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Motivated by the potential applications to the fractional Brownianmotion, we study Volterra stochasticdifferential of the form~:\begin{equation}X\_t = x+ \int\_0^tK(t,s)b(s,X\_s)ds + \int\_0^tK(t,s) \sigma(s,X\_s)\,dB\_s ,\tag{E}…

Probability · Mathematics 2017-03-27 Laure Coutin , Laurent Decreusefond

We provide a general framework for the stability of solutions to stochastic partial differential equations with respect to perturbations of the drift. More precisely, we consider stochastic partial differential equations with drift given as…

Analysis of PDEs · Mathematics 2016-02-03 Benjamin Gess , Jonas M. Tölle

In this paper stochastic Volterra equations admitting exponentially bounded resolvents are studied. After obtaining convergence of resolvents, some properties for stochastic convolutions are studied. Our main result provide sufficient…

Probability · Mathematics 2008-10-19 Anna Karczewska , Carlos Lizama

In this article spatial and temporal regularity of the solution process of a stochastic partial differential equation (SPDE) of evolutionary type with nonlinear multiplicative trace class noise is analyzed.

Probability · Mathematics 2011-11-07 Arnulf Jentzen , Michael Roeckner

We consider a general class of integro-differential evolution equations which includes the governing equation of the generalized grey Brownian motion and the time- and space-fractional heat equation. We present a general relation between…

Probability · Mathematics 2022-04-21 Christian Bender , Yana A. Butko

This work presents a more broadly applicable version of an energy inequality for weak solutions of evolution equations involving fractional time derivatives. Unlike the classical identity that relates the time derivative of the squared norm…

Analysis of PDEs · Mathematics 2025-08-11 Paulo M. Carvalho-Neto , Cicero L. Frota , Juan C. Oyola Ballesteros , Pedro G. P. Torelli

Firstly, we investigate Euler-Maruyama approximation for solutions of stochastic differential equations (SDEs) driven by a symmetric \alpha\ stable process under Komatsu condition for coefficients. The approximation implies naturally the…

Probability · Mathematics 2011-10-13 Hiroya Hashimoto

We consider a nonlinear stochastic differential equation driven by an $\alpha$-stable L\'{e}vy process ($1<\alpha<2$). We first obtain some regularity results for the probability density of its invariant measure via establishing the a…

Probability · Mathematics 2020-08-17 Qi Zhang , Jinqiao Duan

We investigate thermodynamics of general nonequilibrium processes stopped at stochastic times. We propose a systematic strategy for constructing fluctuation-theorem-like martingales for each thermodynamic functional, yielding a family of…

Statistical Mechanics · Physics 2023-06-02 Haoran Yang , Hao Ge

The Donsker-Varadhan rate function for occupation-time fluctuations has been seen numerically to exhibit monotone return to stationary nonequilibrium [Phys. Rev. Lett. 107, 010601 (2011)]. That rate function is related to dynamical activity…

Mathematical Physics · Physics 2015-05-07 Christian Maes , Karel Netocny , Bram Wynants

The purpose of this paper is to establish the convergence in distribution of the normalized error in the Euler approximation scheme for stochastic Volterra equations driven by a standard Brownian motion, with a kernel of the form…

Probability · Mathematics 2022-04-18 David Nualart , Bhargobjyoti Saikia

An alternative approach - nonequilibrium evolution thermodynamics, is compared with classical Landau approach. A statistical justification of the approach is carried out with help of probability distribution function on an example of a…

Statistical Mechanics · Physics 2010-08-13 Leonid S. Metlov

We study a novel alternative approach for the computation of transport coefficients at mesoscales. While standard nonequilibrium molecular dynamics (NEMD) approaches fix the forcing and measure the average induced flux in the system driven…

Computational Physics · Physics 2025-09-05 Xinyi Wu , Xiaocheng Shang

We study the class of continuous polynomial Volterra processes, which we define as solutions to stochastic Volterra equations driven by a continuous semimartingale with affine drift and quadratic diffusion matrix in the state of the…

Probability · Mathematics 2024-03-22 Eduardo Abi Jaber , Christa Cuchiero , Luca Pelizzari , Sergio Pulido , Sara Svaluto-Ferro

We consider a Volterra convolution equation in $\mathbb{R}^d$ perturbed with an additive fractional Brownian motion of Riemann-Liouville type with Hurst parameter $H\in (0,1)$. We show that its solution solves a stochastic partial…

Probability · Mathematics 2023-09-26 Alessandro Bondi , Franco Flandoli

We study multidimensional stochastic volatility models in which the volatility process is a positive continuous function of a continuous multidimensional Volterra process that can be not self-similar. The main results obtained in this paper…

Probability · Mathematics 2022-09-15 Giulia Catalini , Barbara Pacchiarotti

Semi-Markov processes are a generalization of Markov processes since the exponential distribution of time intervals is replaced with an arbitrary distribution. This paper provides an integro-differential form of the Kolmogorov's backward…

Probability · Mathematics 2017-09-20 Enzo Orsingher , Costantino Ricciuti , Bruno Toaldo

For the multivariate COGARCH(1,1) volatility process we show sufficient conditions for the existence of a unique stationary distribution, for the geometric ergodicity and for the finiteness of moments of the stationary distribution by a…

Probability · Mathematics 2019-10-01 Robert Stelzer , Johanna Vestweber

We study a new class of ergodic backward stochastic differential equations (EBSDEs for short) which is linked with semi-linear Neumann type boundary value problems related to ergodic phenomenas. The particularity of these problems is that…

Probability · Mathematics 2010-02-11 Adrien Richou

Based on the notion of paracontrolled distributions, we provide existence and uniqueness results for rough Volterra equations of convolution type with potentially singular kernels and driven by the newly introduced class of convolutional…

Probability · Mathematics 2021-09-21 David J. Prömel , Mathias Trabs
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