ENCUESTA A DOCENTES

Simulations of binary and multiple star formation have been explored through var- ious avenues, including cluster simulations (Bate 2012; Dorval et al. 2017; Belloni et al. 2017; Jones & Bate 2018) and formation from fragmenting molecular cores (Goodwin et al. 2004; Tomisaka et al. 2004; Price & Bate 2007; Machida et al. 2009; Seifried et al. 2013; Offner et al. 2016; Lewis & Bate 2017; Matsumoto et al. 2017). The two main pathways for binary star formation are determined to be either via the fragmentation of the parent molecular core, or the fragmentation of mas- sive protostellar discs. Simulations with varying levels of input physics argue which formation pathway is mostly likely for different types of binary systems. The sim- plest models investigated the collapse of rotating molecular cores. Because these molecular cores inherit angular momentum from their parent clouds, the cores are also rotating. These simple simulations find that clouds with angular frequencies (Ω) greater than 20% of the cloud free-fall time (tf f) fragment easily into multiple protostars (Bodenheimer 1978; Boss & Bodenheimer 1979; Banerjee et al. 2004). Banerjee et al. (2004) find in these simulations that disc fragmentation occurs fre- quently, as well as cloud fragmentation. However, this frequency of fragmentation changes when further physics in introduced.

The introduction of ideal MHD provides magnetic pressure support that can reduce the collapse rate. Magnetic fields are integral for launching protostellar out- flows and must be considered when studying star formation. The mass-to-flux ratio is discussed previously in Section 1.1. Hennebelle & Teyssier (2008) find magnetic pressure can also prevent cloud fragmentation and rotation alone cannot lead to efficient fragmentation, unless the rotation rates are significantly high (Banerjee & Pudritz 2006). They also suggest that strong density perturbations are necessary in the initial cloud core to overcome the magnetic pressure, or other mechanisms such as ambipolar diffusion to reduce the magnetic field strength, for cloud fragmentation to occur (Hennebelle & Teyssier 2008). B¨urzle et al. (2011) also find that strong magnetic fields suppress fragmentation within a core, but found that the magnetic

1.3 Previous simulations of binary star formation 41

‘cushion’ created in circumstellar discs surrounding individual components in a bi- nary aided binary fragmentation. Price & Bate (2007) find that the orientation of the magnetic field to the rotation axis can either hinder (when they are parallel) or aid (perpendicular) fragmentation. However, based on simulations of molecu- lar core collapse Tomisaka et al. (2004) find that even if the initial magnetic field and angular momentum vector are misaligned, the resulting disc is perpendicular to the magnetic field, but the inner disc remains aligned perpendicular to the rotation axis (Lewis & Bate 2017). Tomisaka et al. (2004) Also find that despite magnetic pressure suppressing core fragmentation, the discs formed were able to fragment into binary star systems (Machida et al. 2004). All of these studies find that cores with sufficient density perturbations will fragment in the presence of even strong magnetic fields.

Despite ideal MHD showing magnetic fields can hinder fragmentation, non-ideal MHD effects have been employed to help overcome the magnetic pressure preventing fragmentation. While ambipolar diffusion can help a sub-critical molecular core become supercritical, the magnetic pressure can continue to suppress fragmentation (Hosking & Whitworth 2004). Machida et al. (2008) and Machida et al. (2009) also find that fragmentation of molecular cores is only possible after the magnetic field strength is reduced via Ohmic dissipation. Wurster et al. (2017) carried out a comprehensive study of the effect of Ohmic dissipation, the Hall effect and ambipolar diffusion on binary star formation in perturbed molecular cores with varying initial orientation of the magnetic field to the rotation axis. Overall they find that the non-ideal effects have only a small impact on binary formation and early evolution, with the initial conditions playing the dominant role.

Radiation feedback should also be considered when modelling binary star forma- tion, because young stars are very luminous objects. Previous simulations of star formation with radiation feedback find that fragmentation in molecular cores and massive discs is suppressed due to the increased temperature leading to larger Jeans lengths within the gas (Krumholz et al. 2007; Offner et al. 2009; Bate 2012; Feder- rath et al. 2017). Federrath et al. (2017) and Cunningham et al. (2018) find that radiation feedback plays the dominant role of fragmentation suppression in molecu- lar cores. Despite radiation feedback helping to suppress fragmentation, Bate (2012)

find that gravity and gas dynamics have a greater influence in determining the prop- erties of the formed multiple star systems. Radiation feedback in discs is found to be strong than feedback during the initial molecular cloud collapse, leading to the conclusion that binaries form predominantly via core fragmentation rather than disc instabilities (Offner et al. 2010).

While magnetic fields and radiation may suppress fragmentation, the predom- inant mechanism leading to the formation of binary and multiple star systems is turbulence creating overdensities. Simulations of molecular cloud fragmentation with varying levels of turbulence generally find that stronger turbulence leads to stronger fragmentation (Goodwin et al. 2004). Turbulent simulations produce Kep- lerian discs which planets can form in (Seifried et al. 2013).

Numerical simulations are a good tool for exploring how various physics influ- ences binary star formation, however, they are not useful without being compared with observation. Synthetic observations can be produced from these simulations using radiative transfer codes such as RADMC3D (Dullemond et al. 2012), Polaris

(Reissl et al. 2016) orPyRaTe(Tritsis et al. 2018). These techniques can produce im- ages from a 3D structures and convolve them with a point spread function simulating observational data. The main difficulty in comparing simulations to observations is due to projection effects and varying opacities (Haworth et al. 2018). Bertram et al. (2014) compared synthetic 12CO and 13CO maps produced by RADMC3D with their physical 3D positions of H2 and CO in turbulent simulations. They find that the

synthetic observations are able to trace dense environments well where the hydrogen is mostly molecular, but fails for low density environments. Bertram et al. (2015) find that the CO gradients produced by synthetic observations are shallower than that produced by the 3D simulation. Similarly, based on comparisons to synthetic observations and 3D simulations, Offner & Arce (2014) find that 12CO would be ideal to trace protostellar outflows.