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  5. HCN hyperfine ratio analysis of massive molecular clumps

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Article
en
2016

HCN hyperfine ratio analysis of massive molecular clumps

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en
2016
Vol 465 (3)
Vol. 465
DOI: 10.1093/mnras/stw2842

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Peter J Barnes
Peter J Barnes

Imperial College London

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William J. Schap
Peter J Barnes
Antonio J. Ordoñez
+3 more

Abstract

We report a new analysis protocol for HCN hyperfine data, based on the PySpecKit package, and results of using this new protocol to analyse a sample area of seven massive molecular clumps from the Census of High- and Medium-mass Protostars (CHaMP) survey, in order to derive maps of column density for this species. There is a strong correlation between the HCN integrated intensity, IHCN, and previously reported |$I_{\rm HCO^{+}}$| in the clumps, but |$I_{\rm N_{2}H^{+}}$| is not well correlated with either of these other two 'dense gas tracers'. The four fitted parameters from PySpecKit in this region fall in the range of VLSR = 8–10 km s−1, σV = 1.2–2.2 km s−1, Tex = 4–15 K, and τ = 0.2–2.5. These parameters allow us to derive a column density map of these clouds, without limiting assumptions about the excitation or opacity. A more traditional (linear) method of converting IHCN to total mass column gives much lower clump masses than our results based on the hyperfine analysis. This is primarily due to areas in the sample region of low I, low Tex, and high τ. We conclude that there may be more dense gas in these massive clumps not engaged in massive star formation than previously recognized. If this result holds for other clouds in the CHaMP sample, it would have dramatic consequences for the calibration of the Kennicutt–Schmidt star formation laws, including a large increase in the gas depletion time-scale in such regions.

How to cite this publication

William J. Schap, Peter J Barnes, Antonio J. Ordoñez, Adam Ginsburg, Yoshinori Yonekura, Y. Fukui (2016). HCN hyperfine ratio analysis of massive molecular clumps. , 465(3), DOI: https://doi.org/10.1093/mnras/stw2842.

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Publication Details

Type

Article

Year

2016

Authors

6

Datasets

0

Total Files

0

Language

en

DOI

https://doi.org/10.1093/mnras/stw2842

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