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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 study functionals of the form \[\zeta_{t}=\int_0^{t}...\int_0^{t} | X_1(s_1)+...+ X_p(s_p)|^{-\sigma}ds_1... ds_p\] where $X_1(t),..., X_p(t)$ are i.i.d. $d$-dimensional symmetric stable processes of index $0<\bb\le 2$. We obtain results…

Probability · Mathematics 2007-12-17 R. Bass , X. Chen , J. Rosen

This paper is devoted to proving the small noise asymptotic behaviour, particularly large deviation principle, for multi-scale stochastic dynamical systems with fully local monotone coefficients driven by multiplicative noise. The main…

Probability · Mathematics 2024-03-11 Wei Hong , Wei Liu , Luhan Yang

A large deviations principle is established for the joint law of the empirical measure and the flow measure of a renewal Markov process on a finite graph. We do not assume any bound on the arrival times, allowing heavy tailed distributions.…

Probability · Mathematics 2014-02-18 Mauro Mariani , Lorenzo Zambotti

We establish the large deviation principle for stochastic differential equations with averaging in the case when all coefficients of the fast component depend on the slow one, including diffusion.

Probability · Mathematics 2013-06-11 Alexander Yu. Veretennikov

This paper investigates longtime behaviors of the $\theta$-Euler-Maruyama method for the stochastic functional differential equation with superlinearly growing coefficients. We focus on the longtime convergence analysis in mean-square sense…

Numerical Analysis · Mathematics 2024-04-16 Chuchu Chen , Tonghe Dang , Jialin Hong , Guoting Song

This paper establishs the large deviation principle (LDP) for multiple averages on $\mathbb{N}^d$. We extend the previous work of [Carinci et al., Indag. Math. 2012] to multidimensional lattice $\mathbb{N}^d$ for $d\geq 2$. The same…

Probability · Mathematics 2021-06-21 Jung-Chao Ban , Wen-Guei Hu , Guan-Yu Lai

In this paper, we establish a large deviation principle for stochastic evolution equations with reflection in an infinite dimensional ball. Weak convergence approach plays an important role.

Probability · Mathematics 2024-03-05 Zdzisław Brzeźniak , Qi Li , Tusheng Zhang

In this work, we establish the Freidlin--Wentzell large deviations principle (LDP) of the stochastic Cahn--Hilliard equation with small noise, which implies the one-point LDP. Further, we give the one-point LDP of the spatial finite…

Numerical Analysis · Mathematics 2026-03-06 Diancong Jin , Derui Sheng

It has often been observed that the Multifractal Formalism and the Large Deviation Principles are intimately related. In fact, Multifractal Formalism was heuristically derived using the Large Deviations ideas. In numerous examples in which…

Dynamical Systems · Mathematics 2025-11-11 Mirmukhsin Makhmudov , Evgeny Verbitskiy , Qian Xiao

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

In this paper, we consider the large deviations of invariant measure for the 3D stochastic hyperdissipative Navier-Stokes equations driven by additive noise. The unique ergodicity of invariant measure as a preliminary result is proved using…

Analysis of PDEs · Mathematics 2023-07-11 Zhaoyang Qiu , Hui Liu , Chengfeng Sun

In this paper, we establish a large deviation principle for the solutions to the stochastic heat equations with logarithmic nonlinearity driven by Brownian motion, which is neither locally Lipschitz nor locally monotone. Nonlinear versions…

Probability · Mathematics 2022-07-07 Tianyi Pan , Shijie Shang , Tusheng Zhang

A variational representation for functionals of G-Brownian motion is established by a finite-dimensional approximate technique. As an application of the variational representation, we obtain a large deviation principle for stochastic flows…

Probability · Mathematics 2012-04-23 Fuqing Gao

In this paper we show a some new look at large deviation theorems from the viewpoint of the information-spectrum (IS) methods, which has been first exploited in information theory, and also demonstrate a new basic formula for the large…

Information Theory · Computer Science 2007-07-13 Te Sun Han

In this PhD thesis we introduce a generalized fractional calculus of variations. We consider variational problems containing generalized fractional integrals and derivatives, and study them using standard (indirect) and direct methods. In…

Optimization and Control · Mathematics 2014-03-19 Tatiana Odzijewicz

We consider a stochastic Cahn-Hilliard partial differential equation driven by a space-time white noise. We prove the Large Deviations Principle (LDP) for the law of the solutions in the H\"older norm. We use the weak convergence approach…

Probability · Mathematics 2017-08-29 Lahcen Boulanba , Mohamed Mellouk

In this paper, we first provide a criterion on uniform large deviation principles (ULDP) of stochastic differential equations under Lyapunov conditions on the coefficients, which can be applied to stochastic systems with coefficients of…

Probability · Mathematics 2024-02-27 Jifa Jiang , Jian Wang , Jianliang Zhai , Tusheng Zhang

Stochastic space-time fractional diffusion equations often appear in the modeling of the heat propagation in non-homogeneous medium. In this paper, we firstly investigate the Mittag--Leffler Euler integrator of a class of stochastic…

Numerical Analysis · Mathematics 2023-08-15 Xinjie Dai , Jialin Hong , Derui Sheng

In this paper, we present sufficient conditions and criteria to establish the large and moderate deviation principle of multivalued McKean-Vlasov stochastic differential equation by means of the weak convergence method.

Probability · Mathematics 2022-08-31 Fengwu Zhu , Wei Liu
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