Why So Blue? Atmospheric Retrieval of Brown Dwarf J1416A
Ember Vosmek-Park
Department of Physics & Astronomy
Faculty Supervisor: Eileen Gonzales
The objective for this project is performing L dwarf atmospheric retrievals to contribute to the Arcana of the Ancients spectral metallicity survey. Metallicity is an important parameter that influences the formation and evolution of brown dwarfs. The subject for retrievals is the unusually blue L class brown dwarf J1416A, using JWST data. Retrieved parameters will be compared with values from the previous Brewster retrieval done by Gonzales et al. 2020 using lower resolution SpEX data, in which they found the best-fit to be a power-law deck cloud model. This semester, in-progress retrieval cloud models include a power-law cloud deck run, a gray cloud deck run, and a cloudless run. The Brewster spectral inversion code for analysis of emission spectra of brown dwarfs and giant planets models atmospheres as a set of one dimensional layers. Unlike physically motivated grid models, with Brewster there is no requirement for self-consistency of model parameters (pressure, temperature, gas opacity, cloud opacity), which allows for a more robust investigation of their characteristics without the bias of grid models. The Brewster framework uses Bayesian parameter estimation based on the MCMC Python implementation, the emcee sampler, and model selection to find the best fit parameters given the data.