{"@context":"http://schema.org","@type":"Dataset","@id":"https://doi.org/10.34691/FK2/9SGXZG","identifier":"https://doi.org/10.34691/FK2/9SGXZG","name":"Replicar los datos para: The high cadence transient survey (Hits): Source, light-curve and classification catalogs","creator":[{"@type":"Person","givenName":"Jorge","familyName":"Martínez Palomera","affiliation":{"@type":"Organization","name":"Universidad de Chile"},"name":"Martínez Palomera, Jorge"},{"@type":"Person","givenName":"Francisco","familyName":"Förster","affiliation":{"@type":"Organization","name":"Universidad de Chile"},"name":"Förster, Francisco"}],"author":[{"@type":"Person","givenName":"Jorge","familyName":"Martínez Palomera","affiliation":{"@type":"Organization","name":"Universidad de Chile"},"name":"Martínez Palomera, Jorge"},{"@type":"Person","givenName":"Francisco","familyName":"Förster","affiliation":{"@type":"Organization","name":"Universidad de Chile"},"name":"Förster, Francisco"}],"datePublished":"2019-06-20","dateModified":"2023-04-04","version":"1","description":"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 to 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 u, g, r, and i bands, respectively. We classified all point-like non-moving 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, 3,485 sources were classified as variables, of which 1,321 were classified as periodic. Among the periodic classes we discovered with high confidence, 1 δ scuti, 39 eclipsing binaries, 48 rotational variables, and 90 RR-Lyrae. For the non-periodic classes we discovered 1 cataclysmic variables, 630 QSO, and 1 supernova candidate.","keywords":["Astronomía y astrofísica","Light-curve catalog","Variable stars"],"citation":[{"@type":"CreativeWork","name":"Martínez-Palomera, Jorge, & Förster, Francisco. (2018). THE HIGH CADENCE TRANSIENT SURVEY (HITS): Source, light-curve and classification catalogs.","@id":"http://doi.org/10.5281/zenodo.1410651","identifier":"http://doi.org/10.5281/zenodo.1410651","url":"http://doi.org/10.5281/zenodo.1410651"}],"license":"http://creativecommons.org/licenses/by/4.0","includedInDataCatalog":{"@type":"DataCatalog","name":"Repositorio de datos de investigación de la Universidad de Chile","url":"http://datos.uchile.cl"},"publisher":{"@type":"Organization","name":"Repositorio de datos de investigación de la Universidad de Chile"},"provider":{"@type":"Organization","name":"Repositorio de datos de investigación de la Universidad de Chile"},"distribution":[{"@type":"DataDownload","name":"HiTS_labeled_set.fits","encodingFormat":"application/fits","contentSize":964800,"description":"FITS file, 2 HDUs total:\nThe primary HDU; 1 Table HDU(s) \nThe following recognized metadata keys have been found in the FITS file:\nNAXIS; NAXIS1; NAXIS0; \n","@id":"https://doi.org/10.34691/FK2/9SGXZG/CMX2FI","identifier":"https://doi.org/10.34691/FK2/9SGXZG/CMX2FI","contentUrl":"http://datos.uchile.cl/api/access/datafile/60"}]}