Description
Ultracool Dwarfs (UCDs) are faint, low luminosity objects that span the stellar-substellar boundary, encompassing the lowest-mass stars and brown dwarfs. The Euclid mission will uncover many hundreds of UCDs thanks to its wide coverage and deep sensitivity. To most completely characterize a Euclid UCD the wide wavelength coverage of the Euclid optical and near-infrared photometry should be combined with the low-resolution near-infrared spectrum. In this study we use the ATMO 2020 atmosphere models to assess how we can constrain atmospheric parameters such as effective temperature, surface gravity and metallicity from Euclid spectrophotometry. We use these models to simulate a typical Euclid UCD dataset, and then perform Monte Carlo simulations with randomly generate Gaussian noise to fit our atmospheric model grid to our simulated dataset. We explore how best to weight the photometric and spectroscopic data points in our model fitting simulations, and determine the signal-to-noise required to most accurately determine the atmospheric parameters. Finally, we perform our model fitting on a real Euclid dataset of a T7 type brown dwarf, providing constraints on its effective temperature, surface gravity and metallicity.
