7 papers
Quasi-stationary distributions for time-changed symmetric -stable processes killed upon hitting zero
Zhe-Kang Fang, Yong-Hua Mao, Tao Wang
For a time-changed symmetric -stable process killed upon hitting zero, under the condition of entrance from infinity, we prove the existence and uniqueness of quasi-stationary d…
Dirichlet eigenvalues and exit time moments for symmetric Markov processes
Lu-Jing Huang, Tao Wang
We give some relationships between the first Dirichlet eigenvalues and the exit time moments for the general symmetric Markov processes. As applications, we present some examples,…
Ergodic convergence rates for time-changed symmetric Lévy processes in dimension one
Tao Wang
We obtain the lower bounds for ergodic convergence rates, including spectral gaps and convergence rates in strong ergodicity for time-changed symmetric Lévy processes by using harm…
Variational principles for asymptotic variance of general Markov processes
Lu-Jing Huang, Yong-Hua Mao, Tao Wang
A variational formula for the asymptotic variance of general Markov processes is obtained. As application, we get a upper bound of the mean exit time of reversible Markov processes…
Convergence Rates in Uniform Ergodicity by Hitting Times and -exponential Convergence Rates
Yong-Hua Mao, Tao Wang
Generally the convergence rate in exponential ergodicity is an upper bound for the convergence rate in uniform ergodicity for a Markov process, that is . In th…
Variational formulas for the exit time of Hunt processes generated by semi-Dirichlet forms
Lu-Jing Huang, Kyung-Youn Kim, Yong-Hua Mao +1
Variational formulas for the Laplace transform of the exit time from an open set of a Hunt process generated by a regular lower bounded semi-Dirichlet form are established. While f…
Lyapunov-type Conditions for Non-strong Ergodicity of Markov Processes
Yong-Hua Mao, Tao Wang
We present Lyapunov-type conditions for non-strong ergodicity of Markov processes. Some concrete models are discussed including diffusion processes on Riemannian manifolds and Orns…