Random graph models for real-world networks

Department Away Day `24

Joost Jorritsma

Math,

Music,

Biking

Understanding network models 

Probability, Combinatorics

& Physics, Epidemiology, ...

Information diffusion in random graphs

Distances

Component sizes

Intervention strategies

FINAL SIZE
Randomized optimization algorithms
Optimization under chance constraints
Sampling algorithms for explainable AI

Inhomogeneous degrees, triangles, and small world

Inhomogeneous degrees, triangles, and small world

Inhomogeneous degrees, triangles, and small world

Inhomogeneous degrees, triangles, and small world

Vertex set

  • Spatial locations
  • Vertex weights

Edge more likely if

  • Spatially nearby,
  • High weight

Spatial random graphs

Percolation: Reed-Frost epidemic

Four parameters: new and classical models

New phenomena

  • Delocalized connected components
  • Double-exponential neighbourhood growth
  • Large outbreaks more likely than small outbreaks

Challenges

  • Geometry:
    • Short/Long edges
  • Presence of hubs

New direction: Scaling limits of trees and random graphs

  • Only vertex weights, no location
  • Edge lengths scale with graph size

Figure by Igor Kortchemski

Setup

  • Include asymmetry in edge probabilities
  • Uncountable and unbounded weights

Goal

References

  1. The Continuum Random Tree; David Aldous; Annals of Probability (1991).
  2. Limits of multiplicative inhomogeneous random graphs and Lévy trees: limit theorems;
    Nicolas Broutin, Thomas Duquesne, Minmin Wang; Probability Theory & Related Fields (2021).
  3. Cluster-size decay in supercritical long-range percolation;
    With Júlia Komjáthy, Dieter Mitsche; Electronic Journal of Probability (2024).
  4. Cluster-size decay in supercritical kernel-based spatial random graphs;
    With Júlia Komjáthy, Dieter Mitsche; Min. revision in Annals of Probability, arXiv: 2303.00712.
  5. Large deviations of the giant in supercritical kernel-based spatial random graphs;
    With Júlia Komjáthy, Dieter Mitsche; Preprint
    arXiv: 2404.02984.
  6. Surface order large deviations for Ising, Potts and percolation models;
    Agoston Pisztora; Probability Theory and Related Fields (2024).
     

Department Away Day `24

Joost Jorritsma

Random graph models for real-world networks

Department Away Day `24

Joost Jorritsma

Department Away Day

By joostjor

Department Away Day

  • 541