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Protostellar collapse: regulation of the angular momentum and onset of an ionic precursor

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 Added by Pierre Marchand
 Publication date 2020
  fields Physics
and research's language is English




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Through the magnetic braking and the launching of protostellar outflows, magnetic fields play a major role in the regulation of angular momentum in star formation, which directly impacts the formation and evolution of protoplanetary disks and binary systems. The aim of this paper is to quantify those phenomena in the presence of non-ideal magnetohydrodynamics effects, namely the Ohmic and ambipola r diffusion. We perform three-dimensional simulations of protostellar collapses varying the mass of the prestellar dense core, the thermal support (the $alpha$ ratio) and the dust grain size-distribu tion. The mass mostly influences the magnetic braking in the pseudo-disk, while the thermal support impacts the accretion rate and hence the properties of the disk. Removing the grains smaller than 0. 1 $mu$m in the Mathis, Rumpl, Nordsieck (MRN) distribution enhances the ambipolar diffusion coefficient. Similarly to previous studies, we find that this change in the distribution reduces the magnet ic braking with an impact on the disk. The outflow is also significantly weakened. In either case, the magnetic braking largely dominates the outflow as a process to remove the angular momentum from t he disk. Finally, we report a large ionic precursor to the outflow with velocities of several km s$^{-1}$, which may be observable.



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[abridged] Understanding how the infalling gas redistribute most of its initial angular momentum inherited from prestellar cores before reaching the stellar embryo is a key question. Disk formation has been naturally considered as a possible solution to this angular momentum problem. However, how the initial angular momentum of protostellar cores is distributed and evolves during the main accretion phase and the beginning of disk formation has largely remained unconstrained up to now. In the framework of the IRAM CALYPSO survey, we used high dynamic range C$^{18}$O (2-1) and N$_2$H$^+$ (1-0) observations to quantify the distribution of specific angular momentum along the equatorial axis in a sample of 12 Class 0 protostellar envelopes from scales ~50 to 10000 au. The radial distributions of specific angular momentum in the CALYPSO sample suggest two distinct regimes within protostellar envelopes: the specific angular momentum decreases as $j propto r^{1.6 pm 0.2}$ down to ~1600 au and then tends to become relatively constant around 6 $times$ 10$^{-4}$ km s$^{-1}$ pc down to ~50 au. The values of specific angular momentum measured in the inner Class 0 envelopes, namely that of the material directly involved in the star formation process ($<$1600 au), is on the same order of magnitude as what is inferred in small T-Tauri disks. Thus, disk formation appears to be a direct consequence of angular momentum conservation during the collapse. Our analysis reveals a dispersion of the directions of velocity gradients at envelope scales $>$1600 au, suggesting that they may not be related to rotational motions of the envelopes. We conclude that the specific angular momentum observed at these scales could find its origin in core-forming motions (infall, turbulence) or trace an imprint of the initial conditions for the formation of protostellar cores.
We present the results of a suite of numerical simulations designed to explore the origin of the angular momenta of protostellar cores. Using the hydrodynamic grid code emph{Athena} with a sink implementation, we follow the formation of protostellar cores and protostars (sinks) from the subvirial collapse of molecular clouds on larger scales to investigate the range and relative distribution of core properties. We find that the core angular momenta are relatively unaffected by large-scale rotation of the parent cloud; instead, we infer that angular momenta are mainly imparted by torques between neighboring mass concentrations and exhibit a log-normal distribution. Our current simulation results are limited to size scales $sim 0.05$~pc ($sim 10^4 rm AU$), but serve as first steps toward the ultimate goal of providing initial conditions for higher-resolution studies of core collapse to form protoplanetary disks.
Building on our previous hydrodynamic study of the angular momenta of cloud cores formed during gravitational collapse of star-forming molecular gas in our previous work, we now examine core properties assuming ideal magnetohydrodynamics (MHD). Using the same sink-patch implementation for the emph{Athena} MHD code, we characterize the statistical properties of cores, including the mass accretion rates, specific angular momenta, and alignments between the magnetic field and the spin axis of the core on the $0.1 mathrm{pc}$ scale. Our simulations, which reproduce the observed relation between magnetic field strength and gas density, show that magnetic fields can help collimate low density flows and help seed the locations of filamentary structures. Consistent with our previous purely hydrodynamic simulations, stars (sinks) form within the heterogeneous environments of filaments, such that accretion onto cores is highly episodic leading to short-term variability but no long-term monotonic growth of the specific angular momenta. With statistical characterization of protostellar cores properties and behaviors, we aim to provide a starting point for building more realistic and self-consistent disk formation models, helping to address whether magnetic fields can prevent the development of (large) circumstellar disks in the ideal MHD limit.
The formation of stars is usually accompanied by the launching of protostellar outflows. Observations with the Atacama Large Millimetre/sub-millimetre Array (ALMA) will soon revolutionalise our understanding of the morphologies and kinematics of these objects. In this paper, we present synthetic ALMA observations of protostellar outflows based on numerical magnetohydrodynamic collapse simulations. We find significant velocity gradients in our outflow models and a very prominent helical structure within the outflows. We speculate that the disk wind found in the ALMA Science Verification Data of HD 163296 presents a first instance of such an observation.
The late collapse, core bounce, and the early postbounce phase of rotating core collapse leads to a characteristic gravitational wave (GW) signal. The precise shape of the signal is governed by the interplay of gravity, rotation, nuclear equation of state (EOS), and electron capture during collapse. We explore the dependence of the signal on total angular momentum and its distribution in the progenitor core by means of a large set of axisymmetric general-relativistic core collapse simulations in which we vary the initial angular momentum distribution in the core. Our simulations include a microphysical finite-temperature EOS, an approximate electron capture treatment during collapse, and a neutrino leakage scheme for the postbounce evolution. We find that the precise distribution of angular momentum is relevant only for very rapidly rotating cores with T/|W|>~8% at bounce. We construct a numerical template bank from our baseline set of simulations, and carry out additional simulations to generate trial waveforms for injection into simulated advanced LIGO noise at a fiducial galactic distance of 10 kpc. Using matched filtering, we show that for an optimally-oriented source and Gaussian noise, advanced Advanced LIGO could measure the total angular momentum to within ~20%, for rapidly rotating cores. For most waveforms, the nearest known degree of precollapse differential rotation is correctly inferred by both our matched filtering analysis and an alternative Bayesian model selection approach. We test our results for robustness against systematic uncertainties by injecting waveforms from simulations using a different EOS and and variations in the electron fraction in the inner core. The results of these tests show that these uncertainties significantly reduce the accuracy with which the total angular momentum and its precollapse distribution can be inferred from observations.
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