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We generalize the technique of smoothed analysis to distributed algorithms in dynamic network models. Whereas standard smoothed analysis studies the impact of small random perturbations of input values on algorithm performance metrics,…

Distributed, Parallel, and Cluster Computing · Computer Science 2015-08-17 Michael Dinitz , Jeremy T. Fineman , Seth Gilbert , Calvin Newport

This paper revisits the classical concept of network modularity and its spectral relaxations used throughout graph data analysis. We formulate and study several modularity statistic variants for which we establish asymptotic distributional…

Methodology · Statistics 2024-02-26 Anirban Mitra , Konasale Prasad , Joshua Cape

An important source of high clustering coefficient in real-world networks is transitivity. However, existing approaches for modeling transitivity suffer from at least one of the following problems: i) they produce graphs from a specific…

Social and Information Networks · Computer Science 2022-12-30 Morteza Haghir Chehreghani , Mostafa Haghir Chehreghani

Complex systems are often modeled as Boolean networks in attempts to capture their logical structure and reveal its dynamical consequences. Approximating the dynamics of continuous variables by discrete values and Boolean logic gates may,…

Molecular Networks · Quantitative Biology 2013-05-29 Johannes Norrell , Joshua E. S. Socolar

Near equilibrium, small current fluctuations are described by a Gaussian with a linear-response variance regulated by the dissipation. Here, we demonstrate that dissipation still plays a dominant role in structuring large fluctuations…

Statistical Mechanics · Physics 2016-03-30 Todd R. Gingrich , Jordan M. Horowitz , Nikolay Perunov , Jeremy England

We demonstrate that the self-similarity of some scale-free networks with respect to a simple degree-thresholding renormalization scheme finds a natural interpretation in the assumption that network nodes exist in hidden metric spaces.…

Disordered Systems and Neural Networks · Physics 2008-12-03 M. Angeles Serrano , Dmitri Krioukov , Marian Boguna

In studies of complex heterogeneous networks, particularly of the Internet, significant attention was paid to analyzing network failures caused by hardware faults or overload, where the network reaction was modeled as rerouting of traffic…

Networking and Internet Architecture · Computer Science 2015-05-30 A. S. Stepanenko , I. V. Yurkevich , C. C. Constantinou , I. V. Lerner

The fluctuation-dissipation (F-D) theorem is a fundamental result for systems near thermodynamic equilibrium, and justifies studies between microscopic and macroscopic properties. It states that the nonequilibrium relaxation dynamics is…

Statistical Mechanics · Physics 2015-03-13 Jianhua Xing

A recently developed wavelet based approach is employed to characterize the scaling behavior of spectral fluctuations of random matrix ensembles, as well as complex atomic systems. Our study clearly reveals anti-persistent behavior and…

Chaotic Dynamics · Physics 2009-11-11 P. Manimaran , Prasanta K. Panigrahi , P. Anantha Lakshmi

Turbulence exhibits significant velocity fluctuations even if the scale is much larger than the scale of the energy supply. Since any spatial correlation is negligible, these large-scale fluctuations have many degrees of freedom and are…

Fluid Dynamics · Physics 2015-05-20 H. Mouri , A. Hori , Y. Kawashima , K. Hashimoto

The Reynolds stress, or equivalently the average of the momentum flux, is key to understanding the statistical properties of turbulent flows. Both typical and rare fluctuations of the time averaged momentum flux are needed to fully…

Fluid Dynamics · Physics 2018-02-12 Freddy Bouchet , J. B. Marston , T. Tangarife

Many widely studied graphical models with latent variables lead to nontrivial constraints on the distribution of the observed variables. Inspired by the Bell inequalities in quantum mechanics, we refer to any linear inequality whose…

Artificial Intelligence · Computer Science 2011-07-21 Greg Ver Steeg , Aram Galstyan

There is an abundance of literature on complex networks describing a variety of relationships among units in social, biological, and technological systems. Such networks, consisting of interconnected nodes, are often self-organized,…

Adaptation and Self-Organizing Systems · Physics 2011-08-18 Paul J. Laurienti , Karen E. Joyce , Qawi K. Telesford , Jonathan H. Burdette , Satoru Hayasaka

Random constraint satisfaction problems undergo several phase transitions as the ratio between the number of constraints and the number of variables is varied. When this ratio exceeds the satisfiability threshold no more solutions exist;…

Disordered Systems and Neural Networks · Physics 2017-06-22 Alfredo Braunstein , Luca Dall'Asta , Guilhem Semerjian , Lenka Zdeborova

We address the question of condensation and extremes for three classes of intimately related stochastic processes: (a) random allocation models and zero-range processes, (b) tied-down renewal processes, (c) free renewal processes. While for…

Statistical Mechanics · Physics 2021-02-03 Claude Godrèche

Self-organized network dynamics prevails for systems across physics, biology and engineering. How external signals generate distributed responses in networked systems fundamentally underlies their function, yet is far from fully understood.…

Adaptation and Self-Organizing Systems · Physics 2019-08-05 Xiaozhu Zhang , Sarah Hallerberg , Moritz Matthiae , Dirk Witthaut , Marc Timme

This article is the first in a series of three papers investigating the detailed geometry of river networks. Large-scale river networks mark an important class of two-dimensional branching networks, being not only of intrinsic interest but…

Geophysics · Physics 2013-05-29 Peter Sheridan Dodds , Daniel H. Rothman

In various situations where wave transport is preeminent, like in wireless communication, a strong established transmission is present in a complex scattering environment. We develop a novel approach to describe emerging fluctuations, which…

Mesoscale and Nanoscale Physics · Physics 2020-10-08 Dmitry V. Savin , Martin Richter , Ulrich Kuhl , Olivier Legrand , Fabrice Mortessagne

Inhomogeneous random graphs are fundamental models for real-world networks, where prescribed degrees are imposed as soft constraints. A common assumption in such models is that the degree distribution follows a power-law, capturing the…

Probability · Mathematics 2026-03-09 Riccardo Michielan , Clara Stegehuis , Bert Zwart

The identification of the limiting factors in the dynamical behavior of complex systems is an important interdisciplinary problem which often can be traced to the spectral properties of an underlying network. By deriving a general relation…

Disordered Systems and Neural Networks · Physics 2007-07-03 Adilson E. Motter