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相关论文: Non-Markovian Fully Coupled Forward-Backward Stoch…

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Semiclassical path integral expression for a quantum system coupled to a harmonic bath is derived based on the stationary phase condition. It is discovered that the system path is non-Markovian. Most strikingly, the system path not only…

量子物理 · 物理学 2021-02-03 Fei Wang

The classical Feynman-Kac formula states the connection between linear parabolic partial differential equations (PDEs), like the heat equation, and expectation of stochastic processes driven by Brownian motion. It gives then a method for…

概率论 · 数学 2014-09-03 Huyen Pham

We analyze a class of nonlinear partial differential equations (PDEs) defined on $\mathbb{R}^d \times \mathcal{P}_2(\mathbb{R}^d),$ where $\mathcal{P}_2(\mathbb{R}^d)$ is the Wasserstein space of probability measures on $\mathbb{R}^d$ with…

概率论 · 数学 2015-04-23 Jean-François Chassagneux , Dan Crisan , François Delarue

We present the non-Markovian generalization of the widely used stochastic Schrodinger equation. Our result allows to describe open quantum systems in terms of stochastic state vectors rather than density operators, without approximation.…

量子物理 · 物理学 2009-10-30 Lajos Diosi , Walter T. Strunz

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…

数值分析 · 数学 2025-04-04 Zhipeng Huang , Cornelis W. Oosterlee

In this paper, we introduce a type of path-dependent quasilinear (parabolic) partial differential equations in which the (continuous) paths on an interval [0,t] becomes the basic variables in the place of classical variables (t,x). This new…

概率论 · 数学 2011-08-23 Shige Peng , Falei Wang

We study stochastic differential equations (SDEs) whose drift and diffusion coefficients are path-dependent and controlled. We construct a value process on the canonical path space, considered simultaneously under a family of singular…

概率论 · 数学 2012-05-08 Marcel Nutz

In this paper we propose a new type of viscosity solutions for fully nonlinear path dependent PDEs. By restricting to certain pseudo Markovian structure, we remove the uniform non- degeneracy condition imposed in our earlier works [9, 10].…

偏微分方程分析 · 数学 2016-04-11 Ibrahim Ekren , Jianfeng Zhang

This paper is devoted to path-dependent kinetics equations arising, in particular, from the analysis of the coupled backward - forward systems of equations of mean field games. We present local well-posedness, global existence and some…

概率论 · 数学 2013-03-25 Vassili Koloklotsov , Wei Yang

In this paper, we study the well-posedness of the Forward-Backward Stochastic Differential Equations (FBSDE) in a general non-Markovian framework. The main purpose is to find a unified scheme which combines all existing methodology in the…

概率论 · 数学 2015-06-30 Jin Ma , Zhen Wu , Detao Zhang , Jianfeng Zhang

We study sequences of empirical measures of Euler schemes associated to some non-Markovian SDEs: SDEs driven by Gaussian processes with stationary increments. We obtain the functional convergence of this sequence to a stationary solution to…

概率论 · 数学 2012-06-22 Serge Cohen , Fabien Panloup

We obtain an existence and uniqueness theorem for fully coupled forward-backward SDEs (FBSDEs) with jumps via the classical solution to the associated quasilinear parabolic partial integro-differential equation (PIDE), and provide the…

概率论 · 数学 2019-11-18 Evelina Shamarova , Rui Sá Pereira

We prove the existence of classical solutions to parabolic linear stochastic integro-differential equations with adapted coefficients using Feynman-Kac transformations, conditioning, and the interlacing of space-inverses of stochastic flows…

概率论 · 数学 2014-11-27 James-Michael Leahy , Remigijus Mikulevicius

We propose a time-space discretization scheme for quasi-linear parabolic PDEs. The algorithm relies on the theory of fully coupled forward--backward SDEs, which provides an efficient probabilistic representation of this type of equation.…

概率论 · 数学 2016-08-16 François Delarue , Stéphane Menozzi

In this paper we study dynamic backward problems, with the computation of conditional expectations as a main objective, in a framework where the (forward) state process satisfies a Volterra type SDE, with fractional Brownian motion as a…

概率论 · 数学 2018-10-09 Frederi Viens , Jianfeng Zhang

In this paper, by virtue of Malliavin calculus, we establish a relationship between backward doubly stochastic differential equations with random coefficients and quasilinear stochastic PDEs, and thus extend the well-known nonlinear…

概率论 · 数学 2018-10-17 Jiaqiang Wen , Yufeng Shi

We study (backward) stochastic differential equations with noise coming from a finite state Markov chain. We show that, for the solutions of these equations to be `Markovian', in the sense that they are deterministic functions of the state…

概率论 · 数学 2011-11-28 Samuel N. Cohen , Lukasz Szpruch

We study optimal stochastic control problem for non-Markovian stochastic differential equations (SDEs) where the drift, diffusion coefficients, and gain functionals are path-dependent, and importantly we do not make any ellipticity…

概率论 · 数学 2013-11-04 Marco Fuhrman , Huyên Pham

In [5] the authors obtained Mean-Field backward stochastic differential equations (BSDE) associated with a Mean-field stochastic differential equation (SDE) in a natural way as limit of some highly dimensional system of forward and backward…

概率论 · 数学 2007-11-21 Rainer Buckdahn , Juan Li , Shige Peng

This paper provides a large deviation principle for Non-Markovian, Brownian motion driven stochastic differential equations with random coefficients. Similar to Gao and Liu \cite{GL}, this extends the corresponding results collected in…

概率论 · 数学 2014-07-22 Jin Ma , Zhenjie Ren , Nizar Touzi , Jianfeng Zhang