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Related papers: Competition of Branches

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We analyze the bifurcation phenomenon for the following two-component competition system: \begin{equation*} \begin{cases} -\Delta u_1=\mu u_1(1-u_1)-\beta \alpha u_1u_2,& \text{in}\ B_1\subset \mathbb{R}^N, -\Delta u_2=\sigma…

Analysis of PDEs · Mathematics 2024-04-23 Zaizheng Li , Susanna Terracini

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

Real networks often grow through the sequential addition of new nodes that connect to older ones in the graph. However, many real systems evolve through the branching of fundamental units, whether those be scientific fields, countries, or…

Physics and Society · Physics 2020-06-30 Muhua Zheng , Guillermo García-Pérez , Marián Boguñá , M. Ángeles Serrano

We elaborate on the recently proposed static brane world scenario, where the effective 4-D cosmological constant is exponentially small when parallel 3-branes are far apart. We extend this result to a compactified model with two positive…

High Energy Physics - Theory · Physics 2009-10-31 Eanna Flanagan , Nicholas Jones , Horace Stoica , S. -H. Henry Tye , Ira Wasserman

We propose a theoretical model for branching instabilities in 2-dimensional fracture, offering predictions for when crack branching occurs, how multiple cracks develop, and what is the geometry of multiple branches. The model is based on…

Materials Science · Physics 2009-11-10 Eran Bouchbinder , Joachim Mathiesen , Itamar Procaccia

Criticality can be exactly demonstrated in certain models of brain activity, yet it remains challenging to identify in empirical data. We trained a fully connected deep neural network to learn the phases of an excitable model unfolding on…

Neurons and Cognition · Quantitative Biology 2022-06-13 Hernan Bocaccio , Enzo Tagliazucchi

We propose a simple model that aims at describing, in a stylized manner, how local breakdowns due unbalances or congestion propagate in real dynamical networks. The model converges to a self-organized critical stationary state in which the…

Statistical Mechanics · Physics 2007-05-23 Ginestra Bianconi , Matteo Marsili

We present an interacting branching model of neural network dynamics, incorporating key biological features such as inhibition with several types of inhibitory interactions. We establish a hierarchy of analytical mean-field approximations…

Disordered Systems and Neural Networks · Physics 2025-12-29 Jeremy B. Goetz , Naruepon Weerawongphrom , Rashid V. Williams-García , John M. Beggs , Gerardo Ortiz

Diffusion models (DMs) are a powerful generative framework that have attracted significant attention in recent years. However, the high computational cost of training DMs limits their practical applications. In this paper, we start with a…

Machine Learning · Computer Science 2024-04-12 Tianshuo Xu , Peng Mi , Ruilin Wang , Yingcong Chen

In a recent paper by Cabrera et al (Chaos, Solitons and Fractals 2021 146 110876), a linearization of DRM differences equation, (Delayed Regulation Model), has been proposed as a scheme to explain transfer of energy through different scales…

Statistical Mechanics · Physics 2023-09-07 Juan S. Medina-Alvarez

The emergence of and transitions between distinct phenotypes in isogenic cells can be attributed to the intricate interplay of epigenetic marks, external signals, and gene regulatory elements. These elements include chromatin remodelers,…

Molecular Networks · Quantitative Biology 2022-10-19 M. Ali Al-Radhawi , Shubham Tripathi , Yun Zhang , Eduardo D. Sontag , Herbert Levine

We study the Bolker-Pacala-Dieckmann-Law (BPDL) model of population dynamics in the regime of large population density. The BPDL model is a particle system in which particles reproduce, move randomly in space, and compete with each other…

Probability · Mathematics 2024-09-17 Pascal Maillard , Sarah Penington

Directed Percolation (DP) is a classic model for nonequilibrium phase transitions into a single absorbing state (fixation). It has been extensively studied by analytical and numerical techniques in diverse contexts. Recently, DP has…

Statistical Mechanics · Physics 2019-05-01 Jordan M. Horowitz , Mehran Kardar

A dynamical mechanism for symmetry breaking is investigated under the circumstances with the finite curvature, finite size and non-trivial topology. A four- and eight-fermion interaction model is considered as a prototype model which…

High Energy Physics - Phenomenology · Physics 2015-05-18 Masako Hayashi , Tomohiro Inagaki

Different branching and annihilating random walk models are investigated by cluster mean-field method and simulations in one and two dimensions. In case of the A -> 2A, 2A -> 0 model the cluster mean-field approximations show diffusion…

Statistical Mechanics · Physics 2009-11-10 Geza Odor

In this note, we recall the definition of the binary branching model with Moran type interactions (BBMMI) introduced in [8]. In this interacting particle system, particles evolve, reproduce and die independently and, with a probability that…

Probability · Mathematics 2025-01-31 A M G Cox , E Horton , D Villemonais

We study dielectric breakdown in a semi-classical bond percolation model for nonlinear composite materials introduced by us and the related breakdown exponent near the percolation threshold in two dimensions. The breakdown exponent after…

Condensed Matter · Physics 2015-06-25 Abhijit Kar Gupta , Asok K. Sen

The canonical phase diagram of the Blume-Emery-Griffiths (BEG) model with infinite-range interactions is known to exhibit a fourth order critical point at some negative value of the bi-quadratic interaction $K<0$. Here we study the…

Statistical Mechanics · Physics 2021-09-10 V. V. Prasad , Alessandro Campa , David Mukamel , Stefano Ruffo

Deep learning approaches such as convolutional neural nets have consistently outperformed previous methods on challenging tasks such as dense, semantic segmentation. However, the various proposed networks perform differently, with behaviour…

Computer Vision and Pattern Recognition · Computer Science 2017-11-07 Konstantinos Kamnitsas , Wenjia Bai , Enzo Ferrante , Steven McDonagh , Matthew Sinclair , Nick Pawlowski , Martin Rajchl , Matthew Lee , Bernhard Kainz , Daniel Rueckert , Ben Glocker

Deterministic classical cellular automata can be in two phases, depending on how irreversible the dynamical rules are. In the strongly irreversible phase, trajectories with different initial conditions coalesce quickly, while in the weakly…

Statistical Mechanics · Physics 2026-03-25 Adam Nahum , Sthitadhi Roy