Chemodynamical Simulations of Star-Forming Molecular Clouds

Doctoral thesis, 2023

Stars are known to form from dense, dusty clumps and cores of molecular clouds. However, there is no consensus on a theory that can predict the rate of star formation, its clustering, and the conditions needed for massive stars to be born. A major challenge is how to observe and characterise the gas that is the fuel for star formation. One way is to take advantage of line emission from molecular species, a great variety of which have now been detected in the interstellar medium. However, interpreting the messages from these molecules necessitates an understanding and modeling of astrochemistry. In addition to this diagnostic power, astrochemistry is also expected to impact the physical evolution of the gas by influencing heating and cooling rates and controlling the degree of ionization, which mediates coupling to magnetic fields. To make progress in modeling the physical and chemical evolution of molecular clouds, we develop methods for chemodynamical simulations and carry out several studies combining magnetohydrodynamics (MHD) and astrochemistry. Our first investigation concerns the evolution of chemical abundances in massive pre-stellar cores, which are the initial conditions in some theories of massive star formation. A gas-phase chemical reaction network is applied to MHD simulations, with a focus on predicting the level of deuteration of key diagnostic species that are widely used in observational searches for such cores. We show how the abundances and kinematics of N2D+ and N2H+ can help disentangle the chemodynamical history of massive cores. Next we examine the formation of populations of cores from colliding and non-colliding giant molecular clouds (GMCs). We begin by carrying out high resolution MHD simulations to examine how core properties, especially the core mass function (CMF), are influenced by the dynamics of the GMCs. Synthetic observations of the simulated clouds are derived to enable a more direct comparison with observed CMFs. We then use a gas-grain chemical network to follow the evolution of key gas- and ice-phase species in these GMCs. One application is a study of the influence of the cosmic ray ionization rate on the abundances of CO, HCO+ and N2H+ in the colliding and non-colliding clouds and how observations of these species can help measure this key environmental property. Associated with the release of our astrochemical modeling tool, Naunet, we also discuss the computational performance of chemodynamical simulations and summarize methods to further improve their efficiency.