scholarly journals A CS survey of massive stars embedded in molecular clouds

1991 ◽  
Vol 147 ◽  
pp. 25-28
Author(s):  
L. Bronfman ◽  
J. May ◽  
L. A. Nyman ◽  
P. Thaddeus

the CS J=2 →1 molecular line at 98 GHz, a normally optically thin line requiring high densities to be excited, has been detected with SEST (Swedish ESO Submillimeter Telescope) toward 294 IRAS pointlike sources having the characteristic FIR colors of embedded stellar objects and apparently associated with the largest molecular cloud complexes in the southern Milky Way. We present here their Galactocentric radial distribution and a correlation between their FIR and CS luminosities.

1991 ◽  
Vol 147 ◽  
pp. 25-28
Author(s):  
L. Bronfman ◽  
J. May ◽  
L. A. Nyman ◽  
P. Thaddeus

the CS J=2 →1 molecular line at 98 GHz, a normally optically thin line requiring high densities to be excited, has been detected with SEST (Swedish ESO Submillimeter Telescope) toward 294 IRAS pointlike sources having the characteristic FIR colors of embedded stellar objects and apparently associated with the largest molecular cloud complexes in the southern Milky Way. We present here their Galactocentric radial distribution and a correlation between their FIR and CS luminosities.


2020 ◽  
Vol 498 (2) ◽  
pp. 2440-2455
Author(s):  
Yuxuan (宇轩) Yuan (原) ◽  
Mark R Krumholz ◽  
Blakesley Burkhart

ABSTRACT Molecular line observations using a variety of tracers are often used to investigate the kinematic structure of molecular clouds. However, measurements of cloud velocity dispersions with different lines, even in the same region, often yield inconsistent results. The reasons for this disagreement are not entirely clear, since molecular line observations are subject to a number of biases. In this paper, we untangle and investigate various factors that drive linewidth measurement biases by constructing synthetic position–position–velocity cubes for a variety of tracers from a suite of self-gravitating magnetohydrodynamic simulations of molecular clouds. We compare linewidths derived from synthetic observations of these data cubes to the true values in the simulations. We find that differences in linewidth as measured by different tracers are driven by a combination of density-dependent excitation, whereby tracers that are sensitive to higher densities sample smaller regions with smaller velocity dispersions, opacity broadening, especially for highly optically thick tracers such as CO, and finite resolution and sensitivity, which suppress the wings of emission lines. We find that, at fixed signal-to-noise ratio, three commonly used tracers, the J = 4 → 3 line of CO, the J = 1 → 0 line of C18O, and the (1,1) inversion transition of NH3, generally offer the best compromise between these competing biases, and produce estimates of the velocity dispersion that reflect the true kinematics of a molecular cloud to an accuracy of $\approx 10{{\ \rm per\ cent}}$ regardless of the cloud magnetic field strengths, evolutionary state, or orientations of the line of sight relative to the magnetic field. Tracers excited primarily in gas denser than that traced by NH3 tend to underestimate the true velocity dispersion by $\approx 20{{\ \rm per\ cent}}$ on average, while low-density tracers that are highly optically thick tend to have biases of comparable size in the opposite direction.


2012 ◽  
Vol 8 (S292) ◽  
pp. 83-86
Author(s):  
J. R. Dawson ◽  
N. M. McClure-Griffiths ◽  
Y. Fukui ◽  
J. Dickey ◽  
T. Wong ◽  
...  

AbstractThe role of large-scale stellar feedback in the formation of molecular clouds has been investigated observationally by examining the relationship between Hi and 12CO(J = 1−0) in supershells. Detailed parsec-resolution case studies of two Milky Way supershells demonstrate an enhanced level of molecularisation over both objects, and hence provide the first quantitative observational evidence of increased molecular cloud production in volumes of space affected by supershell activity. Recent results on supergiant shells in the LMC suggest that while they do indeed help to organise the ISM into over-dense structures, their global contribution to molecular cloud formation is of the order of only ∼ 10%.


1996 ◽  
Vol 13 (2) ◽  
pp. 197-201
Author(s):  
Michael Burton

AbstractA condensed summary of molecular cloud astrophysics is presented. Some examples of the power of combining near-IR and mm molecular line observations are given.


2021 ◽  
Vol 921 (2) ◽  
pp. 168
Author(s):  
Susanne Pfalzner ◽  
Dylan Paterson ◽  
Michele T. Bannister ◽  
Simon Portegies Zwart

Abstract Interstellar objects (ISOs), the parent population of 1i/‘Oumuamua and 2i/Borisov, are abundant in the interstellar medium of the Milky Way. This means that the interstellar medium, including molecular-cloud regions, has three components: gas, dust, and ISOs. From observational constraints of the field density of ISOs drifting in the solar neighborhood, we infer that a typical molecular cloud of 10 pc diameter contains some 1018 ISOs. At typical sizes ranging from hundreds of meters to tens of kilometers, ISOs are entirely decoupled from the gas dynamics in these molecular clouds. Here we address the question of whether ISOs can follow the collapse of molecular clouds. We perform low-resolution simulations of the collapse of molecular clouds containing initially static ISO populations toward the point where stars form. In this proof-of-principle study, we find that the interstellar objects definitely follow the collapse of the gas—and many become bound to the new-forming numerical approximations to future stars (sinks). At minimum, 40% of all sinks have one or more ISO test particles gravitationally bound to them for the initial ISO distributions tested here. This value corresponds to at least 1010 actual ISOs being bound after three initial freefall times. Thus, ISOs are a relevant component of star formation. We find that more massive sinks bind disproportionately large fractions of the initial ISO population, implying competitive capture of ISOs. Sinks can also be solitary, as their ISOs can become unbound again—particularly if sinks are ejected from the system. Emerging planetary systems will thus develop in remarkably varied environments, ranging from solitary to richly populated with bound ISOs.


2013 ◽  
Vol 23 ◽  
pp. 198-201
Author(s):  
XIAO-HONG CUI ◽  
ZHUO LI ◽  
LI-PING XIN

Observations imply that long γ-ray bursts (GRBs) are originated from explosions of massive stars, therefore they may occur in the molecular clouds where their progenitors were born. We show here that the prompt optical-UV emission from GRBs may be delayed due to the dust extinction, which can well explain the observed optical delayed onset and fast rise in GRB 080319B. The density and the size of the molecular cloud around GRB 080319B are roughly constrained to be ~ 103cm-3 and ~ 8pc, respectively. We also investigate the other GRBs with prompt optical-UV data, and find similar values of the densities and sizes of the local molecular clouds. The future observations of prompt optical-UV emission from GRBs in subsecond timescale, e.g., by UFFO-Pathfinder and SVOM-GWAC, will provide more evidence and probes of the local GRB environments.


2021 ◽  
Vol 923 (1) ◽  
pp. 106
Author(s):  
Hai-Ming Zhang ◽  
Ruo-Yu Liu ◽  
Yang Su ◽  
Hui Zhu ◽  
Shao-Qiang Xi ◽  
...  

Abstract We present an analysis of Fermi Large Area Telescope data of the gamma-ray emission in the vicinity of a radio supernova remnant (SNR), G045.7-00.4. To study the origin of the gamma-ray emission, we also make use of the CO survey data of Milky Way Imaging Scroll Painting to study the massive molecular gas complex that surrounds the SNR. The whole size of the gigaelectronvolt emission is significantly larger than that of the radio morphology. Above 3 GeV, the gigaelectronvolt emission is resolved into two sources: one is spatially consistent with the position of the SNR with a size comparable to that of the radio emission, and the other is located outside of the western boundary of the SNR and spatially coincident with the densest region of the surrounding molecular cloud. We suggest that the gigaelectronvolt emission of the western source may arise from cosmic rays (CRs) that have escaped the SNR and illuminated the surrounding molecular cloud. We find that the gamma-ray spectra of the western source can be consistently explained by this scenario with a total energy of ∼1050 erg in escaping CRs assuming the escape is isotropic.


2021 ◽  
Vol 922 (1) ◽  
pp. 8
Author(s):  
Qing-Zeng Yan ◽  
Ji Yang ◽  
Yang Su ◽  
Yan Sun ◽  
Ye Xu ◽  
...  

Abstract The principle of the background-eliminated extinction-parallax (BEEP) method is examining the extinction difference between on- and off-cloud regions to reveal the extinction jump caused by molecular clouds, thereby revealing the distance in complex dust environments. The BEEP method requires high-quality images of molecular clouds and high-precision stellar parallaxes and extinction data, which can be provided by the Milky Way Imaging Scroll Painting (MWISP) CO survey and the Gaia DR2 catalog, as well as supplementary A V extinction data. In this work, the BEEP method is further improved (BEEP-II) to measure molecular cloud distances in a global search manner. Applying the BEEP-II method to three regions mapped by the MWISP CO survey, we collectively measured 238 distances for 234 molecular clouds. Compared with previous BEEP results, the BEEP-II method measures distances efficiently, particularly for those molecular clouds with large angular size or in complicated environments, making it suitable for distance measurements of molecular clouds in large samples.


1988 ◽  
Vol 324 ◽  
pp. 248 ◽  
Author(s):  
L. Bronfman ◽  
R. S. Cohen ◽  
H. Alvarez ◽  
J. May ◽  
P. Thaddeus

2018 ◽  
Vol 610 ◽  
pp. A12 ◽  
Author(s):  
Emeric Bron ◽  
Chloé Daudon ◽  
Jérôme Pety ◽  
François Levrier ◽  
Maryvonne Gerin ◽  
...  

Context. Previous attempts at segmenting molecular line maps of molecular clouds have focused on using position-position-velocity data cubes of a single molecular line to separate the spatial components of the cloud. In contrast, wide field spectral imaging over a large spectral bandwidth in the (sub)mm domain now allows one to combine multiple molecular tracers to understand the different physical and chemical phases that constitute giant molecular clouds (GMCs). Aims. We aim at using multiple tracers (sensitive to different physical processes and conditions) to segment a molecular cloud into physically/chemically similar regions (rather than spatially connected components), thus disentangling the different physical/chemical phases present in the cloud. Methods. We use a machine learning clustering method, namely the Meanshift algorithm, to cluster pixels with similar molecular emission, ignoring spatial information. Clusters are defined around each maximum of the multidimensional probability density function (PDF) of the line integrated intensities. Simple radiative transfer models were used to interpret the astrophysical information uncovered by the clustering analysis. Results. A clustering analysis based only on the J = 1–0 lines of three isotopologues of CO proves sufficient to reveal distinct density/column density regimes (nH ~ 100 cm-3, ~500 cm-3, and >1000 cm-3), closely related to the usual definitions of diffuse, translucent and high-column-density regions. Adding two UV-sensitive tracers, the J = 1–0 line of HCO+ and the N = 1–0 line of CN, allows us to distinguish two clearly distinct chemical regimes, characteristic of UV-illuminated and UV-shielded gas. The UV-illuminated regime shows overbright HCO+ and CN emission, which we relate to a photochemical enrichment effect. We also find a tail of high CN/HCO+ intensity ratio in UV-illuminated regions. Finer distinctions in density classes (nH ~ 7 × 103 cm-3, ~4 × 104 cm-3) for the densest regions are also identified, likely related to the higher critical density of the CN and HCO+ (1–0) lines. These distinctions are only possible because the high-density regions are spatially resolved. Conclusions. Molecules are versatile tracers of GMCs because their line intensities bear the signature of the physics and chemistry at play in the gas. The association of simultaneous multi-line, wide-field mapping and powerful machine learning methods such as the Meanshift clustering algorithm reveals how to decode the complex information available in these molecular tracers.


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