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We construct a class of superprocesses by taking the high density limit of a sequence of interacting-branching particle systems. The spatial motion of the superprocess is determined by a system of interacting diffusions, the branching…

Probability · Mathematics 2011-02-19 Donald A. Dawson , Zenghu Li , Hao Wang

There is a growing cross-disciplinary effort in the broad domain of optimization and learning with streams of data, applied to settings where traditional batch optimization techniques cannot produce solutions at time scales that match the…

Optimization and Control · Mathematics 2021-11-29 Emiliano Dall'Anese , Andrea Simonetto , Stephen Becker , Liam Madden

Point processes model the distribution of random point sets in mathematical spaces, such as spatial and temporal domains, with applications in fields like seismology, neuroscience, and economics. Existing statistical and machine learning…

Machine Learning · Computer Science 2024-10-31 David Lüdke , Enric Rabasseda Raventós , Marcel Kollovieh , Stephan Günnemann

Predicting the future behaviour of complex systems exhibiting critical-like dynamics is often considered to be an intrinsically hard task. Here, we study the predictability of the depinning dynamics of elastic interfaces in random media…

Statistical Mechanics · Physics 2026-02-03 Valtteri Haavisto , Marcin Mińkowski , Lasse Laurson

Two cellular automata models with directed mass flow and internal time scales are studied by numerical simulations. Relaxation rules are a combination of probabilistic critical height (probability of toppling $p$) and deterministic critical…

Statistical Mechanics · Physics 2009-10-31 Bosiljka Tadic

The collapse of interdependent networks, as well as similar avalanche phenomena, is driven by cascading failures. At the critical point, the cascade begins as a critical branching process, where each failing node (element) triggers, on…

Physics and Society · Physics 2025-04-10 Dolev Dilmoney , Bnaya Gross , Shlomo Havlin , Nadav M. Shnerb

Branch and bound algorithms have been developed for reliability analysis of coherent systems. They exhibit a set of advantages; in particular, they can find a computationally efficient representation of a system failure or survival event,…

Optimization and Control · Mathematics 2024-10-31 Ji-Eun Byun , Hyeuk Ryu , Daniel Straub

A cellular automaton model is presented for random walkers with biologically motivated interactions favoring local alignment and leading to collective motion or swarming behavior. The degree of alignment is controlled by a sensitivity…

Biological Physics · Physics 2009-10-30 H. J. Bussemaker , A. Deutsch , E. Geigant

Power law distributed fluctuations are known to accompany \emph{terminal} failure in disordered brittle solids. The associated intermittent scale-free behavior is of interest from the fundamental point of view as it emerges universally from…

Disordered Systems and Neural Networks · Physics 2021-10-19 Hudson Borja da Rocha , Lev Truskinovsky

Markov chain Monte Carlo (MCMC) methods are often used in clustering since they guarantee asymptotically exact expectations in the infinite-time limit. In finite time, though, slow mixing often leads to poor performance. Modern computing…

Methodology · Statistics 2022-02-24 Tin D. Nguyen , Brian L. Trippe , Tamara Broderick

Spontaneous structural rearrangements play a central role in the organization and function of complex biomolecular systems. In principle, physics-based computer simulations like Molecular Dynamics (MD) enable us to investigate these…

Quantum Physics · Physics 2026-03-19 Danial Ghamari , Philipp Hauke , Roberto Covino , Pietro Faccioli

Power-law-shaped avalanche-size distributions are widely used to probe for critical behavior in many different systems, particularly in neural networks. The definition of avalanche is ambiguous. Usually, theoretical avalanches are defined…

Biological Physics · Physics 2018-05-22 Mauricio Girardi-Schappo , Marcelo H. R. Tragtenberg

We study avalanche dynamics and local activity of forced-flow imbibition fronts in disordered media. We focus on the front dynamics as the mean velocity $\bar{v}$ of the interface is decreased and the pinning state is approached. Scaling…

Statistical Mechanics · Physics 2010-03-05 Marc Pradas , Juan M. López , A. Hernández-Machado

The origin of power-law distributions in self-organized criticality is investigated by treating the variation of the number of active sites in the system as a stochastic process. An avalanche is then regarded as a first-return random walk…

Statistical Mechanics · Physics 2009-11-10 C. B. Yang

Uncertainty analysis in the form of probabilistic forecasting can significantly improve decision making processes in the smart power grid when integrating renewable energy sources such as wind. Whereas point forecasting provides a single…

Signal Processing · Electrical Eng. & Systems 2019-09-27 Kostas Hatalis , Alberto J. Lamadrid , Katya Scheinberg , Shalinee Kishore

Spreading processes on networks are ubiquitous in both human-made and natural systems. Understanding their behavior is of broad interest; from the control of epidemics to understanding brain dynamics. While in some cases there exists a…

Statistical Mechanics · Physics 2021-06-23 Daniel J. Korchinski , Javier G. Orlandi , Seung-Woo Son , Jörn Davidsen

The branching process is the minimal model for propagation dynamics, avalanches and criticality, broadly used in neuroscience. A simple extension of it, adding inhibitory nodes, induces a much-richer phenomenology, including, an…

Statistical Mechanics · Physics 2022-07-08 Roberto Corral López , Victor Buendía , Miguel A. Muñoz

Within the framework of the random first-order transition theory of glasses, we discuss the statistics of thermal avalanches, the large scale rearrangements in driven amorphous systems near their instability. Stringy excitations yield…

Disordered Systems and Neural Networks · Physics 2026-03-05 Zhiyu Cao , Peter G. Wolynes

We derive a general formulation of the self-organized branching process by considering sandpile dynamics in an evolving population characterized by "birth" (excitation) and "death" (de-excitation) of active sites ($z=1$). New active sites…

Adaptation and Self-Organizing Systems · Physics 2007-05-23 D. E. Juanico , C. Monterola , C. Saloma

We study a neural network model of interacting stochastic discrete two--state cellular automata on a regular lattice. The system is externally tuned to a critical point which varies with the degree of stochasticity (or the effective…

Statistical Mechanics · Physics 2015-06-12 Kaustubh Manchanda , Avinash Chand Yadav , Ramakrishna Ramaswamy
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