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We consider stochastic Volterra integral equations driven by a fractional Brownian motion with Hurst parameter H > 1/2 . We first derive supremum norm estimates for the solution and its Malliavin derivative. We then show existence and…

Probability · Mathematics 2020-04-08 Mireia Besalú , David Márquez-Carreras , Eulàlia Nualart

This work is devoted to deriving the Onsager--Machlup function for a class of degenerate stochastic dynamical systems with (non-Gaussian) L\'{e}vy noise as well as Brownian noise. This is obtained based on the Girsanov transformation and…

Dynamical Systems · Mathematics 2025-01-10 Ying Chao , Pingyuan Wei

Stein's method is a method of probability approximation which hinges on the solution of a functional equation. For normal approximation the functional equation is a first order differential equation. Malliavin calculus is an…

Probability · Mathematics 2015-05-11 Louis H. Y. Chen

Optimal sample path properties of stochastic processes often involve generalized H\"{o}lder- or variation norms. Following a classical result of Taylor, the exact variation of Brownian motion is measured in terms of $\psi (x) \equiv $…

Probability · Mathematics 2007-11-02 Peter Friz , Harald Oberhauser

We show how to apply ideas from the theory of rough paths to the analysis of low-regularity solutions to non-linear dispersive equations. Our basic example will be the one dimensional Korteweg--de Vries (KdV) equation on a periodic domain…

Analysis of PDEs · Mathematics 2009-07-21 M. Gubinelli

We consider It\^o uniformly nondegenerate equations with random coefficients. When the coefficients satisfy some low regularity assumptions with respect to the spatial variables and Malliavin differentiability assumptions on the sample…

Probability · Mathematics 2021-11-11 Guohuan Zhao

This paper develops an It\^o-type fractional pathwise integration theory for fractional Brownian motion with Hurst parameters \( H \in (\frac{1}{3}, \frac{1}{2}] \), using the Lyons' rough path framework. This approach is designed to fill…

Probability · Mathematics 2025-11-10 Zhongmin Qian , Xingcheng Xu

The stochastic partial differential equation analyzed in this work is the Cahn-Hilliard equation perturbed by an additive fractional white noise (fractional in time and white in space). We work in the case of one spatial dimension and apply…

Probability · Mathematics 2026-01-16 Dimitrios Dimitriou , Dimitris Farazakis , Georgia Karali

The combination of functional limit theorems with the pathwise analysis of deterministic and stochastic differential equations has proven to be a powerful approach to the analysis of fast-slow systems. In a multivariate setting, this…

Probability · Mathematics 2024-09-05 Maximilian Engel , Peter K. Friz , Tal Orenshtein

We study different possibilities to apply the principles of rough paths theory in a non-commutative probability setting. First, we extend previous results obtained by Capitaine, Donati-Martin and Victoir in Lyons' original formulation of…

Probability · Mathematics 2016-03-09 Aurélien Deya , René Schott

We obtain estimates on the first-order Malliavin derivative of mild solutions, evaluated at fixed points in time and space, to a class of parabolic dissipative stochastic PDEs on bounded domain of $\mathbb{R}^d$. In particular, such…

Probability · Mathematics 2022-01-04 Carlo Marinelli

We consider an infinite-dimensional dynamical system with polynomial nonlinearity and additive noise given by a finite number of Wiener processes. By studying how randomness is spread by the system we develop a counterpart of Hormander's…

Probability · Mathematics 2007-05-23 Yuri Bakhtin , Jonathan C. Mattingly

In the article, the rough path theory is extended to cover paths from the exponential Besov-Orlicz space \[B^\alpha_{\Phi_\beta,q}\quad\mbox{ for }\quad \alpha\in (1/3,1/2],\,\quad \Phi_\beta(x) \sim…

Probability · Mathematics 2024-06-06 Petr Čoupek , František Hendrych , Jakub Slavík

For degenerate stochastic differential equations driven by fractional Brownian motions with Hurst parameter $H>1/2$, the derivative formulas are established by using Malliavin calculus and coupling method, respectively. Furthermore, we find…

Probability · Mathematics 2018-03-02 Xiliang Fan

T. Lyons' rough path theory is something like a deterministic version of K. Ito's theory of stochastic differential equations, combined with ideas from K. T. Chen's theory of iterated path integrals. In this article we survey rough path…

Probability · Mathematics 2016-02-11 Yuzuru Inahama

The It{\^o} map assigns the solution of a Rough Differential Equation, a generalization of an Ordinary Differential Equation driven by an irregular path, when existence and uniqueness hold. By studying how a path is transformed through the…

Probability · Mathematics 2019-05-01 Laure Coutin , Antoine Lejay

In this article, we present a general methodology for stochastic control problems driven by the Brownian motion filtration including non-Markovian and non-semimartingale state processes controlled by mutually singular measures. The main…

Probability · Mathematics 2024-04-04 Dorival Leão , Alberto Ohashi , Francys Andrews de Souza

Consider stochastic functional differential equations, whose coefficients depend on past histories. The solution determines a non-Markov process. In the present paper, we shall obtain the existence of smooth densities for joint…

Probability · Mathematics 2016-01-07 Atsushi Takeuchi

We consider the one-dimensional outer stochastic Stefan problem with reflection. The problem admits maximal solutions as long as the velocity of the moving boundary remains bounded, [3,9,10]. We apply Malliavin calculus to the transformed…

We introduce novel equations, in the spirit of rough path theory, that parametrize level sets of intrinsically regular maps on the Heisenberg group with values in $\mathbb{R}^2$. These equations can be seen as a sub-Riemannian counterpart…

Differential Geometry · Mathematics 2016-10-28 Valentino Magnani , Eugene Stepanov , Dario Trevisan
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