Related papers: Automated supervised classification of variable st…

We use the OGLE-II and OGLE-III data in conjunction with the 2MASS near-infrared (NIR) photometry to identify and study Miras and Semiregular Variables (SRVs) in the Large Magellanic Cloud. We found in total 3221 variables of both types,…

We present the results of a spectroscopic follow-up of various puzzling variable objects detected in the OGLE-III Galactic disk and bulge fields. The sample includes mainly short-period multi-mode pulsating stars that could not have been…

In this work we apply and expand on a recently introduced outlier detection algorithm that is based on an unsupervised random forest. We use the algorithm to calculate a similarity measure for stellar spectra from the Apache Point…

We present second epoch optical spectra for 30 changing-look (CL) candidates found by searching for Type-1 optical variability in a sample of active galactic nuclei (AGNs) spectroscopically classified as Type 2. We use a random-forest-based…

We describe variable stars found in the data collected during the OGLE-III Shallow Survey covering the I-band magnitude range from 9.7 mag to 14.5 mag. The main result is the extension of period--luminosity relations for Cepheids up to 134…

The photometry data base of the second phase of the OGLE microlensing experiment, OGLE-II, is a rich source of information about the kinematics and structure of the Galaxy. In this work we use the OGLE-II proper motion catalogue to identify…

We present the second part of the OGLE Catalog of Periodic Variable Stars in the Galactic bulge. 800 variable stars found in four Baade's Window fields BW1, BW2, BW3 and BW4 are presented. Among them 71 are classified as pulsating, 465 as…

We present a variability study of 4646 massive stars in the Small Magellanic Cloud (SMC) with known spectral types from the catalog of Bonanos et al. (2010) using the light curves from the OGLE-III database. The goal is to exploit the time…

Most existing star-galaxy classifiers depend on the reduced information from catalogs, necessitating careful data processing and feature extraction. In this study, we employ a supervised machine learning method (GoogLeNet) to automatically…

We present the first part of a new catalog of variable stars (OIII-CVS) compiled from the data collected in the course of the third phase of the Optical Gravitational Lensing Experiment (OGLE-III). In this paper we describe the catalog of…

The data of 8,852 and 2,927 variable stars detected by OGLE survey in the Large and Small Magellanic Clouds are presented. They are cross-identified with the SIRIUS JHK survey data, and their infrared properties are discussed. Variable red…

We present three color, BVI maps of the Small Magellanic Cloud. The maps contain precise photometric and astrometric data for about 2.2 million stars from the central regions of the SMC bar covering ~2.4 square degrees on the sky. Mean…

Due to the latest advances in technology, telescopes with significant sky coverage will produce millions of astronomical alerts per night that must be classified both rapidly and automatically. Currently, classification consists of…

We present the first systematic search for microlensing events with variability in their baselines using data from the third phase of the Optical Gravitational Lensing Experiment (OGLE-III). A total of 137 candidates (88 new) was discovered…

We present ORACLE, the first hierarchical deep-learning model for real-time, context-aware classification of transient and variable astrophysical phenomena. ORACLE is a recurrent neural network with Gated Recurrent Units (GRUs), and has…

This paper is the first part of the Catalog of Periodic Variable Stars in the Galactic bulge. The Catalog is based on observations collected during the OGLE microlensing search. 213 periodic variable stars brighter than I=18 mag: 31…

We adapt the friends of friends algorithm to the analysis of light curves, and show that it can be successfully applied to searches for transient phenomena in large photometric databases. As a test case we search OGLE-III light curves for…

Machine learning has achieved an important role in the automatic classification of variable stars, and several classifiers have been proposed over the last decade. These classifiers have achieved impressive performance in several…

Classification of young stellar objects (YSOs) into different evolutionary stages helps us to understand the formation process of new stars and planetary systems. Such classification has traditionally been based on spectral energy…

The details of bulge formation via collapse, mergers, secular processes or their interplay remain unresolved. To start answering this question and quantify the importance of distinct mechanisms, we mapped a sample of three galactic bulges…