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We prove a Large Deviation Principle for {\color{blue} jump-Markov } Processes on sparse large disordered network with disordered connectivity. The network is embedded in a geometric space, with the probability of a connection a (scaled)…

Probability · Mathematics 2026-02-02 James MacLaurin

Quantum walks provide a natural framework to approach graph problems with quantum computers, exhibiting speedups over their classical counterparts for tasks such as the search for marked nodes or the prediction of missing links.…

Quantum Physics · Physics 2023-06-27 Duarte Magano , João Moutinho , Bruno Coutinho

Nature is pervaded with oscillatory dynamics. In networks of coupled oscillators patterns can arise when the system synchronizes to an external input. Hence, these networks provide processing and memory of input. We present a universal…

Machine Learning · Computer Science 2025-06-23 Thomas Geert de Jong , Hirofumi Notsu , Kohei Nakajima

This paper presents a new variable selection approach integrated with Gaussian process (GP) regression. We consider a sparse projection of input variables and a general stationary covariance model that depends on the Euclidean distance…

Machine Learning · Computer Science 2020-08-26 Chiwoo Park , David J. Borth , Nicholas S. Wilson , Chad N. Hunter

We prove limit theorems for systems of interacting diffusions on sparse graphs. For example, we deduce a hydrodynamic limit and the propagation of chaos property for the stochastic Kuramoto model with interactions determined by…

Probability · Mathematics 2020-01-01 Roberto I. Oliveira , Guilherme H. Reis , Lucas M. Stolerman

We study two intertwined globally coupled networks of noisy Kuramoto phase oscillators that have the same natural frequency, but differ in their perception of the mean field and their contribution to it. Such a give-and-take mechanism is…

Adaptation and Self-Organizing Systems · Physics 2015-06-25 Bernard Sonnenschein , Thomas K. DM. Peron , Francisco A. Rodrigues , Jürgen Kurths , Lutz Schimansky-Geier

We investigate different mean-field-like approximations for stochastic dynamics on graphs, within the framework of a cluster-variational approach. In analogy with its equilibrium counterpart, this approach allows one to give a unified view…

Statistical Mechanics · Physics 2017-07-31 Alessandro Pelizzola , Marco Pretti

We report about the main dynamical features of a model of leaky-integrate-and fire excitatory neurons with short term plasticity defined on random massive networks. We investigate the dynamics by a Heterogeneous Mean-Field formulation of…

Disordered Systems and Neural Networks · Physics 2015-06-22 Matteo di Volo , Raffaella Burioni , Mario Casartelli , Roberto Livi , Alessandro Vezzani

Dynamic networks models describe a growing number of important scientific processes, from cell biology and epidemiology to sociology and finance. There are many aspects of dynamical networks that require statistical considerations. In this…

Methodology · Statistics 2012-05-15 E. C. Wit , A. Abbruzzo

The synchronization pattern of a fully connected competing Kuramoto model with a uniform intrinsic frequency distribution $g(\omega)$ was recently considered. This competing Kuramoto model assigns two coupling constants with opposite signs,…

Statistical Mechanics · Physics 2020-09-04 Jinha Park , B. Kahng

We analyze how the transient dynamics of large dynamical systems in the vicinity of a stationary point, modeled by a set of randomly coupled linear differential equations, depends on the network topology. We characterize the transient…

Adaptation and Self-Organizing Systems · Physics 2024-01-17 Wojciech Tarnowski , Izaak Neri , Pierpaolo Vivo

Based on dynamical cavity method, we propose an approach to the inference of kinetic Ising model, which asks to reconstruct couplings and external fields from given time-dependent output of original system. Our approach gives an exact…

Statistical Mechanics · Physics 2012-07-24 Pan Zhang

We derive exact equations that determine the spectra of undirected and directed sparsely connected regular graphs containing loops of arbitrary length. The implications of our results to the structural and dynamical properties of networks…

Statistical Mechanics · Physics 2011-12-07 F. L. Metz , I. Neri , D. Bollé

Representations based on random walks can exploit discrete data distributions for clustering and classification. We extend such representations from discrete to continuous distributions. Transition probabilities are now calculated using a…

Machine Learning · Computer Science 2012-12-12 Chen-Hsiang Yeang , Martin Szummer

Sparse networks can be found in a wide range of applications, such as biological and communication networks. Inference of such networks from data has been receiving considerable attention lately, mainly driven by the need to understand and…

Systems and Control · Electrical Eng. & Systems 2024-12-20 Junyang Jin , Ye Yuan , Jorge Goncalves

Sharp-momentum transition matrix elements for scattering from a short-range Gaussian potential are computed using a real-time path integral. The computation is based on a numerical implementation of a new interpretation of the path integral…

High Energy Physics - Lattice · Physics 2018-09-10 W. N. Polyzou , Ekaterina Nathanson

Employing the Kuramoto model as an illustrative example, we show how the use of the mean field approximation can be applied to large networks of phase oscillators with assortativity. We then use the ansatz of Ott and Antonsen [Chaos 19,…

Chaotic Dynamics · Physics 2014-11-05 Juan G. Restrepo , Edward Ott

We investigate the statistics of fluctuations in a classical stochastic network of nodes joined by connectors. The nodes carry generalized charge that may be randomly transferred from one node to another. Our goal is to find the time…

Mesoscale and Nanoscale Physics · Physics 2009-11-10 Andrew N. Jordan , Eugene V. Sukhorukov , Sebastian Pilgram

We study the response of an ensemble of synchronized phase oscillators to an external harmonic perturbation applied to one of the oscillators. Our main goal is to relate the propagation of the perturbation signal to the structure of the…

Statistical Mechanics · Physics 2009-11-10 D. H. Zanette

Collective dynamics on small-world networks emerge in a broad range of systems with their spectra characterizing fundamental asymptotic features. Here we derive analytic mean field predictions for the spectra of small-world models that…

Physics and Society · Physics 2015-06-30 Carsten Grabow , Stefan Grosskinsky , Marc Timme
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