Impact of Protostellar Outflows on Turbulence and Star Formation Efficiency in Magnetized Dense Cores

Offner, Stella S. R.; Chaban, Jonah

doi:10.3847/1538-4357/aa8996

Cited by 110 publications

(139 citation statements)

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“…The smaller amount of feedback mass is also consistent with the total stellar mass in Taurus, which is estimated to be on the order of 200 M in Kraus et al (2017). The feedback mass predicted by model ME1 and that calculated from Li et al (2015) are 10 times the stellar mass, which is inconsistent with the expect amount of gas entrained by feedback (Offner, & Chaban 2017).…”

Section: Feedback Identified In the Full Taurus Cloudmentioning

confidence: 63%

“…The mass directly launched by young stars in both theoretical work and observations is small, ∼ 10 −9 M /yr (e.g., Shu et al 1994;Hartigan et al 1995). Numerical simulations suggest the entrained gas can contribute three times more mass than the direct mass loss from young stars (Offner, & Chaban 2017). In observations, the mass associated with feedback is included in the estimate of the entrained gas.…”

Section: Assessing Model Accuracy Using Synthetic Observationsmentioning

confidence: 99%

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Application of Convolutional Neural Networks to Identify Stellar Feedback Bubbles in CO Emission

Offner

Gutermuth

et al. 2020

ApJ

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We adopt a deep learning method casi (Convolutional Approach to Shell Identification) and extend it to 3D (casi-3d) to identify signatures of stellar feedback in molecular line spectra, such as 13 CO. We adopt magneto-hydrodynamics simulations that study the impact of stellar winds in a turbulent molecular cloud as an input to generate synthetic observations. We apply the 3D radiation transfer code radmc-3d to model 13 CO (J=1-0) line emission from the simulated clouds. We train two casi-3d models: ME1 is trained to predict only the position of feedback, while MF is trained to predict the fraction of the mass coming from feedback in each voxel. We adopt 75% of the synthetic observations as the training set and assess the accuracy of the two models with the remaining data. We demonstrate that model ME1 identifies bubbles in simulated data with 95% accuracy, and model MF predicts the bubble mass within 4% of the true value. We test the two models on bubbles that were previously visually identified in Taurus in 13 CO. We show our models perform well on the highest confidence bubbles that have a clear ring morphology and contain one or more sources. We apply our two models on the full 98 deg 2 FCRAO 13 CO survey of the Taurus cloud. Models ME1 and MF predict feedback gas mass of 2894 M and 302 M , respectively. When including a correction factor for missing energy due to the limited velocity range of the 13 CO data cube, model ME1 predicts feedback kinetic energies of 4.0×10 46 ergs and 1.5×10 47 ergs with/without subtracting the cloud velocity gradient. Model MF predicts feedback kinetic energy of 9.6×10 45 ergs and 2.8×10 46 ergs with/without subtracting the cloud velocity gradient. Model ME1 predicts bubble locations and properties consistent with previous visually identified bubbles. However, model MF demonstrates that feedback properties computed based on visual identifications are significantly over-estimated due to line of sight confusion and contamination from background and foreground gas.

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Section: Feedback Identified In the Full Taurus Cloudmentioning

confidence: 63%

Section: Assessing Model Accuracy Using Synthetic Observationsmentioning

confidence: 99%

Application of Convolutional Neural Networks to Identify Stellar Feedback Bubbles in CO Emission

Offner

Gutermuth

et al. 2020

ApJ

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“…As mentioned in Section 3.1, increased resolution would allow for smaller-scale fragmentation and the formation of protostars with even smaller masses. Additionally, protostellar outflows will also reduce star formation efficiency by entraining and expelling dense gas, thereby lowering the median mass of the protostars from ∼ M to the observed value of ∼ 0.2M (Offner & Arce 2014;Offner & Chaban 2017).…”

Section: Multiplicity Statisticsmentioning

confidence: 99%

The Formation and Evolution of Wide-orbit Stellar Multiples In Magnetized Clouds

Lee

Offner

Kratter

et al. 2019

ApJ

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Stars rarely form in isolation. Nearly half of the stars in the Milky Way have a companion, and this fraction increases in starforming regions. However, why some dense cores and filaments form bound pairs while others form single stars remains unclear. We present a set of three-dimensional, gravo-magnetohydrodynamic simulations of turbulent star-forming clouds, aimed at understanding the formation and evolution of multiple-star systems formed through large scale ( 10 3 AU) turbulent fragmentation. We investigate three global magnetic field strengths, with global mass-to-flux ratios of µ φ = 2, 8, and 32. The initial separations of protostars in multiples depends on the global magnetic field strength, with stronger magnetic fields (e.g., µ φ = 2) suppressing fragmentation on smaller scales. The overall multiplicity fraction (MF) is between 0.4 − 0.6 for our strong and intermediate magnetic field strengths, which is in agreement with observations. The weak field case has a lower fraction. The MF is relatively constant throughout the simulations, even though stellar densities increase as collapse continues. While the MF rarely exceeds 60% in all three simulations, over 80% of all protostars are part of a binary system at some point. We additionally find that the distribution of binary spin mis-alignment angles is consistent with a randomized distribution. In all three simulations, several binaries originate with wide separations and dynamically evolve to 10 2 AU separations. We show that a simple model of mass accretion and dynamical friction with the gas can explain this orbital evolution.

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“…13 CO, to ensure the motion of the densest gas is not overlooked [Arce and Sargent, 2006]. Numerical simulations, for example by Offner and Chaban [2017], of the collapse and evolution of isolated dense cores now include the effects of turbulence, radiative transfer, and outflow feedback. These show that outflows can drive and maintain turbulence in the core environment even when magnetic fields are initially strong.…”

Section: Feedback: Outflow Interaction With Molecular Cores and Beyondmentioning

confidence: 99%

“…To overcome this, a number of simulations resort to building subgrid models that effectively prescribe the physics of an MHD outflow whose source region remains unresolved [Federrath et al, 2014]. As already noted, Offner and Chaban [2017] find that the inclusion of real MHD effects in cores reduces the star formation efficiency -lower mass to flux ratios lead to a decrease in the star formation efficiency; drops from 0.4 to 0.15 as λ is decreased from hydro λ ∼ ∞ to λ = 1.5. These simulations also find that ratio of launched outflow to the total (combined launched and entrained) outflow mass is 1:4.…”

Section: Outflow Feedback: Determining Stellar Masses and Star Formatmentioning

confidence: 99%

The Role of Magnetic Fields in Protostellar Outflows and Star Formation

Pudritz

Ray

2019

Front. Astron. Space Sci.

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The role of outflows in the formation of stars and the protostellar disks that generate them is a central question in astrophysics. Outflows are associated with star formation across the entire stellar mass spectrum. In this review, we describe the observational, theoretical, and computational advances on magnetized outflows, and their role in the formation of disks and stars of all masses in turbulent, magnetized clouds. The ability of torques exerted on disks by magnetized winds to efficiently extract and transport disk angular momentum was developed in early theoretical models and confirmed by a variety of numerical simulations. The recent high resolution Atacama Large Millimeter Array (ALMA) observations of disks and outflows now confirm several key aspects of these ideas, e.g. that jets rotate and originate from large regions of their underlying disks. New insights on accretion disk physics show that magneto-rotational instability (MRI) turbulence is strongly damped, leaving magnetized disk winds as the dominant mechanism for transporting disk angular momentum. This has major consequences for star formation, as well as planet formation. Outflows also play an important role in feedback processes particularly in the birth of low mass stars and cluster formation. Despite being almost certainly fundamental to their production and focusing, magnetic fields in outflows in protostellar systems, and even in the disks, are notoriously difficult to measure. Most methods are indirect and lack precision, as for example, when using optical/near-infrared line ratios. Moreover, in those rare cases where direct measurements are possible -where synchrotron radiation is observed, one has to be very careful in interpreting derived values. Here we also explore what is known about magnetic fields from observations, and take a forward look to the time when facilities such as SPIRou and the SKA are in routine operation.

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Impact of Protostellar Outflows on Turbulence and Star Formation Efficiency in Magnetized Dense Cores

Cited by 110 publications

References 111 publications

Application of Convolutional Neural Networks to Identify Stellar Feedback Bubbles in CO Emission

Application of Convolutional Neural Networks to Identify Stellar Feedback Bubbles in CO Emission

The Formation and Evolution of Wide-orbit Stellar Multiples In Magnetized Clouds

The Role of Magnetic Fields in Protostellar Outflows and Star Formation

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