UCL Discovery
UCL home » Library Services » Electronic resources » UCL Discovery

Emergence of giant strongly connected components in continuum disk-spin percolation

Caravelli, F; Bardoscia, M; Caccioli, F; (2016) Emergence of giant strongly connected components in continuum disk-spin percolation. Journal of Statistical Mechanics: Theory and Experiment , 2016 , Article 053211. 10.1088/1742-5468/2016/05/053211. Green open access

[thumbnail of Main.pdf]
Preview
Text
Main.pdf - Accepted Version

Download (468kB) | Preview

Abstract

We propose a continuum model of percolation in two dimensions for overlapping disks with spin. In this model the existence of bonds is determined by the distance between the centers of the disks, and by the scalar product of the (randomly) directed spin with the direction of the vector connecting the centers of neighboring disks. The direction of a single spin is controlled by a 'temperature', representing the amount of polarization of the spins in the direction of an external field. Our model is inspired by biological neuronal networks and aims to characterize their topological properties when axonal guidance plays a major role. We numerically study the phase diagram of the model observing the emergence of a giant strongly connected component, representing the portion of neurons that are causally connected. We provide strong evidence that the critical exponents depend on the temperature.

Type: Article
Title: Emergence of giant strongly connected components in continuum disk-spin percolation
Open access status: An open access version is available from UCL Discovery
DOI: 10.1088/1742-5468/2016/05/053211
Publisher version: http://doi.org/10.1088/1742-5468/2016/05/053211
Language: English
Additional information: © 2016 IOP Publishing Ltd and SISSA Medialab srl
Keywords: Science & Technology, Technology, Physical Sciences, Mechanics, Physics, Mathematical, Physics, percolation problems (theory), neuronal networks (theory), random graphs, networks, DIRECTED PERCOLATION, FEEDFORWARD, NETWORKS, CORTEX, STATES
UCL classification: UCL
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Computer Science
URI: https://discovery.ucl.ac.uk/id/eprint/1482279
Downloads since deposit
108Downloads
Download activity - last month
Download activity - last 12 months
Downloads by country - last 12 months

Archive Staff Only

View Item View Item