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The Bismut formula is a crucial tool characterizing regularities of stochastic systems, and has been extensively studied for various models. However it is not yet available for SDEs with distribution dependent noise. In this paper, we first…

Probability · Mathematics 2026-02-12 Xiaochen Ma , Panpan Ren

By using distribution dependent Zvonkin's transforms and Malliavin calculus, the Bismut type formula is derived for the intrinisc/Lions derivatives of distribution dependent SDEs with singular drifts, which generalizes the corresponding…

Probability · Mathematics 2022-05-11 Xing Huang , Yulin Song , Feng-Yu Wang

In recent years, remarkable progress has been made for Distribution dependent stochastic equations (DDSDEs) with singular interactions, existing results include wellposedness, propagation of chaos, entropy cost inequality and ergodicity. As…

Probability · Mathematics 2026-04-13 Panpan Ren

The Bismut formula is established for the intrinsic derivative of singular McKean-Vlasov SDEs, where the noise coefficient belongs to a local Sobolev space, and the drift contains a locally integrable time-space term as well as a…

Probability · Mathematics 2023-03-10 Feng-Yu Wang

By using the Malliavin calculus and solving a control problem, Bismut type derivative formulae are established for a class of degenerate diffusion semigroups with non-linear drifts. As applications, explicit gradient estimates and Harnack…

Probability · Mathematics 2012-03-13 Feng-Yu Wang , Xi-Cheng Zhang

To characterize the regularity of distribution-path dependent SDEs in the initial distribution which varies in the class of probability measures on the path space, we introduce the intrinsic and Lions derivatives for probability measures on…

Probability · Mathematics 2021-02-16 Jianhai Bao , Panpan Ren , Feng-Yu Wang

By using Malliavin calculus, Bismut type formulas are established for the Lions derivative of $P_tf(\mu):=\mathbb E f(X_t^\mu)$, where $t>0,$ $ f $ is a bounded measurable function, and $X_t^\mu$ solves a distribution dependent SDE with…

Probability · Mathematics 2021-03-12 Panpan Ren , Feng-Yu Wang

The distribution-dependent stochastic differential equations (DDSDEs) describe stochastic systems whose evolution is determined by both the microcosmic site and the macrocosmic distribution of the particle. The density function associated…

Probability · Mathematics 2017-04-18 Feng-Yu Wang

By establishing a local version of Bismut formula for Dirichlet semigroups on a regular domain, gradient estimates are derived for killed SDEs with singular drifts. As an application, the total variation distance between two solutions of…

Probability · Mathematics 2026-03-30 Feng-Yu Wang , Xiao-Yu Zhao

In this paper we present a unified approach to establish gradient type formulas and Bismut type formulas for backward stochastic differential equations (BSDEs). This approach relies on a mix of derivative formulas with respect to the…

Probability · Mathematics 2021-03-12 Xiliang Fan , Michael Röckner , Shao-Qin Zhang

Under nondegeneracy assumptions on the diffusion coefficients, we establish the derivative formulae of Bismut-Elworthy-Li's type for forward-backward stochastic differential equations with respect to Poisson random measure using the lent…

Probability · Mathematics 2025-12-30 Jiagang Ren , Hua Zhang

To characterize the Neumann problem for nonlinear Fokker-Planck equations, we investigate distribution dependent reflecting SDEs (DDRSDEs) in a domain. We first prove the well-posedness and establish functional inequalities for reflecting…

Probability · Mathematics 2021-10-26 Feng-Yu Wang

Due to their intrinsic link with nonlinear Fokker-Planck equations and many other applications, distribution dependent stochastic differential equations (DDSDEs for short) have been intensively investigated. In this paper we summarize some…

Probability · Mathematics 2020-12-29 Xing Huang , Panpan Ren , Feng-Yu Wang

In this paper we derive a Bismut-Elworthy formula under assumptions weaker than the non degeneracy of the noise. By Bismut-Elworthy formula we mean a gradient type estimate on the transition semigroup of a stochastic differential equation…

Probability · Mathematics 2026-05-11 Davide Addona , Federica Masiero

We develop a unified PDE-probabilistic framework for pointwise gradient and Hessian estimates of Markov semigroups associated with stochastic differential equations with singular and unbounded coefficients. Under mild local structural…

Probability · Mathematics 2026-04-02 Pengcheng Xia , Longjie Xie , Xicheng Zhang

Under integrability conditions on distribution dependent coefficients, existence and uniqueness are proved for McKean-Vlasov type SDEs with non-degenerate noise. When the coefficients are Dini continuous in the space variable, gradient…

Probability · Mathematics 2018-05-07 Xing Huang , Feng-Yu Wang

By using coupling method, a Bismut type derivative formula is established for the Markov semigroup associated to a class of hyperdissipative stochastic Navier-Stokes/Burgers equations. As applications, gradient estimates, dimension-free…

Probability · Mathematics 2010-09-09 Feng-Yu Wang , Lihu Xu

In this article we study (possibly degenerate) stochastic differential equations (SDE) with irregular (or discontiuous) coefficients, and prove that under certain conditions on the coefficients, there exists a unique almost everywhere…

Probability · Mathematics 2009-08-18 Xicheng Zhang

We propose a new type SDE depending on the future distributions with all initial values, and establish the correspondence between this equation and the associated singular nonlinear PDE. Well-posedness and regularities are investigated.

Analysis of PDEs · Mathematics 2022-11-14 Feng-yu Wang

In this paper we prove a derivative formula of Bismut-Elworthy-Li's type as well as gradient estimate for stochastic differential equations driven by $\alpha$-stable noises, where $\alpha\in(0,2)$. As an application, the strong Feller…

Probability · Mathematics 2012-04-24 Xicheng Zhang
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