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We define a dynamic model of random networks, where new vertices are connected to old ones with a probability proportional to a sublinear function of their degree. We first give a strong limit law for the empirical degree distribution, and…

Probability · Mathematics 2008-07-31 Steffen Dereich , Peter Morters

Preferential attachment networks are a type of random network where new nodes are connected to existing ones at random, and are more likely to connect to those that already have many connections. We investigate further a family of models…

Probability · Mathematics 2021-07-28 Ben Andrews , Jonathan Jordan

We analyze a dynamic random undirected graph in which newly added vertices are connected to those already present in the graph either using, with probability $p$, an anti-preferential attachment mechanism or, with probability $1-p$, a…

Probability · Mathematics 2020-12-11 Umberto De Ambroggio , Federico Polito , Laura Sacerdote

Consider the multicolored urn model where, after every draw, balls of the different colors are added to the urn in a proportion determined by a given stochastic replacement matrix. We consider some special replacement matrices which are not…

Probability · Mathematics 2009-02-09 Arup Bose , Amites Dasgupta , Krishanu Maulik

Edge expansion is a parameter indicating how well-connected a graph is. It is useful for designing robust networks, analysing random walks or information flow through a network and is an important notion in theoretical computer science.…

Probability · Mathematics 2026-01-12 Colin McDiarmid , Katarzyna Rybarczyk , Fiona Skerman , Małgorzata Sulkowska

In this paper, we consider a multi-drawing urn model with random addition. At each discrete time step, we draw a sample of m balls. According to the composition of the drawn colors, we return the balls together with a random number of balls…

Probability · Mathematics 2018-02-14 Rafik Aguech , Nabil Lasmar , Olfa Selmi

The S-metric has grown popular in network studies, as a measure of ``scale-freeness'' restricted to the collection G(D) of connected graphs with a common degree sequence D=(d_1,\ldots,d_n). The calculation of S depends on the maximum…

Combinatorics · Mathematics 2013-08-20 Jason Cory Brunson

We propose a preferential attachment model for network growth where new entering nodes have a partial information about the state of the network. Our main result is that the presence of bounded information modifies the degree distribution…

Physics and Society · Physics 2015-06-22 Timoteo Carletti , Floriana Gargiulo , Renaud Lambiotte

Preferential attachment lies at the heart of many network models aiming to replicate features of real world networks. To simulate the attachment process, conduct statistical tests, or obtain input data for benchmarks, efficient algorithms…

Data Structures and Algorithms · Computer Science 2023-01-18 Daniel Allendorf , Ulrich Meyer , Manuel Penschuck , Hung Tran

Consider a P\'olya urn with balls of several colours, where balls are drawn sequentially and each drawn ball immediately is replaced together with a fixed number of balls of the same colour. It is well-known that the proportions of balls of…

Probability · Mathematics 2020-11-25 Svante Janson

This paper provides time-dependent expressions for the expected degree distribution of a given network that is subject to growth, as a function of time. We consider both uniform attachment, where incoming nodes form links to existing nodes…

Statistical Mechanics · Physics 2013-12-16 Babak Fotouhi , Michael G. Rabbat

We provide a framework for modeling social network formation through conditional multinomial logit models from discrete choice and random utility theory, in which each new edge is viewed as a "choice" made by a node to connect to another…

Social and Information Networks · Computer Science 2020-05-22 Jan Overgoor , Austin R. Benson , Johan Ugander

We present a multiple colour generalisation of the model of graph interacting urns studied by Benaim et. al., Random Struct. Alg., 46: 614-634, 2015. We show that for complete graphs and for a broad class of reinforcement functions…

Probability · Mathematics 2025-05-29 Benito Pires , Rafael A. Rosales

Many networks exhibit scale free behavior where their degree distribution obeys a power law for large vertex degrees. Models constructed to explain this phenomena have relied on preferential attachment where the networks grow by the…

Physics and Society · Physics 2012-02-08 Vijay K Samalam

Suppose an urn contains initially any number of balls of two colours. One ball is drawn randomly and then put back with $\alpha$ balls of the same colour and $\beta$ balls of the opposite colour. Both cases, $\beta=0$ and $\beta>0$ are well…

Probability · Mathematics 2026-01-06 Raphael Alves , Rafael A. Rosales

Early investigation of P\'{o}lya urns considered drawing balls one at a time. In the last two decades, several authors considered multiple drawing in each step, but mostly for schemes on two colors. In this manuscript, we consider multiple…

Probability · Mathematics 2024-03-20 Joshua Sparks , Markus Kuba , Srinivasan Balaji , Hosam Mahmoud

A model named `Colored Percolation' has been introduced with its infinite number of versions in two dimensions. The sites of a regular lattice are randomly occupied with probability $p$ and are then colored by one of the $n$ distinct colors…

Statistical Mechanics · Physics 2017-09-13 Sumanta Kundu , S. S. Manna

We study an urn process with two urns, initialized with a ball each. Balls are added sequentially, the urn being chosen independently with probability proportional to the $\alpha^{th}$ power $(\alpha >1)$ of the existing number of balls. We…

Probability · Mathematics 2026-01-14 Svante Janson , Subhabrata Sen , Joel Spencer

In this paper, we prove functional limit theorems for P\'olya urn processes whose number of draws and initial number of balls tend to infinity together. This is motivated by recent work of Borovkov [5], where they prove a functional limit…

Probability · Mathematics 2022-06-13 Christopher B. C. Dean

Preferential attachment is a popular generative mechanism to explain the widespread observation of power law distributed networks. We introduce an alternative explanation for the phenomenon by allowing the link growth rates to vary across…

Physics and Society · Physics 2007-06-18 Birgitte Freiesleben de Blasio , Odd O Aalen
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