Large algebraic connectivity fluctuations in spatial network ensembles imply a predictive advantage from node location information
File(s)1805.06797 (1).pdf (3.62 MB)
Accepted version
Author(s)
Garrod, Matthew
Jones, Nick S
Type
Journal Article
Abstract
A random geometric graph (RGG) ensemble is defined by the disordered distribution of its node locations. We investigate how this randomness drives sample-to-sample fluctuations in the dynamical properties of these graphs. We study the distributional properties of the algebraic connectivity which is informative of diffusion and synchronization time scales in graphs. We use numerical simulations to provide a characterization of the algebraic connectivity distribution for RGG ensembles. We find that the algebraic connectivity can show fluctuations relative to its mean on the order of 30%, even for relatively large RGG ensembles (N=105). We explore the factors driving these fluctuations for RGG ensembles with different choices of dimensionality, boundary conditions, and node distributions. Within a given ensemble, the algebraic connectivity can covary with the minimum degree and can also be affected by the presence of density inhomogeneities in the nodal distribution. We also derive a closed-form expression for the expected algebraic connectivity for RGGs with periodic boundary conditions for general dimension.
Date Issued
2018-11-29
Date Acceptance
2018-10-30
Citation
Physical Review E, 2018, 98 (5)
ISSN
1539-3755
Publisher
American Physical Society
Journal / Book Title
Physical Review E
Volume
98
Issue
5
Copyright Statement
©2018 American Physical Society
Identifier
http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000451579200007&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=1ba7043ffcc86c417c072aa74d649202
Subjects
Science & Technology
Physical Sciences
Physics, Fluids & Plasmas
Physics, Mathematical
Physics
SYNCHRONIZATION
CONSENSUS
Publication Status
Published
Article Number
ARTN 052316