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Published November 2022 | public
Journal Article

Dust in the wind with resonant drag instabilities – I. The dynamics of dust-driven outflows in GMCs and Hɪɪ regions

Abstract

Radiation-dust driven outflows, where radiation pressure on dust grains accelerates gas, occur in many astrophysical environments. Almost all previous numerical studies of these systems have assumed that the dust was perfectly coupled to the gas. However, it has recently been shown that the dust in these systems is unstable to a large class of 'resonant drag instabilities' (RDIs) which de-couple the dust and gas dynamics and could qualitatively change the non-linear outcome of these outflows. We present the first simulations of radiation-dust driven outflows in stratified, inhomogeneous media, including explicit grain dynamics and a realistic spectrum of grain sizes and charge, magnetic fields and Lorentz forces on grains (which dramatically enhance the RDIs), Coulomb and Epstein drag forces, and explicit radiation transport allowing for different grain absorption and scattering properties. In this paper, we consider conditions resembling giant molecular clouds (GMCs), Hɪɪ regions, and distributed starbursts, where optical depths are modest (≲1), single-scattering effects dominate radiation-dust coupling, Lorentz forces dominate over drag on grains, and the fastest-growing RDIs are similar, such as magnetosonic and fast-gyro RDIs. These RDIs generically produce strong size-dependent dust clustering, growing non-linear on time-scales that are much shorter than the characteristic times of the outflow. The instabilities produce filamentary and plume-like or 'horsehead' nebular morphologies that are remarkably similar to observed dust structures in GMCs and Hɪɪ regions. Additionally, in some cases they strongly alter the magnetic field structure and topology relative to filaments. Despite driving strong micro-scale dust clumping which leaves some gas 'behind,' an order-unity fraction of the gas is always efficiently entrained by dust.

Additional Information

Support for PFH was provided by NSF Research Grants 1911233 and 20009234, NSF CAREER grant 1455342, NASA grants 80NSSC18K0562, HST-AR-15800.001-A. Numerical calculations were run on the Caltech compute cluster 'Wheeler,' allocations FTA-Hopkins supported by the NSF and TACC, and NASA HEC SMD-16-7592. Support for ALR was provided by the Institute for Theory & Computation at Harvard University. GVP acknowledges support by NASA through the NASA Hubble Fellowship grant # HST-HF2-51444.001-A.

Additional details

Created:
August 22, 2023
Modified:
October 24, 2023