Protostellar accretion traced with chemistry: Comparing synthetic C18O maps of embedded protostars to real observations

Abstract

Context: Understanding how protostars accrete their mass is a central question of star formation. One aspect of this is trying to understand whether the time evolution of accretion rates in deeply embedded objects is best characterised by a smooth decline from early to late stages or by intermittent bursts of high accretion. Aims: We create synthetic observations of deeply embedded protostars in a large numerical simulation of a molecular cloud, which are compared directly to real observations. The goal is to compare episodic accretion events in the simulation to observations and to test the methodology used for analysing the observations. Methods: Simple freeze-out and sublimation chemistry is added to the simulation, and synthetic C${}^{18}$O line cubes are created for a large number of simulated protostars. The spatial extent of C${}^{18}$O is measured for the simulated protostars and compared directly to a sample of 16 deeply embedded protostars observed with the Submillimeter Array. If CO is distributed over a larger area than predicted based on the protostellar luminosity, it may indicate that the luminosity has been higher in the past and that CO is still in the process of refreezing. Results: Approximately 1% of the protostars in the simulation show extended C${}^{18}$O emission, as opposed to approximately 50% in the observations, indicating that the magnitude and frequency of episodic accretion events in the simulation is too low relative to observations. The protostellar accretion rates in the simulation are primarily modulated by infall from the larger scales of the molecular cloud, and do not include any disk physics. The discrepancy between simulation and observations is taken as support for the necessity of disks, even in deeply embedded objects, to produce episodic accretion events of sufficient frequency and amplitude.

Accepted for publication in A&A, 11 pages, 8 figures; v2 contains minor updates to the language

References in corpus (7)

• The Hot Inner Disk of FU Ori
• Infall-Driven Protostellar Accretion and the Solution to the Luminosity Problem
• A Sub-arcsecond Survey Toward Class 0 Protostars in Perseus: Searching for Signatures of Protostellar Disks
• HOPS 383: An Outbursting Class 0 Protostar in Orion
• Molecule sublimation as a tracer of protostellar accretion: Evidence for accretion bursts from high angular resolution C18O images
• Chemical tracers of episodic accretion in low-mass protostars
• ALMA observations of the kinematics and chemistry of disc formation

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• A detailed framework to incorporate dust in hydrodynamical simulations
• Probing Episodic Accretion in Very Low Luminosity Objects
• The VLA/ALMA Nascent Disk and Multiplicity (VANDAM) Survey of Orion Protostars I. Identifying and Characterizing the Protostellar Content of the OMC2-FIR4 and OMC2-FIR3 Regions
• Impact of Cosmic-Ray Feedback on Accretion and Chemistry in Circumstellar Disks
• Physical and Chemical Structure of the Disk and Envelope of the Class 0/I Protostar L1527
• Physical conditions for dust grain alignment in Class 0 protostellar cores II. The role of the radiation field in models aligning/disrupting dust grains
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