Papers › Detecting Multiple DLAs per Spectrum in SDSS DR12 with Gaussian Processes
Detecting Multiple DLAs per Spectrum in SDSS DR12 with Gaussian Processes
Ming-Feng Ho, Simeon Bird, Roman Garnett
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We present a revised version of our automated technique using Gaussian processes (GPs) to detect Damped Lyman-α absorbers (DLAs) along quasar (QSO) sightlines. The main improvement is to allow our Gaussian process pipeline to detect multiple DLAs along a single sightline. Our DLA detections are regularised by an improved model for the absorption from the Lyman-α forest which improves performance at high redshift. We also introduce a model for unresolved sub-DLAs which reduces mis-classifications of absorbers without detectable damping wings. We compare our results to those of two different large-scale DLA catalogues and provide a catalogue of the processed results of our Gaussian process pipeline using 158 825 Lyman-α spectra from SDSS data release 12. We present updated estimates for the statistical properties of DLAs, including the column density distribution function (CDDF), line density (dN/dX), and neutral hydrogen density (Ω_(DLA)).
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