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For critical bond-percolation on high-dimensional torus, this paper proves sharp lower bounds on the size of the largest cluster, removing a logarithmic correction in the lower bound in Heydenreich and van der Hofstad (2007). This…

Probability · Mathematics 2019-07-16 Markus Heydenreich , Remco van der Hofstad

We study site percolation on a sequence of graphs $\{G_n\}_{n\geq1}$ on $n$ vertices where degree of each vertex is in the interval $(np -a_n, np+a_n)$ and the co-degree of every pair of vertices is at most ${n}p^2+ b_n$, where $p \in…

Probability · Mathematics 2017-12-12 Suman Chakraborty

We propose and investigate a unifying class of sparse random graph models, based on a hidden coloring of edge-vertex incidences, extending an existing approach, Random graphs with a given degree distribution, in a way that admits a…

Statistical Mechanics · Physics 2009-11-10 Bo Söderberg

We study the last passage time in geometric last passage percolation (LPP). As the system size increases, we derive precise large deviation probabilities -- up to and including the constant terms -- for both the lower and upper tails. A key…

Probability · Mathematics 2025-10-21 Sung-Soo Byun , Christophe Charlier , Philippe Moreillon , Nick Simm

We study the spectrum of adjacency matrices of random graphs. We develop two techniques to lower bound the mass of the continuous part of the spectral measure or the density of states. As an application, we prove that the spectral measure…

Probability · Mathematics 2021-03-23 Charles Bordenave , Arnab Sen , Balint Virag

We consider robustness and percolation properties of the networks of networks, in which random nodes in different individual networks (layers) can be interdependent. We explore the emergence of the giant mutually connected component,…

Disordered Systems and Neural Networks · Physics 2014-11-18 Ginestra Bianconi , Sergey N. Dorogovtsev

Random graphs have played an instrumental role in modelling real-world networks arising from the internet topology, social networks, or even protein-interaction networks within cells. Percolation, on the other hand, has been the fundamental…

Probability · Mathematics 2018-09-12 Souvik Dhara

Preferential attachment schemes, where the selection mechanism is linear and possibly time-dependent, are considered, and an infinite-dimensional large deviation principle for the sample path evolution of the empirical degree distribution…

Probability · Mathematics 2013-02-25 Jihyeok Choi , Sunder Sethuraman

We consider a random object that is associated with both random walks and random media, specifically, the superposition of a configuration of subcritical Bernoulli percolation on an infinite connected graph and the trace of the simple…

Probability · Mathematics 2019-09-10 Kazuki Okamura

We study the asymptotics of large, moderate and normal deviations for the connected components of the sparse random graph by the method of stochastic processes. We obtain the logarithmic asymptotics of large deviations of the joint…

Probability · Mathematics 2007-05-23 Anatolii A. Puhalskii

The planar rigidity problem asks, given a set of m pairwise distances among a set P of n unknown points, whether it is possible to reconstruct P, up to a finite set of possibilities (modulo rigid motions of the plane). The celebrated…

Combinatorics · Mathematics 2008-12-05 Louis Theran

Boltzmann-Sanov and Cramer-Chernoff's theorems provide large deviation probabilities, entropy, and rate functions for the spatial distribution of systems and the total internal energy of an ensemble respectively. By the method of Lagrange's…

Statistical Mechanics · Physics 2021-09-17 D. P. Shinde

We study the percolation properties of graph partitioning on random regular graphs with N vertices of degree $k$. Optimal graph partitioning is directly related to optimal attack and immunization of complex networks. We find that for any…

Statistical Mechanics · Physics 2007-10-07 Gerald Paul , Reuven Cohen , Sameet Sreenivasan , Shlomo Havlin , H. Eugene Stanley

We present an analytical technique to compute the probability of rare events in which the largest eigenvalue of a random matrix is atypically large (i.e.\ the right tail of its large deviations). The results also transfer to the left tail…

Statistical Mechanics · Physics 2021-05-26 Antoine Maillard

Jigsaw percolation is a model for the process of solving puzzles within a social network, which was recently proposed by Brummitt, Chatterjee, Dey and Sivakoff. In the model there are two graphs on a single vertex set (the `people' graph…

Probability · Mathematics 2017-06-28 Béla Bollobás , Oliver Riordan , Erik Slivken , Paul Smith

We formulate and study a model for inhomogeneous long-range percolation on $\Zbold^d$. Each vertex $x\in\Zbold^d$ is assigned a non-negative weight $W_x$, where $(W_x)_{x\in\Zbold^d}$ are i.i.d.\ random variables. Conditionally on the…

Probability · Mathematics 2011-03-02 Maria Deijfen , Remco van der Hofstad , Gerard Hooghiemstra

The diffusion and bootstrap percolation models were studied in regular random and Erd\H{o}s-R\'{e}nyi networks using the modified Newman-Ziff algorithms. We calculated the percolation threshold and the order parameter of the percolation…

Statistical Mechanics · Physics 2022-02-18 Jeong-Ok Choi , Unjong Yu

\emph{Full-bond percolation} with parameter $p$ is the process in which, given a graph, for every edge independently, we delete the edge with probability $1-p$. Bond percolation is motivated by problems in mathematical physics and it is…

Probability · Mathematics 2022-05-23 Luca Becchetti , Andrea Clementi , Francesco Pasquale , Luca Trevisan , Isabella Ziccardi

Let G_n be a sequence of finite transitive graphs with vertex degree d=d(n) and |G_n|=n. Denote by p^t(v,v) the return probability after t steps of the non-backtracking random walk on G_n. We show that if p^t(v,v) has quasi-random…

Probability · Mathematics 2008-11-25 Asaf Nachmias

Graph neural networks can accurately predict the chemical properties of many molecular systems, but their suitability for large, macromolecular assemblies such as gels is unknown. Here, graph neural networks were trained and optimised for…

Computational Physics · Physics 2025-04-14 D. A. Head