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We consider a telegraph process with elastic boundary at the origin studied recently in the literature. It is a particular random motion with finite velocity which starts at $xgeq 0$, and its dynamics is determined by upward and downward switching rates $lambda$ and $mu$, with $lambda>mu$, and an absorption probability (at the origin) $alphain(0,1]$. Our aim is to study the asymptotic behavior of the absorption time at the origin with respect to two different scalings: $xtoinfty$ in the first case; $mutoinfty$, with $lambda=betamu$ for some $beta>1$ and $x>0$, in the second case. We prove several large and moderate deviation results. We also present numerical estimates of $beta$ based on an asymptotic Normality result for the case of the second scaling.
We study the asymmetric one-dimensional telegraph process in the bounded domain. Lower boundary is absorbing and upper boundary is reflecting with delay. Point stays in the upper boundary until switch of regime occurs. We obtain the distribution of this process in terms of Laplace trasforms.
We consider the last zero crossing time $T_{mu,t}$ of a Brownian motion, with drift $mu eq 0$ in the time interval $[0, t]$. We prove the large deviation principle of ${T_{mu sqrt r t} : r > 0 }$ as $r$ tends to infinity. Moreover, motivated by the
We investigate the macroscopic behavior of asymmetric attractive zero-range processes on $mathbb{Z}$ where particles are destroyed at the origin at a rate of order $N^beta$, where $beta in mathbb{R}$ and $Ninmathbb{N}$ is the scaling parameter. We pr
We consider the process ${x-N(t):tgeq 0}$, where $x>0$ and ${N(t):tgeq 0}$ is a renewal process with light-tailed distributed holding times. We are interested in the joint distribution of $(tau(x),A(x))$ where $tau(x)$ is the first-passage time of ${
We formulate and prove a shape theorem for a continuous-time continuous-space stochastic growth model under certain general conditions. Similarly to the classical lattice growth models the proof makes use of the subadditive ergodic theorem. A precise