Condensation in scale-free geometric graphs with excess edges

Remco van der Hofstad et al.

Annals of Applied Probability2026https://doi.org/10.1214/25-aap2237article
ABDC A
Weight
0.50

Abstract

We identify the upper large deviation probability for the number of edges in scale-free geometric random graph models as the space volume goes to infinity. Our result covers the models of scale-free percolation, the Boolean model with heavy-tailed radius distribution, and the age-dependent random connection model. In all these cases the mechanism behind the large deviation is based on a condensation effect. Loosely speaking, the mechanism randomly selects a finite number of vertices and increases their power, so that they connect to a macroscopic number of vertices in the graph, while the other vertices retain a degree close to their expectation and thus make no more than the expected contribution to the large deviation event. We verify this intuition by means of limit theorems for the empirical distributions of degrees and edge lengths under the conditioning. We observe that at large finite volumes, the edge-length distribution splits into a bulk and travelling wave part of asymptotically positive proportions.

Open via your library →

Cite this paper

https://doi.org/https://doi.org/10.1214/25-aap2237

Or copy a formatted citation

@article{remco2026,
  title        = {{Condensation in scale-free geometric graphs with excess edges}},
  author       = {Remco van der Hofstad et al.},
  journal      = {Annals of Applied Probability},
  year         = {2026},
  doi          = {https://doi.org/https://doi.org/10.1214/25-aap2237},
}

Paste directly into BibTeX, Zotero, or your reference manager.

Flag this paper

Condensation in scale-free geometric graphs with excess edges

Flags are reviewed by the Arbiter methodology team within 5 business days.


Evidence weight

0.50

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.50 × 0.4 = 0.20
M · momentum0.50 × 0.15 = 0.07
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.