Active stop and go motion: A strategy to improve spatial exploration and survival

We consider active Brownian particles that intermittently switch between active and inactive states. Such behavior is ubiquitous at all scales, from bacteria to animals and in artificial active systems. We derive exact expressions for key transport properties, including velocity autocorrelations and diffusion coefficients, and demonstrate that particle dispersion is highly sensitive to minute details, such as whether the memory of active orientation is retained across a stop event. Extending the stop-and-go model to include minimal metabolic dynamics, we show that the average survival time of an intermittently moving particle is maximized at (i) an optimal stopping frequency and (ii) a nontrivial optimal diffusivity, which itself depends on the stopping frequency.