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Suprio Bhar

Publications and source records attributed to Suprio Bhar.

23 records · Page 2Linked to original sources

Smoothness of Flow and Path-by-Path Uniqueness in Stochastic Differential Equations

We consider the stochastic differential equation $$ X_t = x_0 + \int_0^t f(X_s)ds + \int_0^tσ(X_s)dB^{H}_s,$$ with $x_0 \in \mathbb{R}^d$, $d \geq 1$, $f: \mathbb{R}^d \rightarrow \mathbb{R}^d$ is bounded continuous, $σ: \mathbb{R}^d \rightarrow \mathbb{R}^{d\times d}$ is a uniformly elliptic, bounded, twice continuously differentiable conservative vector field and $B^H$ is fractional Brownian motion with $H \in (\frac{1}{3}, \frac{1}{2}]$. When $d=1$, $H= \frac{1}{2}$, and $f$ is Hölder continuous, in the spirit of Davie [D07], we establish the existence of a null set $\mathcal{N}$ depending only on $f, σ$ such that for all $x_0\in \mathbb{R}$ and $ω\in Ω\setminus \mathcal{N}$, the above equation admits a path-by-path unique solution. Our proof is based on establishing the uniform continuous differentiability of the flow associated with the equation. We also establish the path-by-path uniqueness for $d \geq 1$ and $H \in (\frac{1}{3}, \frac{1}{2}]$, but the null set may depend on $x_0$, thus extending a result of Catellier-Gubinelli [CG12].

math.PR↗

Solutions of SPDE's associated with a stochastic flow

We consider the following stochastic partial differential equation, \begin{align*} &dY_t=L^\ast Y_tdt+A^\ast Y_t\cdot dB_t\\ &Y_0=ψ, \end{align*} associated with a stochastic flow $\{X(t,x)\}$, for $t \geq 0$, $x \in \mathbb{R}^d$, as in [Rajeev \& Thangavelu, \emph{Probabilistic representations of solutions of the forward equations}, Potential Anal. \textbf{28} (2008), no.~2, 139--162]. We show that the strong solutions constructed there are `locally of compact support'. Using this notion,we define the mild solutions of the above equation and show the equivalence between strong and mild solutions in the multi Hilbertian space $\mathcal{S}^\prime$. We show uniqueness of solutions in the case when $ψ$ is smooth via the `monotonicity inequality' for $(L^\ast,A^\ast)$, which is a known criterion for uniqueness.

math.PR↗

Stationary solutions of stochastic partial differential equations in the space of tempered distributions

In Rajeev (2013), 'Translation invariant diffusion in the space of tempered distributions', it was shown that there is an one to one correspondence between solutions of a class of finite dimensional SDEs and solutions of a class of SPDEs in $\mathcal{S}'$, the space of tempered distributions, driven by the same Brownian motion. There the coefficients $\barσ, \bar{b}$ of the finite dimensional SDEs were related to the coefficients of the SPDEs in $\mathcal{S}'$ in a special way, viz. through convolution with the initial value $y$ of the SPDEs. In this paper, we consider the situation where the solutions of the finite dimensional SDEs are stationary and ask whether the corresponding solutions of the equations in $\mathcal{S}'$ are also stationary. We provide an affirmative answer, when the initial random variable takes value in a certain set $\mathcal{C}$, which ensures that the coefficients of the finite dimensional SDEs are related to the coefficients of the SPDEs in the above `special' manner.

math.PR↗

An Itō formula in the space of tempered distributions

We extend the Itō formula \cite{MR1837298}*{Theorem 2.3} for semimartingales with rcll paths. We also comment on Local time process of such semimartingales. We apply the Itō formula to Lévy processes to obtain existence of solutions to certain classes of stochastic differential equations in the Hermite-Sobolev spaces.

math.PR↗