility and directionality of the reactions. By elimination of unconnected-reactions from BsRN-2016, reconstruction process of the first ...
Ablation modeling for high speed internal and external flows
Onay, Oğuz Kaan; Eyi, Sinan; Department of Aerospace Engineering (2020)
In this thesis study, the ablation of graphitic materials is modeled and two different analysis tools are developed. In the first model, the computations are conducted with a decoupled approach. Secondly, a more generalized calculation method is introduced via coupling the flow field and solid conduction analysis codes. In the modeling studies, both the gas and solid domains are assumed to be axisymmetric and the physical domains are discretized with structured finite volume cells. For the flow field analys...
Citation Formats
A. E. Turgut, I. E. Okay, E. Ferrante, and C. Huepe, “Interaction network effects on position- and velocity-based models of collective motion,” JOURNAL OF THE ROYAL SOCIETY INTERFACE, pp. 0–0, 2020, Accessed: 00, 2020. [Online]. Available: