Mathematics – Probability
Scientific paper
2011-05-18
Mathematics
Probability
Scientific paper
Let $D\subset R^d$ be a bounded domain and denote by $\mathcal P(D)$ the space of probability measures on $D$. Let \begin{equation*} L=\frac12\nabla\cdot a\nabla +b\nabla \end{equation*} be a second order elliptic operator. Let $\mu\in\mathcal P(D)$ and $\delta>0$. Consider a Markov process $X(t)$ in $D$ which performs diffusion in $D$ generated by the operator $\delta L$ and is stopped at the boundary, and which while running, jumps instantaneously, according to an exponential clock with spatially dependent intensity $V>0$, to a new point, according to the distribution $\mu$. The Markov process is generated by the operator $L_{\delta,\mu, V}$ defined by \begin{equation*} L_{\delta,\mu, V}\phi\equiv \delta L \phi+V(\int_D\phi d\mu-\phi). \end{equation*} %where $C_\mu$ is the % "$\mu$-centering" operator defined by %\begin{equation*} %C_\mu(\phi)=\phi-\int_D\phi d\mu. %\end{equation*} Let $\phi_{\delta,\mu,V}$ denote the solution to the Dirichlet problem \begin{equation*}\label{Dirprob} \begin{aligned} &L_{\delta,\mu,V}\phi=0\ \text{in}\ D;\\ &\phi=f\ \text{on}\ \partial D, \end{aligned} \end{equation*} where $f$ is continuous. The solution has the stochastic representation \begin{equation*} \phi_{\delta,\mu,V}(x)=E_xf(X(\tau_D)). \end{equation*} One has that $\phi_{0,\mu,V}(f)\equiv\lim_{\delta\to0}\phi_{\delta,\mu,V}(x)$ is independent of $x\in D$. We evaluate this constant in the case that $\mu$ has a density in a neighborhood of $\partial D$. We also study the asymptotic behavior as $\delta\to0$ of the principal eigenvalue $\lambda_0(\delta,\mu,V)$ for the operator $L_{\delta,\mu, V}$, which generalizes previously obtained results for the case $L=\frac12 \Delta$.
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