# The dependence of protostar formation on the geometry and strength of the initial magnetic field

Author Lewis, Benjamin T · Bate, Matthew R 2017 See all Details

#### Abstract

We report results from twelve simulations of the collapse of a molecular cloud core to form one or more protostars, comprising three field strengths (mass-to-flux ratios, {\mu}, of 5, 10, and 20) and four field geometries (with values of the angle between the field and rotation axes, {\theta}, of 0{\deg}, 20{\deg}, 45{\deg}, and 90{\deg}), using a smoothed particle magnetohydrodynamics method. We find that the values of both parameters have a strong effect on the resultant protostellar system and outflows. This ranges from the formation of binary systems when {\mu} = 20 to strikingly differing outflow structures for differing values of {\theta}, in particular highly suppressed outflows when {\theta} = 90{\deg}. Misaligned magnetic fields can also produce warped pseudo-discs where the outer regions align perpendicular to the magnetic field but the innermost region re-orientates to be perpendicular to the rotation axis. We follow the collapse to sizes comparable to those of first cores and find that none of the outflow speeds exceed 8 km s$^{-1}$. These results may place constraints on both observed protostellar outflows, and also on which molecular cloud cores may eventually form either single stars and binaries: a sufficiently weak magnetic field may allow for disc fragmentation, whilst conversely the greater angular momentum transport of a strong field may inhibit disc fragmentation.

### Details

Title The dependence of protostar formation on the geometry and strength of the initial magnetic field Lewis, Benjamin T · Bate, Matthew R 2017 Research Article eng Accepted for publication in MNRAS. 14 pages, 14 figures. Animations are other details can be found at http://www.astro.ex.ac.uk/people/blewis/research/outflows_weak_fields.html 2017-01-30 00:00:00
This is Version 1 of this record. We added this version on February 1, 2017. This version is based on an original data import from arXiv.org e-Print archive.