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Register a new userChemical Evolution of Turbulent Multiphase Molecular Clouds
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Molecular clouds are essentially made up of atomic and molecular hydrogen, which in spite of being the simplest molecule in the ISM plays a key role in the chemical evolution of molecular clouds. Since its formation time is very long, the H2 molecules can be transported by the turbulent motions within the cloud toward low density and warm regions, where its enhanced abundance can boost the abundances of molecules with high endothermicities. We present high resolution simulations where we include the evolution of the molecular gas under the effect of the dynamics, and we analyze its impact on the abundance of CH+.
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We investigated the chemical evolution of HC3N in six dense molecular clouds, using archival available data from the Herschel infrared Galactic Plane Survey (Hi-GAL) and the Millimeter Astronomy Legacy Team Survey at 90 GHz (MALT90). Radio sky surveys of the Multi-Array Galactic Plane Imaging Survey (MAGPIS) and the Sydney University Molonglo Sky Survey (SUMSS) indicate these dense molecular clouds are associated with ultracompact HII (UCHII) regions and/or classical HII regions. We find that in dense molecular clouds associated with normal classical HII regions, the abundance of HC3N begins to decrease or reaches a plateau when the dust temperature gets hot. This implies UV photons could destroy the molecule of HC3N. On the other hand, in the other dense molecular clouds associated with UCHII regions, we find the abundance of HC3N increases with dust temperature monotonously, implying HC3N prefers to be formed in warm gas. We also find that the spectra of HC3N (10-9) in G12.804-0.199 and RCW 97 show wing emissions, and the abundance of HC3N in these two regions increases with its nonthermal velocity width, indicating HC3N might be a shock origin species. We further investigated the evolutionary trend of N(N2H+)/N(HC3N) column density ratio, and found this ratio could be used as a chemical evolutionary indicator of cloud evolution after the massive star formation is started.
We have conducted OH 18 cm survey toward 141 molecular clouds in various environments, including 33 optical dark clouds, 98 Planck Galactic cold clumps (PGCCs) and 10 Spitzer dark clouds with the Arecibo telescope. The deviations from local thermal equilibrium are common for intensity ratios of both OH main lines and satellite lines. Line intensity of OH 1667 MHz is found to correlate linearly with visual extinction $Arm_V$ when $Arm_V$ is less than 3 mag. It was converted into OH column density by adopting excitation temperature derived from Monte Carlo simulations with one sigma uncertainty. The relationship between OH abundance $X$(OH) relative to H$_2$ and $Arm_V$ is found to follow an empirical formula, begin{equation} onumber frac{X(textrm{OH})}{10^{-7}} = 1.3^{+0.4}_{-0.4} + 6.3^{+0.5}_{-0.5}times textrm{exp}(-frac{A_textrm{V}}{2.9^{+0.6}_{-0.6}}). end{equation} Linear correlation is found between OH and $^{13}$CO intensity. Besides, nonthermal velocity dispersions of OH and $^{13}$CO are closely correlated. These results imply tight chemical evolution and spatial occupation between OH and $^{13}$CO. No obvious correlation is found between column density and nonthermal velocity dispersion of OH and HI Narrow Self-Absorption (HINSA), indicating different chemical evolution and spatial volume occupation between OH and HINSA. Using the age information of HINSA analysis, OH abundance $X$(OH) is found to increase linearly with cloud age, which is consistent with previous simulations. Fourteen OH components without corresponding CO emission were detected, implying the effectiveness of OH in tracing the `CO-dark molecular gas.
We use 3D-PDR, a three-dimensional astrochemistry code for modeling photodissociation regions (PDRs), to post-process hydrodynamic simulations of turbulent, star-forming clouds. We focus on the transition from atomic to molecular gas, with specific attention to the formation and distribution of H, C+, C, H2 and CO. First, we demonstrate that the details of the cloud chemistry and our conclusions are insensitive to the simulation spatial resolution, to the resolution at the cloud edge, and to the ray angular resolution. We then investigate the effect of geometry and simulation parameters on chemical abundances and find weak dependence on cloud morphology as dictated by gravity and turbulent Mach number. For a uniform external radiation field, we find similar distributions to those derived using a one-dimensional PDR code. However, we demonstrate that a three-dimensional treatment is necessary for a spatially varying external field, and we caution against using one-dimensional treatments for non-symmetric problems. We compare our results with the work of Glover et al. (2010), who self-consistently followed the time evolution of molecule formation in hydrodynamic simulations using a reduced chemical network. In general, we find good agreement with this in situ approach for C and CO abundances. However, the temperature and H2 abundances are discrepant in the boundary regions (Av < 5), which is due to the different number of rays used by the two approaches.
We present high resolution ($1024^3$) simulations of super-/hyper-sonic isothermal hydrodynamic turbulence inside an interstellar molecular cloud (resolving scales of typically 20 -- 100 AU), including a multi-disperse population of dust grains, i.e., a range of grain sizes is considered. Due to inertia, large grains (typical radius $a gtrsim 1.0,mu$m) will decouple from the gas flow, while small grains ($alesssim 0.1,mu$m) will tend to better trace the motions of the gas. We note that simulations with purely solenoidal forcing show somewhat more pronounced decoupling and less clustering compared to simulations with purely compressive forcing. Overall, small and large grains tend to cluster, while intermediate-size grains show essentially a random isotropic distribution. As a consequence of increased clustering, the grain-grain interaction rate is locally elevated; but since small and large grains are often not spatially correlated, it is unclear what effect this clustering would have on the coagulation rate. Due to spatial separation of dust and gas, a diffuse upper limit to the grain sizes obtained by condensational growth is also expected, since large (decoupled) grains are not necessarily located where the growth species in the molecular gas is.
Giant molecular clouds (GMCs) are well-studied in the local Universe, however, exactly how their properties vary during galaxy evolution is poorly understood due to challenging resolution requirements, both observational and computational. We present the first time-dependent analysis of giant molecular clouds in a Milky Way-like galaxy and an LMC-like dwarf galaxy of the FIRE-2 (Feedback In Realistic Environments) simulation suite, which have sufficient resolution to predict the bulk properties of GMCs in cosmological galaxy formation self-consistently. We show explicitly that the majority of star formation outside the galactic center occurs within self-gravitating gas structures that have properties consistent with observed bound GMCs. We find that the typical cloud bulk properties such as mass and surface density do not vary more than a factor of 2 in any systematic way after the first Gyr of cosmic evolution within a given galaxy from its progenitor. While the median properties are constant, the tails of the distributions can briefly undergo drastic changes, which can produce very massive and dense self-gravitating gas clouds. Once the galaxy forms, we identify only two systematic trends in bulk properties over cosmic time: a steady increase in metallicity produced by previous stellar populations and a weak decrease in bulk cloud temperatures. With the exception of metallicity we find no significant differences in cloud properties between the Milky Way-like and dwarf galaxies. These results have important implications for cosmological star and star cluster formation and put especially strong constraints on theories relating the stellar initial mass function to cloud properties.
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