Cloudy with a chance of starlight : coupling of smoothed particle hydrodynamics and Monte Carlo radiative transfer for the study of ionising stellar feedback
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Ionising radiation is present in a variety of astrophysical problems, and it is particularly important for shaping the process of star formation in molecular clouds, containing hot, high-mass stars. In order to account for the effects of ionising radiation within numerical models of star formation, we need to combine a hydrodynamics method with a radiative transfer method and obtain a radiation hydrodynamics scheme (RHD). In this thesis I achieve live radiation hydrodynamics by coupling the Smoothed Particle Hydrodynamics (SPH) code Phantom with the Monte Carlo Radiative Transfer (MCRT) code CMacIonize. Since SPH is particle-based and MCRT is grid-based, I construct an unstructured, Voronoi grid in order to establish a link between the two codes. In areas with large density gradients, a Voronoi grid based purely on the SPH particle positions achieves insufficient resolution, and therefore I propose a novel algorithm for inserting a small number of additional grid cells to improve the local resolution. Furthermore, the MCRT calculations require the knowledge of an average density for each Voronoi cell. To address this, I develop an analytic density mapping from SPH to a Voronoi grid, by deriving an expression for the integrals of a series of kernel functions over the volume of a random polyhedron. Finally, I demonstrate the validity of the live RHD through the benchmark test of D-type expansion of an H II region, where good agreement is shown with the existing literature. The RHD implementation is then used to perform a proof-of-concept simulation of a collapsing cloud, which produces high-mass stars and is subsequently partially ionised by them. The presented code is a valuable tool for future star formation studies, and it can be used for modelling a broad range of additional astronomical problems involving ionising radiation and hydrodynamics.
Thesis, PhD Doctor of Philosophy
Attribution-NonCommercial-NoDerivatives 4.0 Internationalhttp://creativecommons.org/licenses/by-nc-nd/4.0/
Description of related resourcesPetkova, M.A., Laibe, G., Bonnell, I.A.. Fast and accurate Voronoi density gridding from Lagrangian hydrodynamics data. J Comp Phys 2018;353:300–315. doi:10.1016/ j.jcp.2017.10.024. arXiv:astro-ph/1710.07108
Cloudy with a chance of starlight : coupling of smoothed particle hydrodynamics and Monte Carlo radiative transfer for the study of ionising stellar feedback (thesis data) Petkova, M.A., University of St Andrews, 25 November 2018, DOI: https://doi.org/10.17630/a3f5b723-1c49-4464-9d4d-ffbf85bf65b5
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