2020
DOI: 10.1051/0004-6361/201937104
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Dense gas formation in the Musca filament due to the dissipation of a supersonic converging flow

Abstract: Observations with the Herschel Space Telescope have established that most star forming gas is organised in filaments, a finding that is supported by numerical simulations of the supersonic interstellar medium (ISM) where dense filamentary structures are ubiquitous. We aim to understand the formation of these dense structures by performing observations covering the 12CO(4→3), 12CO(3→2), and various CO(2–1) isotopologue lines of the Musca filament, using the APEX telescope. The observed CO intensities and line r… Show more

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Cited by 28 publications
(28 citation statements)
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References 96 publications
(128 reference statements)
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“…Panopoulou et al 2017;Seifried et al 2017;Ossenkopf-Okada & Stepanov 2019), filament width of 0.1 pc in nearby molecular clouds is close to the sonic scale which could fit in a scenario where filaments are made of dense, post-shock gas of converging flows (Arzoumanian et al 2011;Schneider et al 2011;Federrath 2016). In the companion paper (Bonne et al 2020), observational indications were found of warm gas from low-velocity shocks associated with mass accretion on the Musca filament. It has also led to some theoretical models considering gravitational inflow that might provide an explanation for this universal width (Heitsch 2013;Hennebelle & André 2013).…”
Section: Introductionmentioning
confidence: 94%
“…Panopoulou et al 2017;Seifried et al 2017;Ossenkopf-Okada & Stepanov 2019), filament width of 0.1 pc in nearby molecular clouds is close to the sonic scale which could fit in a scenario where filaments are made of dense, post-shock gas of converging flows (Arzoumanian et al 2011;Schneider et al 2011;Federrath 2016). In the companion paper (Bonne et al 2020), observational indications were found of warm gas from low-velocity shocks associated with mass accretion on the Musca filament. It has also led to some theoretical models considering gravitational inflow that might provide an explanation for this universal width (Heitsch 2013;Hennebelle & André 2013).…”
Section: Introductionmentioning
confidence: 94%
“…In order to stabilise the filamentary structure we instead assume a radial inflow in our idealised simulations. Such radial accretion flows have been observed in many filaments (Schneider et al 2010;Kirk et al 2013;Palmeirim et al 2013;Shimajiri et al 2019;Bonne et al 2020) and typically show estimated accretion rates of around 10 − 100 M pc −1 Myr −1 and accretion velocities of the order of 0.25 − 1.0 km s −1 . If we assume a shock inflow region feeding the filament of around 0.5 pc, this would lead to a sustained inflow of material on timescales of 0.5-2 Myr.…”
Section: Introductionmentioning
confidence: 83%
“…Furthermore, Herschel observations reveal a network of striations orthogonal to the filament, which are thought to be indications of mass inflow along the magnetic field (Cox et al 2016). An indication of continuous mass accretion from inflow toward the Musca filament was found by observed presence of low-velocity filament accretion shocks around the Musca filament (Bonne et al 2020b). Hacar et al (2016) conclude from individual 13 CO and C 18 O pointings that the crest of the Musca filament is a single velocity-coherent structure.…”
Section: The Musca Cloud: Herschel Flux Density Mapmentioning
confidence: 95%
“…Musca is a prominent filamentary structure, 6 pc in length, with a high aspect ratio at a distance of only 140-150 pc (Hacar et al 2016;Cox et al 2016;Kainulainen et al 2016;Gaia Collaboration 2018). It has a low average column density N, with N(max) ∼ 4-8 10 21 cm −2 (Bonne et al 2020b), and shows only one protostellar source located at the northern end of the filament (Juvela et al 2012;Machaieie et al 2017). Furthermore, Herschel observations reveal a network of striations orthogonal to the filament, which are thought to be indications of mass inflow along the magnetic field (Cox et al 2016).…”
Section: The Musca Cloud: Herschel Flux Density Mapmentioning
confidence: 99%