The High Cadence Transient Survey (HiTS) aims to discover and study transient objects with characteristic timescales between hours and days, such as pulsating, eclipsing, and exploding stars. This survey represents a unique laboratory to explore large etendue observations from cadences of about 0.1 days and test new computational tools for the analysis of large data. This work follows a fully data science approach, from the raw data to the analysis and classification of variable sources. We compile a catalog of ~15 million object detections and a catalog of ~2.5 million light curves classified by variability. The typical depth of the survey is 24.2, 24.3, 24.1, and 23.8 in the u, g, r, and i bands, respectively. We classified all point-like nonmoving sources by first extracting features from their light curves and then applying a random forest classifier. For the classification, we used a training set constructed using a combination of cross-matched catalogs, visual inspection, transfer/active learning, and data augmentation. The classification model consists of several random forest classifiers organized in a hierarchical scheme. The classifier accuracy estimated on a test set is approximately 97%. In the unlabeled data, 3485 sources were classified as variables, of which 1321 were classified as periodic. Among the periodic classes, we discovered with high confidence one {delta} Scuti, 39 eclipsing binaries, 48 rotational variables, and 90 RR Lyrae, and for the nonperiodic classes, we discovered one cataclysmic variable, 630 QSOs, and one supernova candidate.

Cone search capability for table J/AJ/156/186/cat13a (HiTS source catalog for 2013 u band observational campaign)

Cone search capability for table J/AJ/156/186/cat14a (HiTS source catalog for 2014 g band observational campaign)

Cone search capability for table J/AJ/156/186/cat15a (HiTS source catalog for 2015 gri bands observational campaign)