The Completed SDSS-IV extended Baryon Oscillation Spectroscopic Survey: The Damped Lyman-$\alpha$ systems Catalog

TL;DR

This paper presents a large catalog of Damped Lyman-$\alpha$ systems identified in SDSS DR16 data using CNNs, providing insights into their characteristics and detection efficiency.

Contribution

It introduces a new catalog of DLAs from SDSS DR16 using CNN-based identification, with detailed analysis of detection efficiency and purity.

Findings

117,458 absorber candidates identified

Over 57,000 DLAs with high column density

Detection efficiency and purity exceed 90% for certain ranges

Abstract

We present the characteristics of the Damped Lyman-$\alpha$ (DLA) systems found in the data release DR16 of the extended Baryon Oscillation Spectroscopic Survey (eBOSS) of the Sloan Digital Sky Survey (SDSS). DLAs were identified using the convolutional neural network (CNN) of~\cite{Parks2018}. A total of 117,458 absorber candidates were found with $2 \leq \zdla \leq 5.5$ and $19.7 \leq \lognhi \leq 22$, including 57,136 DLA candidates with $\lognhi \geq 20.3$. Mock quasar spectra were used to estimate DLA detection efficiency and the purity of the resulting catalog. Restricting the quasar sample to bright forests, i.e. those with mean forest fluxes $\meanflux>2\times\fluxunit$, the completeness and purity are greater than 90\% for DLAs with column densities in the range $20.1\leq \lognhi \leq 22$.