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This work addresses the mean-field limit of inertial particle systems with singular interactions in a perturbative regime around Gibbs equilibrium. We prove that small fluctuations around equilibrium are asymptotically governed by the…

Analysis of PDEs · Mathematics 2026-05-29 Mitia Duerinckx , Pierre-Emmanuel Jabin

Suppose $\{X_{t}:t\ge 0\}$ is a supercritical superprocess on a Luzin space $E$, with a non-local branching mechanism and probabilities $\mathbb{P}_{\delta_{x}}$, when initiated from a unit mass at $x\in E$. By ``supercritical", we mean…

Probability · Mathematics 2025-09-11 Ting Yang

Density fluctuations of expanding nuclear matter are studied within a mean-field model in which fluctuations are generated by an external stochastic field. Fluctuations develop about a mean one-body phase-space density corresponding to a…

Nuclear Theory · Physics 2016-09-08 F. Matera , A. Dellafiore , G. Fabbri

Stochastic fluctuations are central to the understanding of extinction dynamics. In the context of population models they allow for the description of the transition from the vicinity of a non-trivial fixed point of the deterministic…

Statistical Mechanics · Physics 2015-08-04 Claudia Cianci , Duccio Fanelli , Alan J. McKane

We study the effects of additive noise on traveling pulse solutions in spatially extended neural fields with linear adaptation. Neural fields are evolution equations with an integral term characterizing synaptic interactions between neurons…

Pattern Formation and Solitons · Physics 2014-01-03 Zachary P Kilpatrick , Gregory Faye

We consider the adjacency matrix $A$ of a large random graph and study fluctuations of the function $f_n(z,u)=\frac{1}{n}\sum_{k=1}^n\exp\{-uG_{kk}(z)\}$ with $G(z)=(z-iA)^{-1}$. We prove that the moments of fluctuations normalized by…

Mathematical Physics · Physics 2015-05-14 M. Shcherbina , B. Tirozzi

We review a recent approach to the mean-field limits in neural networks that takes into account the stochastic nature of input current and the uncertainty in synaptic coupling. This approach was proved to be a rigorous limit of the network…

Probability · Mathematics 2010-01-22 Jonathan Touboul , Bard Ermentrout , Olivier Faugeras , Bruno Cessac

Mathematical models of biological neural networks are associated to a rich and complex class of stochastic processes. In this paper, we consider a simple {\em plastic} neural network whose {\em connectivity/synaptic strength} $(W(t))$…

Probability · Mathematics 2021-06-30 Philippe Robert , Gaetan Vignoud

The observed magnetic field on the solar surface is characterized by a very complex spatial and temporal behavior. Although feature-tracking algorithms have allowed us to deepen our understanding of this behavior, subjectivity plays an…

We consider the asymptotic behaviour of the fluctuation process for large stochastic systems of interacting particles driven by both idiosyncratic and common noise with an interaction kernel \(k \in L^2(\R^d) \cap L^\infty(\R^d)\). Our…

Probability · Mathematics 2026-05-28 Paul Nikolaev

In this article, we consider the stochastic wave equation on $\mathbb{R}_{+} \times \mathbb{R}$, driven by a linear multiplicative space-time homogeneous Gaussian noise whose temporal and spatial covariance structures are given by locally…

Probability · Mathematics 2019-01-03 Raluca M. Balan , Lluís Quer-Sardanyons , Jian Song

We introduce the notion of a Young generating function for a probability measure on integer partitions. We use this object to characterize probability distributions over integer partitions satisfying a law of large numbers and those that…

Probability · Mathematics 2025-09-12 Gabriel Raposo

The random transitions of ion channels between conducting and non-conducting states generate a source of internal fluctuations in a neuron, known as channel noise. The standard method for modeling fluctuations in the states of ion channels…

Neurons and Cognition · Quantitative Biology 2011-04-27 Joshua H. Goldwyn , Nikita S. Imennov , Michael Famulare , Eric Shea-Brown

The Hawkes self-excited point process provides an efficient representation of the bursty intermittent dynamics of many physical, biological, geological and economic systems. By expressing the probability for the next event per unit time…

Statistical Mechanics · Physics 2020-09-23 Kiyoshi Kanazawa , Didier Sornette

We study the fluctuations of the area $A(t)= \int_0^t x(\tau)\, d\tau$ under a self-similar Gaussian process (SGP) $x(\tau)$ with Hurst exponent $H>0$ (e.g., standard or fractional Brownian motion, or the random acceleration process) that…

Statistical Mechanics · Physics 2022-06-10 Naftali R. Smith , Satya N. Majumdar

We present a detailed analysis of the dynamical regimes observed in a balanced network of identical Quadratic Integrate-and-Fire (QIF) neurons with a sparse connectivity for homogeneous and heterogeneous in-degree distribution. Depending on…

Neurons and Cognition · Quantitative Biology 2025-05-29 Matteo Di Volo , Marco Segneri , Denis Goldobin , Antonio Politi , Alessandro Torcini

Recently it has been shown that when an equation that allows so-called pulled fronts in the mean-field limit is modelled with a stochastic model with a finite number $N$ of particles per correlation volume, the convergence to the speed…

Statistical Mechanics · Physics 2009-11-07 Debabrata Panja

For a many-particle system with long-range interactions and evolving under stochastic dynamics, we study for the first time the out-of-equilibrium fluctuations of the work done on the system by a time-dependent external force. For…

Statistical Mechanics · Physics 2016-04-19 Shamik Gupta , Thierry Dauxois , Stefano Ruffo

We establish a way to handle main collective fluctuations in correlated quantum systems based on a Fluctuation Local Field concept. This technique goes beyond standard mean-field approaches, such as Hartree-Fock and dynamical mean-field…

Strongly Correlated Electrons · Physics 2021-01-04 Alexey N. Rubtsov , Evgeny A. Stepanov , Alexander I. Lichtenstein

We analyze nonequilibrium fluctuations of the averaging process on $\mathbb T_\varepsilon^d$, a continuous degenerate Gibbs sampler running over the edges of the discrete $d$-dimensional torus. We show that, if we start from a smooth…

Probability · Mathematics 2025-12-09 Federico Sau