Flows for Singular Stochastic Differential Equations with Unbounded Drifts

Abstract

In this paper, we are interested in the following singular stochastic differential equation (SDE) $${\rm d} X_t = b(t,X_t) {\rm d} t + {\rm d} B_{t},\ 0\leq t\leq T,\ X_0 = x \in \mathbb{R}^d,$$ where the drift coefficient $b:[0,T]\times \mathbb{R}^{d}\longrightarrow \mathbb{R}^{d}$ is Borel measurable, possibly unbounded and has spatial linear growth. The driving noise $B_{t}$ is a $d-$ dimensional Brownian motion. The main objective of the paper is to establish the existence and uniqueness of a strong solution and a Sobolev differentiable stochastic flow for the above SDE. Malliavin differentiability of the solution is also obtained (cf.\cite{MMNPZ13, MNP2015}). Our results constitute significant extensions to those in \cite{Zvon74, Ver79, KR05, MMNPZ13, MNP2015} by allowing the drift $b$ to be unbounded. We employ methods from white-noise analysis and the Malliavin calculus. As application, we prove existence of a unique strong Malliavin differentiable solution to the following stochastic delay differential equation $${\rm d} X (t) = b (X(t-r), X(t,0,(v,\eta)) {\rm d} t + {\rm d} B(t), \,t \geq 0 ,\textbf{ } (X(0), X_0)= (v, \eta) \in \mathbb{R}^d \times L^2 ([-r,0], \mathbb{R}^d),$$ with the drift coefficient $b: \mathbb{R}^d \times \mathbb{R}^d \rightarrow \mathbb{R}^d$ is a Borel-measurable function bounded in the first argument and has linear growth in the second argument.