activity
20132026
most citedScale-free Networks Well Done

168 citations · 236 across the 16 of their papers we have counts for

collaborators

19 papers

math.PR2026

Limiting Behavior of Degree-Degree Metrics under Local Convergence in Probability

Andrei-Eugeniu Patularu, Pim van der Hoorn

This paper investigates the limiting behaviour of degree-degree correlation metrics for sequences of random graphs under a general assumption of local convergence in probability. W…

math.PR2025

Flexible random graph modeling for cell-cell interactions

Mike van Santvoort, Pim van der Hoorn

In this paper we explore generalisations to a random digraph model designed for modelling cell-cell interactions (RaCInG). In its baseline model -- tested both theoretically and in…

math.PR2024

Condensation in scale-free geometric graphs with excess edges

Remco van der Hofstad, Pim van der Hoorn, Céline Kerriou +2

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 mo…

cond-mat.stat-mech2024

A Graph Random Walk Method for Calculating Time-of-Flight Charge Mobility in Organic Semiconductors from Multiscale Simulations

Zhongquan Chen, Pim van der Hoorn, Björn Baumeier

We present a graph random walk (GRW) method for the study of charge transport properties of complex molecular materials in the time-of-flight regime. The molecules forming the mate…

math.PR2023★ 1 cited

From inhomogeneous random digraphs to random graphs with fixed arc counts

Mike van Santvoort, Pim van der Hoorn

Consider a random graph model with vertices where each vertex has a vertex-type drawn from some discrete distribution. Suppose that the number of arcs to be placed between each…

physics.soc-ph2023★ 1 cited

Nearest-neighbour directed random hyperbolic graphs

I. A. Kasyanov, P. van der Hoorn, D. Krioukov +1

Undirected hyperbolic graph models have been extensively used as models of scale-free small-world networks with high clustering coefficient. Here we presented a simple directed hyp…

math.PR2022★ 6 cited

Scaling of the clustering function in spatial inhomogeneous random graphs

Remco van der Hofstad, Pim van der Hoorn, Neeladri Maitra

We consider an infinite spatial inhomogeneous random graph model with an integrable connection kernel that interpolates nicely between existing spatial random graph models. Key exa…

physics.soc-ph2022★ 9 cited

Entropy of labeled versus unlabeled networks

Jeremy Paton, Harrison Hartle, Huck Stepanyants +2

The structure of a network is an unlabeled graph, yet graphs in most models of complex networks are labeled by meaningless random integers. Is the associated labeling noise always…

math.PR2021★ 2 cited

Local limits of spatial inhomogeneous random graphs

Remco van der Hofstad, Pim van der Hoorn, Neeladri Maitra

Consider a set of vertices, where each vertex has a location in that is sampled uniformly from the unit cube in , and a weight associated to it. Co…

math.PR2020★ 8 cited

Ollivier curvature of random geometric graphs converges to Ricci curvature of their Riemannian manifolds

Pim van der Hoorn, Gabor Lippner, Carlo Trugenberger +1

Curvature is a fundamental geometric characteristic of smooth spaces. In recent years different notions of curvature have been developed for combinatorial discrete objects such as…

math.PR2020

Clustering in a hyperbolic model of complex networks

Nikolaos Fountoulakis, Pim van der Hoorn, Tobias Müller +1

In this paper we consider the clustering coefficient and clustering function in a random graph model proposed by Krioukov et al.~in 2010. In this model, nodes are chosen randomly i…

physics.soc-ph2018★ 168 cited

Scale-free Networks Well Done

Ivan Voitalov, Pim van der Hoorn, Remco van der Hofstad +1

We bring rigor to the vibrant activity of detecting power laws in empirical degree distributions in real-world networks. We first provide a rigorous definition of power-law distrib…

math.PR2017

Limit theorems for assortativity and clustering in null models for scale-free networks

Remco van der Hofstad, Pim van der Hoorn, Nelly Litvak +1

An important problem in modeling networks is how to generate a randomly sampled graph with given degrees. A popular model is the configuration model, a network with assigned degree…

math.PR2017★ 27 cited

Sparse Maximum-Entropy Random Graphs with a Given Power-Law Degree Distribution

Pim van der Hoorn, Gabor Lippner, Dmitri Krioukov

Even though power-law or close-to-power-law degree distributions are ubiquitously observed in a great variety of large real networks, the mathematically satisfactory treatment of r…

math.PR2017★ 3 cited

Average nearest neighbor degrees in scale-free networks

Dong Yao, Pim van der Hoorn, Nelly Litvak

The average nearest neighbor degree (ANND) of a node of degree is widely used to measure dependencies between degrees of neighbor nodes in a network. We formally analyze ANND i…

math.PR2015

Typical distances in the directed configuration model

Pim van der Hoorn, Mariana Olvera-Cravioto

We analyze the distribution of the distance between two nodes, sampled uniformly at random, in digraphs generated via the directed configuration model, in the supercritical regime.…

math.PR2015

Upper bounds for number of removed edges in the Erased Configuration Model

Pim van der Hoorn, Nelly Litvak

Models for generating simple graphs are important in the study of real-world complex networks. A well established example of such a model is the erased configuration model, where e…

physics.soc-ph2015★ 10 cited

Phase transitions for scaling of structural correlations in directed networks

Pim van der Hoorn, Nelly Litvak

Analysis of degree-degree dependencies in complex networks, and their impact on processes on networks requires null models, i.e. models that generate uncorrelated scale-free networ…

math.PR2013★ 1 cited

Degree-degree dependencies in directed networks with heavy-tailed degrees

Pim van der Hoorn, Nelly Litvak

In network theory, Pearson's correlation coefficients are most commonly used to measure the degree assortativity of a network. We investigate the behavior of these coefficients in…