Most stars form in binaries and the evolution of their discs remains poorly understood. To shed light on this subject, we carry out 3D ideal magnetohydrodynamic simulations with the adaptive mesh refinement code FLASH of binary star formation for separations of 10-20 au. We run a simulation with no initial turbulence (NT), and two with turbulent Mach numbers of Mach = sigma_v/c_s = 0.1 and 0.2 (T1 and T2) for 5000 yr after protostar formation. By the end of the simulations the circumbinary discs in NT and T1, if any, have radii of <~ 20 au with masses <~ 0.02 solar masses, while T2 hosts a circumbinary disc with radius ~ 70-80 au and mass ~ 0.12 solar masses. These circumbinary discs formed from the disruption of circumstellar discs and harden the binary orbit. Our simulated binaries launch large single outflows. We find that outflows of NT carry the most mass, and linear and angular momentum from the system. T2 produces the least efficient outflows concerning mass, momentum, and angular momentum (~61 per cent, ~71 per cent, ~68 per cent of the respective quantities in NT). We conclude that while turbulence helps to build circumbinary discs, which leads to the restructuring of magnetic fields for efficient outflow launching, too much turbulence may disrupt the ordered magnetic field structure required for magnetocentrifugal launching of jets. We conclude that the role of turbulence in building large circumbinary discs may explain some observed very old (> 10 Myr) circumbinary discs. The longer lifetime of circumbinary discs may increase the likelihood of planet formation.
The following movie shows gas density slices orientated along the dense accretion streams such that the slice captures the dense material and two sink particles for the disc simulation without turbulence (left), with turbulent Mach number 0.1 (middle) and turbulent Mach number 0.2 (right). The thin lines show the magnetic field, and the arrows indicate the velocity field. Crosses show the position of the sink particles (stars). The mass accreted by the sink particles in the simulations is indicated on the bottom left of each panel.
We thank the anonymous referee for insightful comments and improving this paper. R. K. would like to thank the Australian Government and the financial support provided by the Research Training Program Domestic Scholarship. C. F. acknowledges funding provided by the Australian Research Council (Discovery Projects DP150104329 and DP170100603, and Future Fellowship FT180100495), and the Australia-Germany Joint Research Cooperation Scheme (UA-DAAD). The simulations presented in this work used high performance computing resources provided by the Leibniz Rechenzentrum and the Gauss Centre for Supercomputing (grants pr32lo, pr48pi and GCS Large-scale project 10391), the Partnership for Advanced Computing in Europe (PRACE grant pr89mu), the Australian National Computational Infrastructure (grant ek9), and the Pawsey Supercomputing Centre with funding from the Australian Government and the Government of Western Australia, in the framework of the National Computational Merit Allocation Scheme and the ANU Allocation Scheme. The simulation software FLASH was in part developed by the DOE-supported Flash Center for Computational Science at the University of Chicago. yt (Turk et al. 2011) was used to help visualise and analyse these simulations.