中文

测度变换下扩散过程泛函的分数光滑性

概率论 2012-10-18 v1 偏微分方程分析 泛函分析

摘要

v:[0,T]×RdRv:[0,T]\times \R^d \to \R为抛物型向后方程\partial_t v + (1/2) \sum_{i,l} [\sigma \sigma^\perp]_{il} \partial_{x_i \partial_{x_l} v + \sum_{i} b_i \partial_{x_i}v + kv =0的解,其终端条件为gg,其中系数依赖于时间和状态,并满足一定的正则性假设。设X=(Xt)t[0,T]X=(X_t)_{t\in [0,T]}为定义在某个适当的(Ω,\cF,\Q)(\Omega,\cF,\Q)上的相关Rd\R^d值扩散过程。对于p[2,)p\in [2,\infty)和测度d=λTd\Qd\P=\lambda_T d\Q(其中λT\lambda_Tα(1,p)\alpha \in (1,p)满足 Muckenhoupt 条件AαA_\alpha),我们将g(XT)\eptg(XT)Lp()\|g(X_T)-\ept g(X_T) \|_{L_p(\P)}v(t,Xt)Lp()\|\nabla v(t,X_t) \|_{L_p(\P)}D2v(t,Xt)Lp()\|D^2 v(t,X_t) \|_{L_p(\P)}的行为相互关联起来,其中D^2v:=(\partial_{x_i \partial_{x_l}v)_{i,l}为 Hessian 矩阵。

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引用

@article{arxiv.1210.4572,
  title  = {Fractional smoothness of functionals of diffusion processes under a change of measure},
  author = {Stefan Geiss and Emmanuel Gobet},
  journal= {arXiv preprint arXiv:1210.4572},
  year   = {2012}
}