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The moving average of the complex modulus of the analytic wavelet transform provides a robust time-scale representation for signals to small time shifts and deformation. In this work, we derive the Wiener chaos expansion of this…

Probability · Mathematics 2024-10-23 Gi-Ren Liu , Yuan-Chung Sheu , Hau-Tieng Wu

In this work we establish a Freidlin-Wentzell type large deviation principle for stochastic nonlinear Schr\"{o}dinger equation, with either focusing or defocusing nonlinearity, driven by nonlinear multiplicative L\'evy noise in the Marcus…

Probability · Mathematics 2024-08-19 Jiahui Zhu , Wei Liu , Jianliang Zhai

For a class of additive processes driven by the affine recursion $X_{n+1} = A_n X_n + B_n$, we develop a sample-path large deviations principle in the $M_1'$ topology on $D [0,1]$. We allow $B_n$ to have both signs and focus on the case…

Probability · Mathematics 2024-03-26 Bohan Chen , Chang-Han Rhee , Bert Zwart

In this paper, we study a linear control system with a given state feedback law. The system is influenced by rapid random sampling occurring at frequency $\frac 1n, n \in \mathbb N$, as well as by white noise of small intensity $\varepsilon…

Probability · Mathematics 2026-03-18 Sarvesh Ravichandran Iyer , Vivek Kumar

We investigate the possibility of characterizing the different thermalization pathways through a large-deviation approach. Specifically, we consider clean, disordered and quasi-periodic harmonic chains under energy and momentum-conserving…

Statistical Mechanics · Physics 2024-08-21 Stefano Lepri

White noise is a fundamental and fairly well understood stochastic process that conforms the conceptual basis for many other processes, as well as for the modeling of time series. Here we push a fresh perspective toward white noise that,…

Statistical Mechanics · Physics 2023-01-04 Alvaro Diaz-Ruelas

The recently introduced basis adaptation method for Homogeneous (Wiener) Chaos expansions is explored in a new context where the rotation/projection matrices are computed by discovering the active subspace where the random input exhibits…

Computation · Statistics 2018-07-04 Panagiotis A. Tsilifis

We consider the damped nonlinear wave (NLW) equation driven by a spatially regular white noise. Assuming that the noise is non-degenerate in all Fourier modes, we establish a large deviations principle (LDP) for the occupation measures of…

Analysis of PDEs · Mathematics 2015-05-15 Davit Martirosyan , Vahagn Nersesyan

In this paper we present a numerical scheme for stochastic differential equations based upon the Wiener chaos expansion. The approximation of a square integrable stochastic differential equation is obtained by cutting off the infinite chaos…

Probability · Mathematics 2019-06-05 Tony Huschto , Mark Podolskij , Sebastian Sager

This work concerns about multiscale multivalued McKean-Vlasov stochastic systems. First of all, we use a contractive mapping principle to establish the well-posedness for fully coupled multivalued McKean-Vlasov stochastic systems under…

Probability · Mathematics 2025-09-30 Huijie Qiao

We investigate an additive perturbation of a complex Wishart random matrix and prove that a large deviation principle holds for the spectral measures. The rate function is associated to a vector equilibrium problem coming from logarithmic…

Probability · Mathematics 2013-03-14 Adrien Hardy , Arno B. J. Kuijlaars

In this paper, we consider a class of reflected stochastic differential equations for which the constraint is not on the paths of the solution but on its law. We establish a small noise large deviation principle, a large deviation for short…

Probability · Mathematics 2023-03-27 Ping Chen , Jianliang Zhai

In this paper, a large deviation principle for the strong solution of the p-Laplace equation on unbounded domain driven by small multiplicative Brownian noise is established. The weak convergence approach and the localized time increment…

Probability · Mathematics 2024-08-28 Ananta K Majee

We treat some classes of linear and semilinear stochastic partial differential equations of Schr\"odinger type on $\mathbb{R}^d$, involving a non-flat Laplacian, within the framework of white noise analysis, combined with Wiener-It\^o chaos…

Analysis of PDEs · Mathematics 2025-04-04 Sandro Coriasco , Stevan Pilipović , Dora Seleši

Ciesielski's isomorphism between the space of alpha-H\"older continuous functions and the space of bounded sequences is used to give an alternative proof of the large deviation principle for Wiener processes with values in Hilbert space.

Probability · Mathematics 2012-03-22 Andreas Andresen , Peter Imkeller , Nicolas Perkowski

As an enhanced version of existing results on Kac's propagation of chaos, which describes the convergence of mean-field particle systems to a system of independent McKean-Vlasov particles as the number of particles tends to infinity, we…

Probability · Mathematics 2026-05-12 Xiao-Yu Zhao

We consider the one-dimensional stochastic heat and wave equations driven by Gaussian noises with constant initial conditions. We study the spatial average of the solutions on an interval of length $R$ and show that the family of laws of…

Probability · Mathematics 2025-08-05 Masahisa Ebina

We establish large deviations properties valid for almost every sample path of a class of stationary mixing processes $(X_1,..., X_n,...)$. These properties are inherited from those of $S_n=\sum_{i=1}^nX_i$ and describe how the local…

Probability · Mathematics 2011-12-08 Julien Barral , Patrick Loiseau

Uniform large deviation principles for positive functionals of all equivalent types of infinite dimensional Brownian motions acting together with a Poisson random measure are established. The core of our approach is a variational…

Probability · Mathematics 2014-03-13 Vasileios Maroulas

We consider expansive homeomorphisms with the specification property. We give a new simple proof of a large deviation principle for Gibbs measures corresponding to a regular potential and we establish a general symmetry of the rate function…

Chaotic Dynamics · Physics 2015-05-26 Christian Maes , Evgeny Verbitskiy
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