Space and time correlations for diffusion models with prompt and delayed birth-and-death events.

Abstract

Understanding the statistical properties of a collection of individuals subject to random displacements and birth-and-death events is key to several applications in physics and life sciences, encompassing the diagnostic of nuclear reactors and the analysis of epidemic patterns. Previous investigations of the critical regime, where births and deaths balance on average, have shown that highly non-Poissonian fluctuations might occur in the population, leading to spontaneous spatial clustering, and eventually to a "critical catastrophe," where fluctuations can result in the extinction of the population. A milder behavior is observed when the population size is kept constant: the fluctuations asymptotically level off and the critical catastrophe is averted. In this paper, we extend these results by considering the broader class of models with prompt and delayed birth-and-death events, which mimic the presence of precursors in nuclear reactor physics or incubation in epidemics. We consider models with and without population control mechanisms. Analytical or semi-analytical results for the density, the two-point correlation function, and the mean-squared pair distance will be derived and compared with Monte Carlo simulations, which will be used as a reference.