Polydisperse Streaming Instability I. Tightly coupled particles and the terminal velocity approximation

TL;DR

This paper develops a polydisperse streaming instability model for dust-gas mixtures, revealing distinct behaviors from monodisperse cases, especially under the terminal velocity approximation, with implications for planetesimal formation.

Contribution

It introduces a polydisperse version of the streaming instability and analyzes its behavior under the terminal velocity approximation, highlighting differences from the monodisperse case.

Findings

Unstable modes exist for tightly coupled particles with exponential growth.

Growth rates depend on dust-to-gas ratios and Stokes numbers, differing from monodisperse predictions.

No growing modes at small wave numbers under the terminal velocity approximation.

Abstract

We introduce a polydisperse version of the streaming instability, where the dust component is treated as a continuum of sizes. We show that its behaviour is remarkably different from the monodisperse streaming instability. We focus on tightly coupled particles in the terminal velocity approximation and show that unstable modes that grow exponentially on a dynamical time scale exist. However, for dust to gas ratios much smaller than unity they are confined to radial wave numbers that are a factor $\sim 1/\overline{\rm St}$ larger than where the monodisperse streaming instability growth rates peak. Here $\overline{\rm St} \ll 1$ is a suitable average Stokes number for the dust size distribution. For dust to gas ratios larger than unity, polydisperse modes that grow on a dynamical time scale are found as well, similar as for the monodisperse streaming instability and at similarly large wave numbers. At smaller wave numbers, where the classical monodisperse streaming instability shows secular growth, no growing polydisperse modes are found under the terminal velocity approximation. Outside the region of validity for the terminal velocity approximation, we have found unstable epicyclic modes that grow on $\sim 10^4$ dynamical time scales.