Dataset Information

The Molecular Cloud Lifecycle.

ABSTRACT: Giant molecular clouds (GMCs) and their stellar offspring are the building blocks of galaxies. The physical characteristics of GMCs and their evolution are tightly connected to galaxy evolution. The macroscopic properties of the interstellar medium propagate into the properties of GMCs condensing out of it, with correlations between e.g. the galactic and GMC scale gas pressures, surface densities and volume densities. That way, the galactic environment sets the initial conditions for star formation within GMCs. After the onset of massive star formation, stellar feedback from e.g. photoionisation, stellar winds, and supernovae eventually contributes to dispersing the parent cloud, depositing energy, momentum and metals into the surrounding medium, thereby changing the properties of galaxies. This cycling of matter between gas and stars, governed by star formation and feedback, is therefore a major driver of galaxy evolution. Much of the recent debate has focused on the durations of the various evolutionary phases that constitute this cycle in galaxies, and what these can teach us about the physical mechanisms driving the cycle. We review results from observational, theoretical, and numerical work to build a dynamical picture of the evolutionary lifecycle of GMC evolution, star formation, and feedback in galaxies.

SUBMITTER: Chevance M

PROVIDER: S-EPMC7188702 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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The Molecular Cloud Lifecycle.

Chevance Mélanie M Kruijssen J M Diederik JMD Vazquez-Semadeni Enrique E Nakamura Fumitaka F Klessen Ralf R Ballesteros-Paredes Javier J Inutsuka Shu-Ichiro SI Adamo Angela A Hennebelle Patrick P

Space science reviews 20200428 4

Giant molecular clouds (GMCs) and their stellar offspring are the building blocks of galaxies. The physical characteristics of GMCs and their evolution are tightly connected to galaxy evolution. The macroscopic properties of the interstellar medium propagate into the properties of GMCs condensing out of it, with correlations between e.g. the galactic and GMC scale gas pressures, surface densities and volume densities. That way, the galactic environment sets the initial conditions for star format ...[more]

PMID: 32377024

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Project description: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 suffcient 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.

Project description:L1630 in the Orion B molecular cloud, which includes the iconic Horsehead Nebula, illuminated by the star system σ Ori, is an example of a photodissociation region (PDR). In PDRs, stellar radiation impinges on the surface of dense material, often a molecular cloud, thereby inducing a complex network of chemical reactions and physical processes. Observations toward L1630 allow us to study the interplay between stellar radiation and a molecular cloud under relatively benign conditions, that is, intermediate densities and an intermediate UV radiation field. Contrary to the well-studied Orion Molecular Cloud 1 (OMC1), which hosts much harsher conditions, L1630 has little star formation. Our goal is to relate the [Cii] fine-structure line emission to the physical conditions predominant in L1630 and compare it to studies of OMC1. The [Cii] 158 μm line emission of L1630 around the Horsehead Nebula, an area of 12' × 17', was observed using the upgraded German Receiver for Astronomy at Terahertz Frequencies (upGREAT) onboard the Stratospheric Observatory for Infrared Astronomy (SOFIA). Of the [Cii] emission from the mapped area 95%, 13 L⊙, originates from the molecular cloud; the adjacent Hii region contributes only 5%, that is, 1 L⊙. From comparison with other data (CO(1-0)-line emission, far-infrared (FIR) continuum studies, emission from polycyclic aromatic hydrocarbons (PAHs)), we infer a gas density of the molecular cloud of nH ∼ 3 · 103 cm-3, with surface layers, including the Horsehead Nebula, having a density of up to nH ∼ 4 · 104 cm-3. The temperature of the surface gas is T ∼ 100 K. The average [Cii] cooling efficiency within the molecular cloud is 1.3 · 10-2. The fraction of the mass of the molecular cloud within the studied area that is traced by [Cii] is only 8%. Our PDR models are able to reproduce the FIR-[Cii] correlations and also the CO(1-0)-[Cii] correlations. Finally, we compare our results on the heating efficiency of the gas with theoretical studies of photoelectric heating by PAHs, clusters of PAHs, and very small grains, and find the heating efficiency to be lower than theoretically predicted, a continuation of the trend set by other observations. In L1630 only a small fraction of the gas mass is traced by [Cii]. Most of the [Cii] emission in the mapped area stems from PDR surfaces. The layered edge-on structure of the molecular cloud and limitations in spatial resolution put constraints on our ability to relate different tracers to each other and to the physical conditions. From our study, we conclude that the relation between [Cii] emission and physical conditions is likely to be more complicated than often assumed. The theoretical heating efficiency is higher than the one we calculate from the observed [Cii] emission in the L1630 molecular cloud.

Dataset Information

The Molecular Cloud Lifecycle.

Publications

The Molecular Cloud Lifecycle.

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