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In this paper we construct a new type of noise of fractional nature that has a strong regularizing effect on differential equations. We consider an equation with this noise with a highly irregular coefficient. We employ a new method to…

Functional Analysis · Mathematics 2018-06-26 Oussama Amine , David Baños , Frank Proske

In this work, we consider a wide two-layer neural network and study the behavior of its empirical weights under a dynamics set by a stochastic gradient descent along the quadratic loss with mini-batches and noise. Our goal is to prove a…

Probability · Mathematics 2023-03-02 Arnaud Descours , Arnaud Guillin , Manon Michel , Boris Nectoux

We present an application of Large Deviation Theory to the problem of structure growth on large-scale structure cosmology. Starting from gaussian distributed overdensities on concentric spherical shells, we show that a Large Deviation…

Cosmology and Nongalactic Astrophysics · Physics 2016-09-21 Francis Bernardeau , Paulo Reimberg

In equilibrium, the Mermin-Wagner theorem prohibits the continuous symmetry breaking for all dimensions $d\leq 2$. In this work, we discuss that this limitation can be circumvented in non-equilibrium systems driven by the spatio-temporally…

Statistical Mechanics · Physics 2023-12-27 Harukuni Ikeda

We establish the large deviations principle (LDP) and the moderate deviations principle (MDP) and an almost sure version of the central limit theorem (CLT) for the stochastic 3D viscous primitive equations driven by a multiplicative white…

Probability · Mathematics 2020-10-27 Jakub Slavík

In this work we study permanence of hyperbolicity for autonomous differential equations under nonautonomous random/stochastic perturbations. For the linear case, we study robustness and existence of exponential dichotomies for nonautonomous…

Analysis of PDEs · Mathematics 2021-04-06 Tomás Caraballo , Alexandre N. de Carvalho , José A. Langa , Alexandre N. Oliveira-Sousa

This paper is devoted to investigating the random dynamics of stochastic discrete long-wave-short-wave resonance equations, which are characterized by the following features: $(1)$ the equations contain locally Lipschitz nonlinear coupling…

Probability · Mathematics 2026-03-18 Xia Pan , Jianhua Huang , Juntao Wu , Jiangwei Zhang

We consider a system of stochastic Allen-Cahn equations on a finite network represented by a finite graph. On each edge in the graph a multiplicative Gaussian noise driven stochastic Allen-Cahn equation is given with possibly different…

Analysis of PDEs · Mathematics 2021-04-28 Mihály Kovács , Eszter Sikolya

We study the large deviations principle (LDP) for stationary solutions of a class of stochastic differential equations (SDE) in infinite time intervals by the weak convergence approach, and then establish the LDP for the invariant measures…

Probability · Mathematics 2022-06-07 Peipei Gao , Yong Liu , Yue Sun , Zuohuan Zheng

We study the the sharp interface limit of $\varepsilon$-dependent two dimensional stochastic Cahn-Hilliard equation driven by space-time white noise and conservative noise as $\varepsilon\to 0$. In the case when the noise is sufficiently…

Probability · Mathematics 2019-11-04 Lubomir Banas , Huanyu Yang and , Rongchan Zhu

In this paper, we study the issue of estimating a structured signal $x_0 \in \mathbb{R}^n$ from non-linear and noisy Gaussian observations. Supposing that $x_0$ is contained in a certain convex subset $K \subset \mathbb{R}^n$, we prove that…

Statistics Theory · Mathematics 2017-02-21 Martin Genzel

Stochastic resonance (SR) is a prominent phenomenon in many natural and engineered noisy system, whereby the response to a periodic forcing is greatly amplified when the intensity of the noise is tuned to within a specific range of values.…

Statistical Mechanics · Physics 2019-12-25 Valerio Lucarini

We study the steady states and the coarsening dynamics in a one dimensional driven non-conserved system modelled by the so called driven Allen-Cahn equation, which is the standard Allen-Cahn equation with an additional driving force. In…

Statistical Mechanics · Physics 2022-08-17 Rajiv G Pereira

Abstract. We take a pathwise approach to classical McKean-Vlasov stochastic differential equations with additive noise, as e.g. exposed in Sznitmann [38]. Our study was prompted by some concrete problems in battery modelling [23], and also…

Probability · Mathematics 2020-09-25 Michele Coghi , Jean-Dominique Deuschel , Peter Friz , Mario Maurelli

We study the large deviation behavior of a system of diffusing particles with a mean field interaction, described through a collection of stochastic differential equations, in which each particle is driven by a vanishing independent…

Probability · Mathematics 2021-08-10 Amarjit Budhiraja , Michael Conroy

In our companion work \cite{Stojnicl1RegPosasymldp} we revisited random under-determined linear systems with sparse solutions. The main emphasis was on the performance analysis of the $\ell_1$ heuristic in the so-called asymptotic regime,…

Optimization and Control · Mathematics 2016-12-20 Mihailo Stojnic

We analyse the effect of a generic continuous additive perturbation to the well-posedness of ordinary differential equations. Genericity here is understood in the sense of prevalence. This allows us to discuss these problems in a setting…

Classical Analysis and ODEs · Mathematics 2020-12-15 Lucio Galeati , Massimiliano Gubinelli

The formation of codimension-one interfaces for multi-well gradient-driven problems is well-known and established in the scalar case, where the equation is often referred to as the Allen-Cahn equation. The proofs rely for a large on a…

Analysis of PDEs · Mathematics 2020-03-24 Fabrice Bethuel

We analyze the nonlinear stochastic heat equation driven by heavy-tailed noise in free space and arbitrary dimension. The existence of a solution is proved even if the noise only has moments up to an order strictly smaller than its…

Probability · Mathematics 2019-03-26 Carsten Chong

In contrast to ordinary stochastic differential equations (SDEs), the numerical simulation of McKean-Vlasov stochastic differential equations (MV-SDEs) requires approximating the distribution law first. Based on the theory of propagation of…

Numerical Analysis · Mathematics 2025-06-12 Yuhang Zhang , Minghui Song
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