The Green Bank Ammonia Survey: Dense Cores under Pressure in Orion A

Kirk, Helen; Friesen, Rachel; Pineda, Jaime E.; Rosolowsky, Erik; Offner, Stella S. R.; Matzner, Christopher D.; Myers, Philip C.; Francesco, James Di; Caselli, P.; Alves, F. O.; Chacón-Tanarro, A.; Chen, Hope How-Huan; Chen, Michael Chun-Yuan; Keown, Jared; Punanova, A.; Seo, Young Min; Shirley, Yancy L.; Ginsburg, Adam; Hall, Christine; Singh, Ayushi; Arce, Héctor G.; Goodman, Alyssa A.; Martín, P. G.; Redaelli, E.

doi:10.3847/1538-4357/aa8631

Cited by 89 publications

(135 citation statements)

References 103 publications

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“…Since these cores are embedded in dense clumps, the external pressure with the cloud provides additional force against the internal support, which could decreases the virial parameters. Therefore, these effects may play an important role in the balance between the external pressure, gravitational potential energy and internal kinetic energy (Pattle et al 2015;Zhang et al 2015;Kirk et al 2017).…”

Section: Dense Cores Dynamical Statementioning

confidence: 99%

Formation of Massive Protostellar Clusters—Observations of Massive 70 μm Dark Molecular Clouds

Zhang

Pillai

et al. 2019

ApJ

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We present Submillimeter Array (SMA) observations of seven massive molecular clumps which are dark in the far-infrared for wavelengths up to 70 µm. Our 1.3 mm continuum images reveal 44 dense cores, with gas masses ranging from 1.4 to 77.1 M ⊙ . Twenty-nine dense cores have masses greater than 8 M ⊙ and the other fifteen dense cores have masses between 1.4 and 7.5 M ⊙ . Assuming the core density follows a power-law in radius ρ ∝ r −b , the index b is found to be between 0.6 and 2.1 with a mean value of 1.3. The virial analysis reveals that the dense cores are not in virial equilibrium. CO outflow emission was detected toward 6 out of 7 molecular clumps and associated with 17 dense cores. For five of these cores, CO emissions appear to have line-wings at velocities of greater than 30 km s −1 with respect to the source systemic velocity, which indicates that most of the clumps harbor protostars and thus are not quiescent in star formation. The estimated outflow timescale increase with core mass, which likely indicates that massive cores have longer accretion timescale than that of the less massive ones. The fragmentation analysis shows that the mass of low-mass and massive cores are roughly consistent with thermal and turbulent Jeans masses, respectively.

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Section: Dense Cores Dynamical Statementioning

confidence: 99%

Formation of Massive Protostellar Clusters—Observations of Massive 70 μm Dark Molecular Clouds

Zhang

Pillai

et al. 2019

ApJ

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“…CLOVER's two-component spectral classifications and kinematics predictions can be used to improve existing analyses that neglect the presence of multiple velocity components. For instance, many virial stability analyses of star-forming structures rely on velocity dispersions measured from models that assume a single velocity component along the line of sight (e.g., Keown et al 2017;Kirk et al 2017;Chen et al 2019a;Kerr et al 2019). When multiple velocity components are present along the line of sight, however, models assuming a single velocity component typically fit the observed spectrum with a much wider velocity dispersion than would be obtained by using a model with multiple velocity components.…”

Section: Improving Virial Analyses With Clovermentioning

confidence: 99%

CLOVER: Convnet Line-fitting Of Velocities in Emission-line Regions

Keown

Francesco

Teimoorinia

et al. 2019

ApJ

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When multiple star-forming gas structures overlap along the line-of-sight and emit optically thin emission at significantly different radial velocities, the emission can become non-Gaussian and often exhibits two distinct peaks. Traditional line-fitting techniques can fail to account adequately for these double-peaked profiles, providing inaccurate cloud kinematics measurements. We present a new method called Convnet Linefitting Of Velocities in Emission-line Regions (CLOVER) for distinguishing between one-component, two-component, and noise-only emission lines using 1D convolutional neural networks trained with synthetic spectral cubes. CLOVER utilizes spatial information in spectral cubes by predicting on 3 × 3 pixel sub-cubes, using both the central pixel's spectrum and the average spectrum over the 3×3 grid as input. On an unseen set of 10,000 synthetic spectral cubes in each predicted class, CLOVER has classification accuracies of ∼ 99% for the one-component class and ∼ 97% for the two-component class. For the noise-only class, which is analogous to a signal-to-noise cutoff of four for traditional line-fitting methods, CLOVER has classification accuracy of 100%. CLOVER also has exceptional performance on real observations, correctly distinguishing between the three classes across a variety of star-forming regions. In addition, CLOVER quickly and accurately extracts kinematics directly from spectra identified as two-component class members. Moreover, we show that CLOVER is easily scalable to emission lines with hyperfine splitting, making it an attractive tool in the new era of large-scale NH 3 and N 2 H + mapping surveys.

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“…(ii) When multi-threshold methods are used, but still the reported mass-size relation is that of the cores without inner substructure, there is not necessarily a single slope, as it may be the case of the algorithms getsources, gaussclumps, or the leaves in dendrograms (e.g., Könyves et al 2015;Kirk et al 2017;Veltchev et al 2018;Sanhueza et al 2019).…”

Section: Mass-size Relation For Dense Cores Withing Single Cloudsmentioning

confidence: 99%

What is the physics behind the Larson mass–size relation?

Ballesteros-Paredes¹,

Román-Zúñiga²,

Salomé³

et al. 2019

Monthly Notices of the Royal Astronomical Society

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Different studies have reported a power-law mass-size relation M ∝ R q for ensembles of molecular clouds. In the case of nearby clouds, the index of the power-law q is close to 2. However, for clouds spread all over the Galaxy, indexes larger than 2 are reported. We show that indexes larger than 2 could be the result of line-of-sight superposition of emission that does not belong to the cloud itself. We found that a random factor of gas contamination, between 0.001% and 10% of the line-of-sight, allows to reproduce the mass-size relation with q ∼ 2.2 − 2.3 observed in Galactic CO surveys. Furthermore, for dense cores within a single cloud, or molecular clouds within a single galaxy, we argue that, even in these cases, there is observational and theoretical evidence that some degree of superposition may be occurring. However, additional effects may be present in each case, and are briefly discussed. We also argue that defining the fractal dimension of clouds via the mass-size relation is not adequate, since the mass is not necessarily a proxy to the area, and the size reported in M − R relations is typically obtained from the square root of the area, rather than from an estimation of the size independent from the area. Finally, we argue that the statistical analysis of finding clouds satisfying the Larson's relations does not mean that each individual cloud is in virial equilibrium.

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The Green Bank Ammonia Survey: Dense Cores under Pressure in Orion A

Cited by 89 publications

References 103 publications

Formation of Massive Protostellar Clusters—Observations of Massive 70 μm Dark Molecular Clouds

Formation of Massive Protostellar Clusters—Observations of Massive 70 μm Dark Molecular Clouds

CLOVER: Convnet Line-fitting Of Velocities in Emission-line Regions

What is the physics behind the Larson mass–size relation?

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