Modelling the Spectra of Brown Dwarfs

Brown dwarfs (BDs) are substellar mass objects with masses â¤80MJup, the hydrogenburning limit. Deuterium fusion occurs in objects with â¥13MJup, lasting only a very short period (4-50 Myrs). This means that brown dwarfs are constantly cooling over their lifetime, passing through temperature ranges equivalent to those of exoplanets and planets in the Solar System. This aging and cooling creates a spectral sequence (hottest to coolest: M, L, T, Y) as various molecules and condensates begin to form. The atmospheres created during this sequence are extremely similar to gas giant planets. As brown dwarfs are free-floating objects, it is possible to attain much higher resolution spectra than with exoplanets because we do not have to subtract out the light from the host star, and thus they provide the perfect testbed for atmospheric modelling of objects beyond our Solar System. The aim of this thesis is to characterise the coolest brown dwarf atmospheres, spectrally classified as Y dwarfs, and the associated change in their atmospheric structure and composition with decreasing temperature. In order to achieve this ultimate goal, a number of steps are taken. The first is the updating of the molecular and atomic data to include the latest line lists and pressure broadening parameters, which enables us to more accurately model BDs with our radiative transfer calculations. Along the way, we discuss the most effective method to calculate gaseous absorption, and illustrate the effects of using sub-optimal techniques. With the radiative transfer calculations optimised, we proceed to implement a new inverse method to our NEMESIS retrieval code: Nested Sampling. This algorithm employs state-of-the-art Bayesian statistics to fit spectra and derive probability distributions for each parameter of interest. We verify our new Bayesian method and radiative transfer code against two other codes from separate groups, and investigate the model dependency of parameters using realistic atmospheric models of exoplanets that may be probed by the James Webb Space Telescope. We discuss the model-dependency of each parameter in the context of changing signal-to-noise, finding that some retrieved parameters are more model-dependent than others. Finally, having updated and verified our code through the methods previously discussed, we apply it to a range of ultracool T and Y dwarf atmospheres. The retrieved probability distributions of each parameter representing the atmospheric structure and composition of the brown dwarfs are compared to one another to elucidate trends with decreasing temperature. For the coldest object that we analysed, we discovered a cloud that is consistent with a Na2S cloud, which is expected to form at these temperatures. This is the first Bayesian detection of such a feature on a Y dwarf. We also discuss the plausibility that this cloud may instead be a water cloud. The analysis of these objects and the work presented here helps elucidate the atmospheric structure and composition of the Y dwarf population. We hope that this work will assist not only in future analyses of Y dwarf atmospheres, but also more generally in any atmosphere within or beyond our Solar System