TY - JOUR
T1 - How clustering affects the bond percolation threshold in complex networks
AU - Gleeson, James P.
AU - Melnik, Sergey
AU - Hackett, Adam
PY - 2010/6/18
Y1 - 2010/6/18
N2 - The question of how clustering (nonzero density of triangles) in networks affects their bond percolation threshold has important applications in a variety of disciplines. Recent advances in modeling highly clustered networks are employed here to analytically study the bond percolation threshold. In comparison to the threshold in an unclustered network with the same degree distribution and correlation structure, the presence of triangles in these model networks is shown to lead to a larger bond percolation threshold (i.e. clustering increases the epidemic threshold or decreases resilience of the network to random edge deletion).
AB - The question of how clustering (nonzero density of triangles) in networks affects their bond percolation threshold has important applications in a variety of disciplines. Recent advances in modeling highly clustered networks are employed here to analytically study the bond percolation threshold. In comparison to the threshold in an unclustered network with the same degree distribution and correlation structure, the presence of triangles in these model networks is shown to lead to a larger bond percolation threshold (i.e. clustering increases the epidemic threshold or decreases resilience of the network to random edge deletion).
UR - http://www.scopus.com/inward/record.url?scp=77953973695&partnerID=8YFLogxK
U2 - 10.1103/PhysRevE.81.066114
DO - 10.1103/PhysRevE.81.066114
M3 - Article
AN - SCOPUS:77953973695
SN - 1539-3755
VL - 81
JO - Physical Review E - Statistical Physics, Plasmas, Fluids, and Related Interdisciplinary Topics
JF - Physical Review E - Statistical Physics, Plasmas, Fluids, and Related Interdisciplinary Topics
IS - 6
M1 - 066114
ER -