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Variability in Young Stellar Objects (YSOs) is one of their primary characteristics. Long-term, multi-filter, high-cadence monitoring of large YSO samples is the key to understand the partly unusual light-curves that many of these objects…
We have used deep V-band and JHKs-band observations to investigate variability and stellar populations near the Galactic plane in Centaurus, and compared the observations with the Galactic model of Besancon. By applying image subtraction…
We present the first results of the application of supervised classification methods to the Kepler Q1 long-cadence light curves of a subsample of 2288 stars measured in the asteroseismology program of the mission. The methods, originally…
We present results of star variability analysis in OGLE II first bulge field. Photometric database was derived by means of image subtraction method (Wozniak 2000) and contains 4597 objects pre-classified as variables. We analyzed all the…
In this paper we present a catalog which includes 141 bright candidates ($\leq10.27$ mag, V band) showing the infrared (IR) excess at 22 $\mu$m. Of which, 38 stars are known IR excess stars or disk, 23 stars are double or multiple stars and…
The All-Sky Automated Survey for Supernovae (ASAS-SN) is the first optical survey to monitor the entire sky, currently with a cadence of $\lesssim 24$ hours down to $g \lesssim 18.5$ mag. ASAS-SN has routinely operated since 2013,…
A key science goal of large sky surveys such as those conducted by the Vera C. Rubin Observatory and precursors to the Square Kilometre Array is the identification of variable and transient objects. One approach is the statistical analysis…
The All-Sky Automated Survey for Supernovae (ASAS-SN) provides long baseline (${\sim}4$ yrs) light curves for sources brighter than V$\lesssim17$ mag across the whole sky. The Transiting Exoplanet Survey Satellite (TESS) has started to…
Time-domain astronomy is progressing rapidly with the ongoing and upcoming large-scale photometric sky surveys led by the Vera C. Rubin Observatory project (LSST). Billions of variable sources call for better automatic classification…
We analysed the light curves of a large sample of long period variables in the LMC from the AGAPEROS catalogue. The (non)regularity of the light change is discussed in detail showing that the majority of the light curves cannot be described…
The accurate automated classification of variable stars into their respective sub-types is difficult. Machine learning based solutions often fall foul of the imbalanced learning problem, which causes poor generalisation performance in…
The first step when investigating time varying data is the detection of any reliable changes in star brightness. This step is crucial to decreasing the processing time by reducing the number of sources processed in later, slower steps.…
The exact period determination of a multi-periodic variable star based on its luminosity time series data is believed a task requiring skill and experience. Thus the majority of available time series analysis techniques require human…
We explore the synergy between photometric and spectroscopic surveys by searching for periodic variable stars among the targets observed by the Apache Point Observatory Galactic Evolution Experiment (APOGEE) using photometry from the…
With the advent of digital astronomy, new benefits and new problems have been presented to the modern day astronomer. While data can be captured in a more efficient and accurate manor using digital means, the efficiency of data retrieval…
We have shown previously that a broad correlation between the peak radio luminosity and the variability time-scales, approximately L ~ t^5, exists for variable synchrotron emitting sources and that different classes of astrophysical source…
Stars exhibit a bewildering variety of rapidly variable behaviors ranging from explosive magnetic flares to stochastically changing accretion to periodic pulsations or rotation. The principal Rubin Observatory Legacy Survey of Space and…
Classifying variable stars is key for understanding stellar evolution and galactic dynamics. With the demands of large astronomical surveys, machine learning models, especially attention-based neural networks, have become the…
We present a catalog of 4880 newly identified RR Lyrae variable stars (4433 RRab, 446 RRc and 1 RRd) found during the search for supernovae by the All-Sky Automated Survey for Supernovae (ASAS-SN). The light curves, classified using the…
Presented are the results of a near-IR photometric survey on 1678 stars in the direction of the \rho Ophiuchus (\rho Oph) star forming region using data from the 2MASS Calibration Database. For each target in this sample, up to 1584…