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arXiv 2006.09133math.PR
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由独立Lévy过程驱动的随机方程的转移半群的梯度公式

Gradient formula for transition semigroup corresponding to stochastic equation driven by a system of independent Lévy processes

Alexei Kulik, Szymon Peszat, Enrico Priola

摘要:

设$(P_t)$是由Markov $$ d X= b(X) dt + d Z, \qquad X(0)=x, $$定义的Markov族$(X^x(t))$的转移半群,其中$Z=\left(Z_1, \ldots, Z_d\right)^*$是独立实值Lévy过程系统.使用Malliavin演算,我们建立了以下梯度公式$$ \nabla P_tf(x)= \mathbb{E}\, f\left(X^x(t)\right) Y(t,x), \qquad f\in B_b(\mathbb{R}^d), $$,其中随机场$Y$不依赖于$f$。当$Z_1, \ldots , Z_d$是$α$ -稳定过程时,给出了关于$\nabla P_tf(x)$的精确估计,即$α\in (0,2)$.

英文摘要:

Let $(P_t)$ be the transition semigroup of the Markov family $(X^x(t))$ defined by SDE $$ d X= b(X) dt + d Z, \qquad X(0)=x, $$ where $Z=\left(Z_1, \ldots, Z_d\right)^*$ is a system of independent real-valued Lévy processes. Using the Malliavin calculus we establish the following gradient formula $$ \nabla P_tf(x)= \mathbb{E}\, f\left(X^x(t)\right) Y(t,x), \qquad f\in B_b(\mathbb{R}^d), $$ where the random field $Y$ does not depend on $f$. Sharp estimates on $\nabla P_tf(x)$ when $Z_1, \ldots , Z_d$ are $α$-stable processes, $α\in (0,2)$, are also given.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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