Magnetic fields play an important role for the formation of stars in both local and high-redshift galaxies. Recent studies of dynamo amplification in the first dark matter haloes suggest that significant magnetic fields were likely present during the formation of the first stars in the Universe at redshifts of 15 and above. In this work, we study how these magnetic fields potentially impact the initial mass function (IMF) of the first stars. We carry out 200 high-resolution, three-dimensional (3D), magnetohydrodynamic (MHD) simulations of the collapse of primordial clouds with different initial turbulent magnetic field strengths as predicted from turbulent dynamo theory in the early Universe, forming more than 1100 first stars in total. We detect a strong statistical signature of suppressed fragmentation in the presence of strong magnetic fields, leading to a dramatic reduction in the number of first stars with masses low enough that they might be expected to survive to the present day. Additionally, strong fields shift the transition point where stars go from being mostly single to mostly multiple to higher masses. However, irrespective of the field strength, individual simulations are highly chaotic, show different levels of fragmentation and clustering, and the outcome depends on the exact realisation of the turbulence in the primordial clouds. While the origin of primordial magnetic fields is still not fully understood, our work shows that primordial magnetic fields potentially have a larger impact on the primordial IMF than their counterparts have on the present-day IMF.
The following two movies show the density and temperature structure of a primordial disc forming the first stars in the Universe. The top panel is without a magnetic field and the bottom panel is with a strong magnetic field. Everything else is the same. This case is an (extreme) example of how magnetic fields can suppress fragmentation in primordial accretion discs.
This paper was primarily written during the 2019-2020 bushfire crisis in Australia. We dedicate this work to the emergency response personnel from Australia and elsewhere who have relentlessly protected the community from severe bushfires that raged all across the country, and ensured life goes on as normal during this calamity. PS is supported by an Australian Government Research Training Program (RTP) Scholarship. CF and MRK acknowledge funding provided by the Australian Research Council (ARC) through Discovery Projects DP170100603 (CF) and DP190101258 (MRK) and Future Fellowships FT180100495 (CF) and FT180100375 (MRK), and the Australia-Germany Joint Research Cooperation Scheme (UA-DAAD; both CF and MRK). MRK acknowledges support from an Alexander von Humboldt Research Award. The simulations and data analyses presented in this work used high-performance computing resources provided by the Australian National Computational Infrastructure (NCI) through projects ek9 (CF) and jh2 (MRK) in the framework of the National Computational Merit Allocation Scheme and the Australian National University (ANU) Allocation Scheme, and as part of a contribution by NCI to the ARC Centre of Excellence for All Sky Astrophysics in 3 Dimensions (ASTRO 3D, CE170100013). Parts of this paper were also written during the ASTRO 3D writing retreat in 2019. The simulation software FLASH was in part developed by the Department of Energy supported Flash Centre for Computational Science at the University of Chicago. Analysis was performed in ipython (Perez & Granger 2007) and Jupyter packages using yt (Turk et al. 2011), VisIt (Childs et al. 2012), numpy (Oliphant 2006) and scipy (Virtanen et al. 2020); plots were created using Matplotlib (Hunter 2007; Caswell et al. 2019). VisIt is supported by the Department of Energy with funding from the Advanced Simulation and Computing Program and the Scientific Discovery through Advanced Computing Program.