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Sufficient conditions for existence and uniqueness of the solution of the Volterra integral equations of the first kind with piecewise continuous kernels are derived in framework of Sobolev-Schwartz distribution theory. The asymptotic…

Mathematical Physics · Physics 2012-04-26 Denis Sidorov

We explore the limit of stochastic differential equations driven by some random processes satisfying singularly perturbed second order stochastic differential equations. The main tool we employ is the universal limit theorem in rough path…

Probability · Mathematics 2026-04-08 Qingming Zhao , Xueru Liu , Wei Wang

We continue the development of the theory of pathwise stochastic entropy solutions for scalar conservation laws in $\R^N$ with quasilinear multiplicative ''rough path'' dependence by considering inhomogeneous fluxes and a single rough path…

Analysis of PDEs · Mathematics 2014-04-07 Pierre-Louis Lions , Benoit Perthame , Panagiotis E. Souganidis

We study controlled differential equations with unbounded drift terms, where the driving paths is $\nu$ - H\"older continuous for $\nu \in (\frac{1}{3},\frac{1}{2})$, so that the rough integral are interpreted in the Gubinelli sense…

Probability · Mathematics 2020-10-19 Luu Hoang Duc

We consider one-dimensional stochastic Volterra equations with jumps for which we establish conditions upon the convolution kernel and coefficients for the strong existence and pathwise uniqueness of a non-negative c\`adl\`ag solution. By…

Probability · Mathematics 2024-07-23 Aurélien Alfonsi , Guillaume Szulda

This paper focuses on the optimal control of a class of stochastic Volterra integral equations. Here the coefficients are regular and not assumed to be of convolution type. We show that, under mild regularity assumptions, these equations…

Probability · Mathematics 2026-04-08 Dylan Possamaï , Mehdi Talbi

The accurate numerical solution of partial differential equations is a central task in numerical analysis allowing to model a wide range of natural phenomena by employing specialized solvers depending on the scenario of application. Here,…

Numerical Analysis · Mathematics 2022-12-13 Moritz Reh , Martin Gärttner

In this paper, we first study the existence-uniqueness and large deviation estimate of solutions for stochastic Volterra integral equations with singular kernels in 2-smooth Banach spaces. Then, we apply them to a large class of semilinear…

Probability · Mathematics 2008-12-05 Xicheng Zhang

We study the regular conditional law of mixed Gaussian Volterra processes under the influence of model disturbances. More precisely, we study prediction of Gaussian Volterra processes driven by a Brownian motion in a case where the Brownian…

Probability · Mathematics 2019-04-23 Tommi Sottinen , Lauri Viitasaari

New classes of stochastic differential equations can now be studied using rough path theory (e.g. Lyons et al. [LCL07] or Friz--Hairer [FH14]). In this paper we investigate, from a numerical analysis point of view, stochastic differential…

Probability · Mathematics 2016-06-20 Christian Bayer , Peter K. Friz , Sebastian Riedel , John Schoenmakers

We analyze common lifts of stochastic processes to rough paths/rough drivers-valued processes and give sufficient conditions for the cocycle property to hold for these lifts. We show that random rough differential equations driven by such…

Probability · Mathematics 2016-12-07 Ismael Bailleul , Sebastian Riedel , Michael Scheutzow

In this paper, we are interested in comparing solutions to stochastic Volterra equations for the convex order on the space of continuous $\R^d$-valued paths and for the monotonic convex order when $d=1$. Even if in general these solutions…

Probability · Mathematics 2022-11-21 Benjamin Jourdain , Gilles Pagès

We study a compound Poisson (random time-change) approximation for stochastic differential equations (SDEs) and stochastic Volterra equations whose coefficients may be merely measurable in time and may even exhibit integrable singularities.…

Probability · Mathematics 2026-03-10 Xicheng Zhang , Yuanlong Zhao

In this paper a class of optimization problems with uncertain linear constraints is discussed. It is assumed that the constraint coefficients are random vectors whose probability distributions are only partially known. Possibility theory is…

Optimization and Control · Mathematics 2021-11-30 Romain Guillaume , Adam Kasperski , Pawel Zielinski

We are interested in (uniformly) parabolic PDEs with a nonlinear dependance of the leading-order coefficients, driven by a rough right hand side. For simplicity, we consider a space-time periodic setting with a single spatial variable:…

Analysis of PDEs · Mathematics 2018-11-07 Felix Otto , Hendrik Weber

In this paper we study singular kinetic equations on $\mathbb{R}^{2d}$ by the paracontrolled distribution method introduced in \cite{GIP15}. We first develop paracontrolled calculus in the kinetic setting, and use it to establish the global…

Probability · Mathematics 2021-08-12 Zimo Hao , Xicheng Zhang , Rongchan Zhu , Xiangchan Zhu

We review recent results on the analysis of singular stochastic partial differential equations in the language of paracontrolled distributions.

Probability · Mathematics 2017-02-13 Massimiliano Gubinelli , Nicolas Perkowski

The main result of the present paper is a statement on existence, uniqueness and regularity for mild solutions to a parabolic transport diffusion type equation that involves a non-smooth coefficient. We investigate related Cauchy problems…

Analysis of PDEs · Mathematics 2013-07-19 Elena Issoglio

Motivated by applications in physics (e.g., turbulence intermittency) and financial mathematics (e.g., rough volatility), this paper examines a family of integrated stochastic Volterra processes characterized by a small Hurst parameter…

Probability · Mathematics 2025-01-28 Mireille Bossy , Kerlyns Martinez , Paul Maurer

In the paper stochastic Volterra equations of nonscalar type in Hilbert space are studied. The aim of the paper is to provide some results on stochastic convolution and mild solutions to those Volterra equations. The motivation of the paper…

Probability · Mathematics 2007-05-23 Anna Karczewska
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