从无穷远处快速返回的马氏过程的拟平稳分布的存在唯一性
Existence and uniqueness of a quasi-stationary distribution for Markov processes with fast return from infinity
摘要：
我们研究了马尔可夫过程在$\mathbb{N}$中演化的长时间行为，条件是不达到0。假设该过程很快从无穷大返回，我们证明了该过程允许一个唯一的准平稳分布（特别是，当时间趋于无穷大时，条件过程的分布允许一个极限）。此外，我们证明了该过程的分布在全变差范数下指数快速收敛到其拟平稳分布，并给出了一个明确的收敛速率。作为我们结果的第一个应用，我们对出生和死亡过程的准平稳分布的收敛速度提出了新的见解：我们证明了这些过程当且仅当它们具有唯一的准平稳分布时以指数方式快速收敛到准平稳分布。此外，考虑到可数空间上非不可约过程的拟平稳分布的结果缺乏，作为我们结果的第二个应用，我们证明了一类可能非不可约过程的拟平稳分布的存在性和唯一性.
英文摘要：
We study the long time behaviour of a Markov process evolving in $\mathbb{N}$ and conditioned not to hit 0. Assuming that the process comes back quickly from infinity, we prove that the process admits a unique quasi-stationary distribution (in particular, the distribution of the conditioned process admits a limit when time goes to infinity). Moreover, we prove that the distribution of the process converges exponentially fast in total variation norm to its quasi-stationary distribution and we provide an explicit rate of convergence. As a first application of our result, we bring a new insight on the speed of convergence to the quasi-stationary distribution for birth and death processes: we prove that these processes converge exponentially fast to a quasi-stationary distribution if and only if they have a unique quasi-stationary distribution. Also, considering the lack of results on quasi-stationary distributions for non-irreducible processes on countable spaces, we show, as a second application of our result, the existence and uniqueness of a quasi-stationary distribution for a class of possibly non-irreducible processes.
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