Position distribution in a generalised run and tumble process

Abstract

We study a class of stochastic processes of the type $\frac{d^{n}x}{d{t}^n}=v_0\sigma (t)$ where $n>0$ is a positive integer and $\sigma (t)=\pm 1$ represents an `active' telegraphic noise that flips from one state to the other with a constant rate $\gamma$. For $n=1$, it reduces to the standard run and tumble process for active particles in one dimension. This process can be analytically continued to any $n>0$ including non-integer values. We compute exactly the mean squared displacement at time $t$ for all $n>0$ and show that at late times while it grows as $\sim t^{2n-1}$ for $n>1/2$, it approaches a constant for $n<1/2$. In the marginal case $n=1/2$, it grows very slowly with time as $\sim \ln t$. Thus the process undergoes a {\em localisation} transition at $n=1/2$. We also show that the position distribution $p_n(x,t)$ remains time-dependent even at late times for $n\ge 1/2$, but approaches a stationary time-independent form for $n<1/2$. The tails of the position distribution at late times exhibit a large deviation form, $p_n(x,t)\sim \exp \left[-\gamma t{\Phi }_n\left(\frac{x}{x^{\ast }(t)}\right)\right]$, where $x^{\ast }(t)=v_0{t}^n/\Gamma (n+1)$. We compute the rate function ${\Phi }_n(z)$ analytically for all $n>0$ and also numerically using importance sampling methods, finding excellent agreement between them. For three special values $n=1$, $n=2$ and $n=1/2$ we compute the exact cumulant generating function of the position distribution at all times $t$.

24 pages, 4 Figures

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