Exactly Solvable Population Model with Square-Root Growth Noise and Cell-Size Regulation

Abstract

Stochastic exponential growth is nearly ubiquitous across cellular life, but how its microscopic noise structure shapes population growth remains poorly understood. Here, we introduce an exactly solvable population model in which cells grow exponentially with fluctuations that scale with the square root of cell size, and divide according to general size-control mechanisms. Our first result is that the population growth rate is exactly equal to the mean single-cell growth rate, for all noise strengths and for all division and size-regulation schemes that maintain size homeostasis. Thus square-root growth noise does not affect long-term fitness, in sharp contrast to models with size-independent stochastic growth rates. Second, we derive an exact solution for the steady-state distribution of cell sizes in the population and show that it is broadened by growth fluctuations. Third, the mean-rescaled population size $N_t/\langle N_t \rangle$ converges to a stationary compound Poisson-exponential distribution that depends only on growth noise. This distribution, and hence the long-time shape of population-size fluctuations, is unchanged by division-size noise or asymmetric partitioning. These results identify Feller-type exponential growth with square-root noise as an exactly solvable benchmark for stochastic growth in size-controlled populations and provide concrete signatures that distinguish it from models with size-independent growth-rate noise.