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Giant molecular clouds: A view through molecular tracers and synthetic images

Penaloza Cabrera, Camilo 2018. Giant molecular clouds: A view through molecular tracers and synthetic images. PhD Thesis, Cardiff University.
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Line emission is strongly dependent on the local environmental conditions in which the emitting tracers reside. In this work, we focus on modelling the CO emission from simulated giant molecular clouds (GMCs), and study the variations in the resulting line ratios arising from the emission from the J = 1 − 0, J = 2 − 1 and J = 3 − 2 transitions. We first study the ratio (R2−1/1−0) between CO’s first two emission lines and examine what information it provides about the physical properties of the cloud. To study R2−1/1−0 we perform smooth particle hydrodynamic simulations with time dependent chemistry (using GADGET-2), along with post-process radiative transfer calculations on an adaptive grid (using RADMC-3D) to create synthetic emission maps of a MC. R2−1/1−0 has a bimodal distribution that is a consequence of the excitation properties of each line, given that J = 1 reaches local thermal equilibrium (LTE) while J = 2 is still sub-thermally excited in the considered clouds. The bimodality of R2−1/1−0 serves as a tracer of the physical properties of different regions of the cloud and it helps constrain local temperatures, densities and opacities. Then to study the dependence line emission has on environment we perform a set of smoothed particle hydrodynamics (SPH) simulations with time-dependent chemistry, in which environmental conditions – including total cloud mass, density, size, velocity dispersion, metallicity, interstellar radiation field (ISRF) and the cosmic ray ionisation rate (CRIR) – were systematically varied. The simulations were then post-processed using radiative transfer to produce synthetic emission maps in the 3 transitions quoted above. We find that the cloud-averaged values of the line ratios can vary by up to ±0.3 dex, triggered by changes in the environmental conditions. Changes in the ISRF and/or in the CRIR have the largest impact on line ratios since they directly affect the abundance, temperature and distribution of CO-rich gas within the clouds. We show that the standard methods used to convert CO emission to H2 column density can underestimate the total H2 molecular gas in GMCs by factors of 2 or 3, depending on the environmental conditions in the clouds. One of the underlying assumptions in star formation is that stars are formed in long lived, bound molecular clouds. This paradigm comes from examining the virial parameter of molecular clouds. To calculate the virial parameter we rely on three quantities: velocity dispersion, size and mass, each of which have their own underlying assumptions, uncertainties and biases. It should come as no surprise that variations in these quantities can have a significant impact on our assessment of cloud dynamics and hence our overall understanding of star formation. We therefore use CO line emission from synthetic observation to study how the dynamical state of clouds changes as a function of metallicity and to test how accurately the virial parameter traces these changes. First we show how the ”observed” velocity dispersion significantly decreases with lower metallicities and how this is reflected on the virial parameter. Second we highlight the importance of understanding the intrinsic assumptions that go into calculating the virial parameter, such as how the mass and radius are derived. Finally, we show how the virial parameter of a cloud changes with metallicity and how the ’observed’ virial parameter compares to the ’true’ value in the simulation. x

Item Type: Thesis (PhD)
Date Type: Submission
Status: Unpublished
Schools: Physics and Astronomy
Subjects: Q Science > QB Astronomy
Uncontrolled Keywords: simulated giant molecular clouds, modelling the CO2 emission, GADGET-2, interstellar radiation field, cosmic ray ionisation rate
Funders: Cardiff University
Date of First Compliant Deposit: 24 October 2018
Last Modified: 23 Jan 2020 04:31

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