Ming-Feng Ho | Finding Strong Lyα Absorbers in the Shadows of Quasars with Bayesian Machine Learning скачать в хорошем качестве

Ming-Feng Ho | Finding Strong Lyα Absorbers in the Shadows of Quasars with Bayesian Machine Learning

Parallel Talk | Cosmology from Home 2020 https://www.cosmologyfromhome.com/ Talk title: Finding Strong Lyα Absorbers in the Shadows of Quasars with Bayesian Machine Learning Talk abstract: Damped Lyman alpha absorbers (DLAs) are the neutral hydrogen gases around galaxies. The column densities of DLAs are dense enough to cause self-shielding from the UV background and leave absorption features in the quasar spectra. DLAs dominate the neutral hydrogen budget after reionisation. DLAs are also considered to be the systematics in the Baryonic acoustic oscillation measurement from Lyman alpha forest and need to be removed before the analysis. We present a revised version of our previous DLA detecting pipeline using Gaussian processes (GPs). Our automated method allows us to make probabilistic detection on the existence of DLAs per spectrum. We show we can measure DLA properties, the total mass of DLAs, from our pipeline. Finally, we will also show we can extend our GP model to make inference on quasar redshifts.