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How do real graphs evolve over time? What are ``normal'' growth patterns in social, technological, and information networks? Many studies have discovered patterns in static graphs, identifying properties in a single snapshot of a large…

Physics and Society · Physics 2007-05-23 Jure Leskovec , Jon Kleinberg , Christos Faloutsos

The Lorentz mirror model provides a clean setting to study macroscopic transport generated solely by quenched environmental randomness. We introduce a hierarchical version whose distribution of left--right crossings satisfies an exact…

Statistical Mechanics · Physics 2026-03-05 Raphael Lefevere , Hal Tasaki

Recently, we developed a theory of a geometrically growing system. Here we show that the theory can explain some phenomena of power-law distribution including classical demographic and economic and novel pandemic instances, without…

Physics and Society · Physics 2023-02-28 Kim Chol-jun

In this paper we introduce a model of spatial network growth in which nodes are placed at randomly selected locations on a unit square in $\mathbb{R}^2$, forming new connections to old nodes subject to the constraint that edges do not…

Physics and Society · Physics 2016-02-12 Garvin Haslett , Seth Bullock , Markus Brede

Kinetically grown self-avoiding walks on various types of generalized random networks have been studied. Networks with short- and long-tailed degree distributions $P(k)$ were considered ($k$, degree or connectivity), including scale-free…

Disordered Systems and Neural Networks · Physics 2009-11-11 Carlos P. Herrero

Graph neural networks (GNNs) have shown promising results across various graph learning tasks, but they often assume homophily, which can result in poor performance on heterophilic graphs. The connected nodes are likely to be from different…

Machine Learning · Computer Science 2023-05-31 Kai Zhao , Qiyu Kang , Yang Song , Rui She , Sijie Wang , Wee Peng Tay

This work addresses the superdiffusive motion of a discrete time random walker on ordered discrete substrates and complex networks with the presence of long-range interactions (LRIs). In ordered regular lattices, where LRIs have a clear…

It is shown that there exists a sequence of 3-regular graphs $\{G_n\}_{n=1}^\infty$ and a Hadamard space $X$ such that $\{G_n\}_{n=1}^\infty$ forms an expander sequence with respect to $X$, yet random regular graphs are not expanders with…

Metric Geometry · Mathematics 2015-11-03 Manor Mendel , Assaf Naor

Let $G$ be a connected nonregular graphs of order $n$ with maximum degree $\Delta$ that attains the maximum spectral radius. Liu and Li (2008) proposed a conjecture stating that $G$ has a degree sequence $(\Delta,\ldots,\Delta,\delta)$ with…

Combinatorics · Mathematics 2024-11-27 Zejun Huang , Jiahui Liu , Chenxi Yang

Wireless network topologies change over time and maintaining routes requires frequent updates. Updates are costly in terms of consuming throughput available for data transmission, which is precious in wireless networks. In this paper, we…

Networking and Internet Architecture · Computer Science 2009-09-16 Dominique Tschopp , Suhas Diggavi , Matthias Grossglauser

Rank 1 inhomogeneous random graphs are a natural generalization of Erd\H{o}s R\'enyi random graphs. In this generalization each node is given a weight. Then the probability that an edge is present depends on the product of the weights of…

Probability · Mathematics 2021-07-28 Othmane Safsafi

We show that continuous random walks (diffusion) in the Poincar\'{e} hyperbolic upper halfplane $\mathbb{H}^2 = \{(x,y)|y>0\}$ provide a unifying description of three seemingly unrelated phenomena: (i) the non-analytic divergence of the…

Statistical Mechanics · Physics 2026-05-25 Daniil Fedotov , Sergei Nechaev

Let H(n) be the group of 3x3 uni-uppertriangular matrices with entries in Z/nZ, the integers mod n. We show that the simple random walk converges to the uniform distribution in order n^2 steps. The argument uses Fourier analysis and is…

Probability · Mathematics 2015-02-17 Daniel Bump , Persi Diaconis , Angela Hicks , Laurent Miclo , Harold Widom

Random walks are ubiquitous in the sciences, and they are interesting from both theoretical and practical perspectives. They are one of the most fundamental types of stochastic processes; can be used to model numerous phenomena, including…

Physics and Society · Physics 2020-04-13 Naoki Masuda , Mason A. Porter , Renaud Lambiotte

Diffusive dynamics abound in nature and have been especially studied in physical, biological, and financial systems. These dynamics are characterised by a linear growth of the mean squared displacement (MSD) with time. Often, the conditions…

Statistical Mechanics · Physics 2025-11-14 Alvaro Lanza , Xiang Qu , Stefano Bo

We analyse how simple local constraints in two dimensions lead a defect to exhibit robust, non-transient, and tunable, subdiffusion. We uncover a rich dynamical phenomenology realised in ice- and dimer-type models. On the microscopic scale…

Mesoscale and Nanoscale Physics · Physics 2025-04-02 Nilotpal Chakraborty , Markus Heyl , Roderich Moessner

Several kinds of walks on complex networks are currently used to analyze search and navigation in different systems. Many analytical and computational results are known for random walks on such networks. Self-avoiding walks (SAWs) are…

Disordered Systems and Neural Networks · Physics 2009-11-10 Carlos P. Herrero

In this paper, we are interested in the mixing behaviour of simple random walks on inhomogeneous directed graphs. We focus our study on the Chung-Lu digraph, which is an inhomogeneous network that generalizes the Erd\H{o}s-R\'enyi digraph.…

Probability · Mathematics 2024-09-25 Alessandra Bianchi , Giacomo Passuello

We analyze information diffusion using empirical data that tracks online communication around two instances of mass political mobilization, including the year that lapsed in-between the protests. We compare the global properties of the…

Physics and Society · Physics 2015-06-16 Raquel A. Baños , Javier Borge-Holthoefer , Ning Wang , Yamir Moreno , Sandra González-Bailón

Deeper modern architectures are costly to train, making hyperparameter transfer preferable to expensive repeated tuning. Maximal Update Parametrization ($\mu$P) helps explain why many hyperparameters transfer across width. Yet depth scaling…

Machine Learning · Computer Science 2026-02-10 Shenxi Wu , Haosong Zhang , Xingjian Ma , Shirui Bian , Yichi Zhang , Xi Chen , Wei Lin