SPECTRAL BOUNDS IN RANDOM GRAPHS APPLIED TO SPREADING PHENOMENA AND PERCOLATION

被引:0
|
作者
Lemonnier, Remi [1 ,2 ]
Scaman, Kevin [1 ,3 ]
Vayatis, Nicolas [4 ]
机构
[1] Ecole Normale Super Paris Saclay, Cachan, France
[2] 55 Rue Rome, F-75008 Paris, France
[3] 18 Quai Point Jour, F-92100 Boulogne, France
[4] Ecole Normale Super Paris Saclay, CMLA, 61 Ave President Wilson, F-94230 Cachan, France
关键词
Random graph; local positive correlation; hazard matrix; percolation; epidemiology; information cascade; VIRUS SPREAD;
D O I
10.1017/apr.2018.22
中图分类号
O21 [概率论与数理统计]; C8 [统计学];
学科分类号
020208 ; 070103 ; 0714 ;
摘要
In this paper we derive nonasymptotic upper bounds for the size of reachable sets in random graphs. These bounds are subject to a phase transition phenomenon triggered by the spectral radius of the hazard matrix, a reweighted version of the adjacency matrix. Such bounds are valid for a large class of random graphs, called local positive correlation (LPC) random graphs, displaying local positive correlation. In particular, in our main result we state that the size of reachable sets in the subcritical regime for LPC random graphs is at most of order O(root n), where n is the size of the network, and of order O(n(2/3)) in the critical regime, where the epidemic thresholds are driven by the size of the spectral radius of the hazard matrix with respect to 1. As a corollary, we also show that such bounds hold for the size of the giant component in inhomogeneous percolation, the SIR model in epidemiology, as well as for the long-term influence of a node in the independent cascade model.
引用
收藏
页码:480 / 503
页数:24
相关论文
共 50 条
  • [1] Inhomogeneous percolation models for spreading phenomena in random graphs
    Dall'Asta, L
    [J]. JOURNAL OF STATISTICAL MECHANICS-THEORY AND EXPERIMENT, 2005, : 219 - 256
  • [2] Core percolation in random graphs: a critical phenomena analysis
    M. Bauer
    O. Golinelli
    [J]. The European Physical Journal B - Condensed Matter and Complex Systems, 2001, 24 : 339 - 352
  • [3] Core percolation in random graphs: a critical phenomena analysis
    Bauer, M
    Golinelli, O
    [J]. EUROPEAN PHYSICAL JOURNAL B, 2001, 24 (03): : 339 - 352
  • [4] Spectral techniques applied to sparse random graphs
    Feige, U
    Ofek, E
    [J]. RANDOM STRUCTURES & ALGORITHMS, 2005, 27 (02) : 251 - 275
  • [5] Spreading of infections on random graphs: A percolation-type model for COVID-19
    Croccolo, Fabrizio
    Roman, H. Eduardo
    [J]. CHAOS SOLITONS & FRACTALS, 2020, 139
  • [6] Clique percolation in random graphs
    Li, Ming
    Deng, Youjin
    Wang, Bing-Hong
    [J]. PHYSICAL REVIEW E, 2015, 92 (04)
  • [7] CLUTTER PERCOLATION AND RANDOM GRAPHS
    MCDIARD, C
    [J]. MATHEMATICAL PROGRAMMING STUDY, 1980, 13 (AUG): : 17 - 25
  • [8] GENERAL PERCOLATION AND RANDOM GRAPHS
    MCDIARMID, C
    [J]. ADVANCES IN APPLIED PROBABILITY, 1981, 13 (01) : 40 - 60
  • [9] Spreading of Messages in Random Graphs
    Ching-Lueh Chang
    Yuh-Dauh Lyuu
    [J]. Theory of Computing Systems, 2011, 48 : 389 - 401
  • [10] Spreading of Messages in Random Graphs
    Chang, Ching-Lueh
    Lyuu, Yuh-Dauh
    [J]. THEORY OF COMPUTING SYSTEMS, 2011, 48 (02) : 389 - 401