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This paper provide a comprehensive analysis of the finite and long time behavior of continuous-time non-Markovian dynamical systems, with a focus on the forward Stochastic Volterra Integral Equations(SVIEs).We investigate the properties of…

Probability · Mathematics 2025-11-06 Emmanuel Gnabeyeu , Gilles Pagès

In this paper we introduce a multilevel Picard approximation algorithm for general semilinear parabolic PDEs with gradient-dependent nonlinearities whose coefficient functions do not need to be constant. We also provide a full convergence…

Numerical Analysis · Mathematics 2025-02-19 Ariel Neufeld , Sizhou Wu

In this paper, the theory of mean-field backward doubly stochastic Volterra integral equations (MF-BDSVIEs) is studied. First, we derive the well-posedness of M-solutions to MFBDSVIEs, and prove the comparison theorem for such a type of…

Probability · Mathematics 2023-12-21 Bixuan Yang , Jinbiao Wu , Tiexin Guo

Traditional Monte Carlo methods for particle transport utilize source iteration to express the solution, the flux density, of the transport equation as a Neumann series. Our contribution is to show that the particle paths simulated within…

Probability · Mathematics 2024-07-03 J. Darby Smith , Rich Lehoucq , Brian Franke

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

In this paper, we consider the solvability problems for the fully coupled forward-backward stochastic difference equations (FBS{\Delta}Es) on spaces related to discrete time, finite state processes. On one hand, we provide the necessary and…

Probability · Mathematics 2019-07-09 Shaolin Ji , Haodong Liu

We propose some numerical schemes for forward-backward stochastic differential equations (FBSDEs) based on a new fundamental concept of transposition solutions. These schemes exploit time-splitting methods for the variation of constants…

Numerical Analysis · Mathematics 2018-05-01 Kazufumi Ito , Yufei Zhang , Jun Zou

Inverse problems are ubiquitous because they formalize the integration of data with mathematical models. In many scientific applications the forward model is expensive to evaluate, and adjoint computations are difficult to employ; in this…

Dynamical Systems · Mathematics 2021-11-05 G. A. Pavliotis , A. M. Stuart , U. Vaes

We extend the results of the FBSDE theory in order to construct a probabilistic representation of a viscosity solution to the Cauchy problem for a system of quasilinear parabolic equations. We derive a BSDE associated with a class of…

Probability · Mathematics 2016-06-09 Ya. I. Belopolskaya

In this paper we consider the problem of viscosity solution of integro-partial differential equation(IPDE in short) via the solution of backward stochastic differential equations(BSDE in short) with jumps where L\'evy's measure is not…

Probability · Mathematics 2018-09-11 Lamine Sylla

In the present paper we discuss a new type of mean-field coupled forward-backward stochastic differential equations (MFFBSDEs). The novelty consists in the fact that the coefficients of both the forward as well as the backward SDEs depend…

Probability · Mathematics 2023-07-27 Rainer Buckdahn , Juan Li , Junsong Li , Chuanzhi Xing

We propose algorithms for solving high-dimensional Partial Differential Equations (PDEs) that combine a probabilistic interpretation of PDEs, through Feynman-Kac representation, with sparse interpolation. Monte-Carlo methods and…

Numerical Analysis · Mathematics 2022-03-25 Marie Billaud-Friess , Arthur Macherey , Anthony Nouy , Clémentine Prieur

The Feynman path integral approach to quantum mechanics is examined in the case where the configuration space is curved. It is shown how the ambiguity that is present in the choice of path integral measure may be resolved if, in addition to…

High Energy Physics - Theory · Physics 2007-05-23 David J. Toms

We introduce and study a new type of integral equations called anticipating backward stochastic Volterra integral equations (anticipating BSVIEs). In these equations the generator involves not only the present values but also the future…

Probability · Mathematics 2016-06-01 Jiaqiang Wen , Yufeng Shi

Discretizations of the Feynman-Kac path integral representation of the quantum mechanical density matrix are investigated. Each infinite-dimensional path integral is approximated by a Riemann integral over a finite-dimensional function…

Statistical Mechanics · Physics 2007-05-23 Stephen D. Bond , Brian B. Laird , Benedict J. Leimkuhler

We introduce and analyse a continuum model for an interacting particle system of Vicsek type. The model is given by a non-linear kinetic partial differential equation (PDE) describing the time-evolution of the density $f_t$, in the single…

Mathematical Physics · Physics 2022-04-11 Paolo Buttà , Franco Flandoli , Michela Ottobre , Boguslaw Zegarlinski

A new Monte-Carlo method for solving linear parabolic partial differential equations is presented. Since, in this new scheme, the particles are followed backward in time, it provides great flexibility in choosing critical points in…

Numerical Analysis · Mathematics 2025-10-20 Johan Carlsson

In this paper, we investigate the Markovian iteration method for solving coupled forward-backward stochastic differential equations (FBSDEs) featuring a fully coupled forward drift, meaning the drift term explicitly depends on both the…

Numerical Analysis · Mathematics 2025-04-04 Zhipeng Huang , Cornelis W. Oosterlee

In this paper, we study backward doubly stochastic integral equations of the Volterra type (BDSIEVs in short). Under uniform Lipschitz assumptions, we establish an existence and uniqueness result.

Probability · Mathematics 2011-08-16 Jean Marc Owo

We study the forward investment performance process (FIPP) in an incomplete semimartingale market model with closed and convex portfolio constraints, when the investor's risk preferences are of the power form. We provide necessary and…

Probability · Mathematics 2022-01-27 Lijun Bo , Agostino Capponi , Chao Zhou