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The Galton--Watson process is the simplest example of a branching process. The relationship between the offspring distribution, and, when the extinction occurs almost surely, the distribution of the total progeny is well known. In this…

Probability · Mathematics 2017-04-10 Claudio Macci , Barbara Pacchiarotti

We show that the classical Kolmogorov and Richardson scaling laws in fully developed turbulence are consistent with a random Gaussian force field. Numerical simulations of a shell model approximation to the Navier-Stokes equations suggest…

Chaotic Dynamics · Physics 2009-11-13 Mogens H. Jensen , Kim Sneppen , Luiza Angheluta

We develop a general mathematical framework to analyze scaling regimes and derive explicit analytic solutions for gradient flow (GF) in large learning problems. Our key innovation is a formal power series expansion of the loss evolution,…

Machine Learning · Computer Science 2026-02-05 Dmitry Yarotsky , Eugene Golikov , Yaroslav Gusev

We consider the Linear-Quadratic-Regulator (LQR) problem in terms of optimizing a real-valued matrix function over the set of feedback gains. Such a setup facilitates examining the implications of a natural initial-state independent…

Systems and Control · Electrical Eng. & Systems 2019-07-31 Jingjing Bu , Afshin Mesbahi , Maryam Fazel , Mehran Mesbahi

We prove a large deviation principle for stochastic differential equations driven by semimartingales, with additive controls. Conditions are given in terms of characteristics of driven semimartingales, so that if the noise-control pairs…

Probability · Mathematics 2024-08-13 Qiao Huang , Wei Wei , Jinqiao Duan

In this paper we present a dynamical system to generate Brownian motion based on the Langevin equation without stochastic term and using fractional derivatives, i.e., a deterministic Brownian motion model is proposed. The stochastic process…

Chaotic Dynamics · Physics 2018-05-09 H. E. Gilardi-Velázquez , E. Campos-Cantón

Conditional independence and graphical models are crucial concepts for sparsity and statistical modeling in higher dimensions. For L\'evy processes, a widely applied class of stochastic processes, these notions have not been studied. By the…

Statistics Theory · Mathematics 2024-11-13 Sebastian Engelke , Jevgenijs Ivanovs , Jakob D. Thøstesen

We study stochastic particle systems on a complete graph and derive effective mean-field rate equations in the limit of diverging system size, which are also known from cluster aggregation models. We establish the propagation of chaos under…

Probability · Mathematics 2021-07-21 Watthanan Jatuviriyapornchai , Stefan Grosskinsky

We use a semi-Markov process method to calculate large deviations of counting statistics for three open quantum systems, including a resonant two-level system and resonant three-level systems in the $\Lambda$- and $V$-configurations. In the…

Statistical Mechanics · Physics 2023-12-15 Fei Liu

Study of random networks generally requires the nodes to be independently and uniformly distributed such as a Poisson point process. In this work, we venture beyond this standard paradigm and investigate a stochastic forest obtained from a…

Probability · Mathematics 2023-02-28 Rahul Roy , Kumarjit Saha , Anish Sarkar

This work presents a unified viscoelastic-viscoplastic continuum framework for modeling rate-dependent granular flows across regimes. The formulation incorporates two distinct rate-dependent mechanisms, namely micro-inertia and viscoelastic…

Soft Condensed Matter · Physics 2026-04-28 Bodhinanda Chandra , Sachith Dunatunga , Ken Kamrin

We study lower large deviations for the current of totally asymmetric zero-range processes on a ring with concave current-density relation. We use an approach by Jensen and Varadhan which has previously been applied to exclusion processes,…

Statistical Mechanics · Physics 2021-07-21 Paul Chleboun , Stefan Grosskinsky , Andrea Pizzoferrato

The static QCD force from the lattice can be used to extract $\Lambda_{\overline{\textrm{MS}}}$, which determines the running of the strong coupling. Usually, this is done with a numerical derivative of the static potential. However, this…

High Energy Physics - Lattice · Physics 2024-09-09 Nora Brambilla , Viljami Leino , Julian Mayer-Steudte , Antonio Vairo

In this work, a stochastic representation based on a physical transport principle is proposed to account for mesoscale eddy effects on the large-scale oceanic circulation. This stochastic framework arises from a decomposition of the…

Geophysics · Physics 2022-07-26 Long Li , Bruno Deremble , Noé Lahaye , Etienne Mémin

This paper is concerned with the large deviation principle of the non-local fractional stochastic reaction-diffusion equation with a polynomial drift of arbitrary degree driven by multiplicative noise defined on unbounded domains. We first…

Probability · Mathematics 2023-05-23 Bixiang Wang

This paper provides a large deviation principle for Non-Markovian, Brownian motion driven stochastic differential equations with random coefficients. Similar to Gao and Liu \cite{GL}, this extends the corresponding results collected in…

Probability · Mathematics 2014-07-22 Jin Ma , Zhenjie Ren , Nizar Touzi , Jianfeng Zhang

Rheological properties of dense flows of hard particles are singular as one approaches the jamming threshold where flow ceases, both for aerial granular flows dominated by inertia, and for over-damped suspensions. Concomitantly, the…

Soft Condensed Matter · Physics 2015-06-17 E. DeGiuli , G. Düring , E. Lerner , M. Wyart

Small nonequelibrium systems driven by an external periodic protocol can be described by Markov processes with time-periodic transition rates. In general, current fluctuations in such small systems are large and may play a crucial role. We…

Statistical Mechanics · Physics 2018-06-21 Andre C Barato , Raphael Chetrite

We investigate the non-equilibrium large deviations function of the particle densities in two steady-state driven systems exchanging particles at a vanishing rate. We first derive through a systematic multi-scale analysis the coarse-grained…

Statistical Mechanics · Physics 2020-08-26 Jules Guioth , Éric Bertin

We study large deviations for the current of one-dimensional stochastic particle systems with periodic boundary conditions. Following a recent approach based on an earlier result by Jensen and Varadhan, we compare several candidates for…

Statistical Mechanics · Physics 2018-10-02 Paul Chleboun , Stefan Grosskinsky , Andrea Pizzoferrato