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In the pathwise stochastic calculus framework, the paper deals with the general study of equations driven by an additive Gaussian noise, with a drift function having an infinite limit at point zero. An ergodic theorem and the convergence of…

Probability · Mathematics 2019-01-16 Nicolas Marie

The stochastic partial differential equation analyzed in this work, is motivated by a simplified mesoscopic physical model for phase separation. It describes pattern formation due to adsorption and desorption mechanisms involved in surface…

Probability · Mathematics 2018-02-20 D. C. Antonopoulou , D. Farazakis , G. D. Karali

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

We consider the class of non-linear stochastic partial differential equations studied in \cite{conusdalang}. Equivalent formulations using integration with respect to a cylindrical Brownian motion and also the Skorohod integral are…

Probability · Mathematics 2015-03-25 Marta Sanz-Solé , André Süß

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

We study Malliavin differentiability of solutions to sub-critical singular parabolic stochastic partial differential equations (SPDEs) and we prove the existence of densities for a class of singular SPDEs. Both of these results are…

Probability · Mathematics 2018-09-12 Philipp Schönbauer

We study Malliavin differentiability for the solutions of a stochastic differential equation with drift of super-linear growth. Assuming we have a monotone drift with polynomial growth, we prove Malliavin differentiability of any order. As…

Probability · Mathematics 2024-05-31 Cristina Anton

A new method is described for constructing a generalized solution for stochastic differential equations. The method is based on the Cameron-Martin version of the Wiener Chaos expansion and provides a unified framework for the study of…

Probability · Mathematics 2007-05-23 S. V. Lototsky , B. L. Rozovskii

Via a special transform and by using the techniques of the Malliavin calculus, we analyze the density of the solution to a stochastic differential equation with unbounded drift.

Probability · Mathematics 2018-05-18 C. Olivera , C. Tudor

Suppose $B$ is a Brownian motion and $B^n$ is an approximating sequence of rescaled random walks on the same probability space converging to $B$ pointwise in probability. We provide necessary and sufficient conditions for weak and strong…

Probability · Mathematics 2016-03-01 Christian Bender , Peter Parczewski

Using the Bismut's approach to Malliavin calculus, we introduce a simplified Malliavin matrix ([11]) for stochastic differential equations (SDEs) force by degenerate stable like noises. For the degenerate SDEs driven by Wiener noises, one…

Probability · Mathematics 2014-02-21 Lihu Xu

We consider finite dimensional rough differential equations driven by centered Gaussian processes. Combining Malliavin calculus, rough paths techniques and interpolation inequalities, we establish upper bounds on the density of the…

Probability · Mathematics 2020-06-18 Benjamin Gess , Cheng Ouyang , Samy Tindel

A recent paper of Melbourne & Stuart, A note on diffusion limits of chaotic skew product flows, Nonlinearity 24 (2011) 1361-1367, gives a rigorous proof of convergence of a fast-slow deterministic system to a stochastic differential…

Dynamical Systems · Mathematics 2015-06-15 Georg A. Gottwald , Ian Melbourne

Malliavin Calculus is about Sobolev-type regularity of functionals on Wiener space, the main example being the Ito map obtained by solving stochastic differential equations. Rough path analysis is about strong regularity of solution to…

Probability · Mathematics 2007-11-12 Thomas Cass , Peter Friz , Nicolas Victoir

In this paper we aim at generalizing the results of A. K. Zvonkin and A. Y. Veretennikov on the construction of unique strong solutions of stochastic differential equations with singular drift vector field and additive noise in the…

Probability · Mathematics 2019-03-15 David Baños , Martin Bauer , Thilo Meyer-Brandis , Frank Proske

We consider the stochastic continuity equation driven by Brownian motion. We use the techniques of the Malliavin calculus to show that the law of the solution has a density with respect to the Lebesgue measure. We also prove that the…

Probability · Mathematics 2018-03-19 David A. C. Mollinedo , Christian Olivera , Ciprian A. Tudor

For a mixed stochastic differential driven by independent fractional Brownian motions and Wiener processes, the existence and integrability of the Malliavin derivative of its solution are established. It is also proved that the solution…

Probability · Mathematics 2013-09-25 Georgiy Shevchenko , Taras Shalaiko

We investigate the existence of densities for finite-dimensional distributions of Hermite processes of order \(q \ge 1\) and self-similarity parameter \(H\in(\frac12,1)\). Whereas the Gaussian case \(q=1\) (fractional Brownian motion) is…

Probability · Mathematics 2025-09-26 Laurent Loosveldt , Yassine Nachit , Ivan Nourdin , Ciprian Tudor

We apply Malliavin calculus to the $\Phi^4_3$ equation on the torus and prove existence of densities for the solution of the equation evaluated at regular enough test functions. We work in the framework of regularity structures and rely on…

Probability · Mathematics 2019-02-05 Paul Gassiat , Cyril Labbé

We study stochastic evolution equations driven by Gaussian noise. The key features of the model are that the operators in the deterministic and stochastic parts can have the same order and the noise can be time-only, space-only, or…

Probability · Mathematics 2007-09-20 S. V. Lototsky , B. L. Rozovskii
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