Transport of Protostellar Cosmic Rays in Turbulent Dense Cores

Margot Fitz Axen, Stella S.S. Offner, Brandt A.L. Gaches, Chris L. Fryer, Aimee Hungerford, Kedron Silsbee

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5 Scopus citations

Abstract

Recent studies have suggested that low-energy cosmic rays (CRs) may be accelerated inside molecular clouds by the shocks associated with star formation. We use a Monte Carlo transport code to model the propagation of CRs accelerated by protostellar accretion shocks through protostellar cores. We calculate the CR attenuation and energy losses and compute the resulting flux and ionization rate as a function of both radial distance from the protostar and angular position. We show that protostellar cores have nonuniform CR fluxes that produce a broad range of CR ionization rates, with the maximum value being up to two orders of magnitude higher than the radial average at a given distance. In particular, the CR flux is focused in the direction of the outflow cavity, creating a "flashlight"effect and allowing CRs to leak out of the core. The radially averaged ionization rates are less than the measured value for the Milky Way of ζ ≈ 10-16 s-1; however, within r ≈ 0.03 pc from the protostar, the maximum ionization rates exceed this value. We show that variation in the protostellar parameters, particularly in the accretion rate, may produce ionization rates that are a couple of orders of magnitude higher or lower than our fiducial values. Finally, we use a statistical method to model unresolved subgrid magnetic turbulence in the core. We show that turbulence modifies the CR spectrum and increases the uniformity of the CR distribution but does not significantly affect the resulting ionization rates.

Original languageEnglish
Article number43
JournalAstrophysical Journal
Volume915
Issue number1
DOIs
StatePublished - Jul 1 2021
Externally publishedYes

Funding

This work was supported by the U.S. Department of Energy through the Los Alamos National Laboratory. Los Alamos National Laboratory is operated by Triad National Security, LLC, for the National Nuclear Security Administration of the U.S. Department of Energy (contract No. 89233218CNA000001) This research was supported in part by the National Science Foundation under grant No. NSF PHY-1748958 and by NASA ATP grant 80NSSC20K0507. This material is based on work supported by the U.S. Department of Energy, Office of Science, Office of Advanced Scientific Computing Research, Department of Energy Computational Science Graduate Fellowship under award No. DESC0021110. We thank an anonymous referee for helpful comments that improved the manuscript

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