Anomalous Power Law Distribution of Total Lifetimes of Branching   Processes Relevant to Earthquakes
  We consider a branching model of triggered seismicity, the ETAS (epidemic-type aftershock sequence) model which assumes that each earthquake can trigger other earthquakes (``aftershocks''). An aftershock sequence results in this model from the cascade of aftershocks of each past earthquake. Due to the large fluctuations of the number of aftershocks triggered directly by any earthquake (``productivity'' or ``fertility''), there is a large variability of the total number of aftershocks from one sequence to another, for the same mainshock magnitude. We study the regime where the distribution of fertilities $\mu$ is characterized by a power law $\sim 1/\mu^{1+\gamma}$ and the bare Omori law for the memory of previous triggering mothers decays slowly as $\sim 1/t^{1+\theta}$, with $0 < \theta <1$ relevant for earthquakes. Using the tool of generating probability functions and a quasistatic approximation which is shown to be exact asymptotically for large durations, we show that the density distribution of total aftershock lifetimes scales as $\sim 1/t^{1+\theta/\gamma}$ when the average branching ratio is critical ($n=1$). The coefficient $1<\gamma = b/\alpha<2$ quantifies the interplay between the exponent $b \approx 1$ of the Gutenberg-Richter magnitude distribution $ \sim 10^{-bm}$ and the increase $\sim 10^{\alpha m}$ of the number of aftershocks with the mainshock magnitude $m$ (productivity) with $\alpha \approx 0.8$. More generally, our results apply to any stochastic branching process with a power-law distribution of offsprings per mother and a long memory. 
A. Saichev (Nizhny Novgorod) and D. Sornette (UCLA and CNRS-Univ.   Nice)