Detecting rare neutral atomic-carbon absorbers with a deep neural network.

C  i absorbers play an important role as indicators for exploring the presence of cold gas in the interstellar medium of galaxies. However, the current data base of C  i absorbers is very limited due to their weak absorption feature and rarity. Here, we report results from a search of C  i λλ1560, 1656 absorption lines using Mg  ii absorbers as signposts with modified deep learning algorithms, which provides a very quick way to search for weak C  i absorber candidates. A total of 107 C  i absorbers were detected, which nearly doubles the size of previously known samples. In addition, we found 17 C  i absorbers to be associated with 2175 Å dust absorbers (2DAs), i.e. about 16 per cent C  i absorbers are associated with 2DAs. Comparing the average dust depletion patterns of C  i absorbers with those of damped Lyman α absorbers (DLAs), Mg  ii absorbers, Ca  ii absorbers, and 2175 Å dust absorbers (2DAs) shows that C  i absorbers generally have environments with more dust than DLAs, Mg  ii , and Ca  ii absorbers, but similar to dust in 2DAs. Similarity between the dust depletion pattern of C  i absorbers to that of the warm disc in the Milky Way indicates that C  i absorption clouds are possibly associated with disc components in distant galaxies. Therefore, C  i absorbers are confirmed to be excellent probes to trace cold gas and dust in the Universe. [ABSTRACT FROM AUTHOR]