Related papers: PyTICS: An Iterative Method for Photometric Lightc…
We introduce a numerical optimization method to extract the X-ray reverberation response functions from the multi-band light curves of the active galactic nuclei. This approach does not require prior assumptions about the accretion disc and…
Information on the structure around active galactic nuclei (AGN) has long been derived from measuring lags in their varying light output at different wavelengths. In principle, infrared data would reach to larger radii, potentially even…
Catalogs of periodic variable stars contain large numbers of periodic light-curves (photometric time series data from the astrophysics domain). Separating anomalous objects from well-known classes is an important step towards the discovery…
Laser guide stars with adaptive optics allow astronomical image correction in the absence of a natural guide star. Single guide star systems with a star created in the earth's sodium layer can be used to correct the wavefront in the near…
With an ever-increasing amount of astronomical data being collected, manual classification has become obsolete; and machine learning is the only way forward. Keeping this in mind, the Large Synoptic Survey Telescope (LSST) Team hosted the…
We test the standardizability of a homogeneous sample of 41 lower-redshift ($0.00415\leq z \leq 0.474$) active galactic nuclei (AGNs) reverberation-mapped (RM) using the broad H$\alpha$ and H$\beta$ emission lines. We find that these…
Observations of 21cm line from neutral hydrogen promise to be an exciting new probe of astrophysics and cosmology during the Cosmic Dawn and through the Epoch of Reionization (EoR) to when dark energy accelerates the expansion of the…
Aperiodic variability is a characteristic feature of young stars, massive stars, and active galactic nuclei. With the recent proliferation of time domain surveys, it is increasingly essential to develop methods to quantify and analyze…
Phenomenological characteristics of the sample of the Algol-type stars are revised using a recently developed NAV ("New Algol Variable") algorithm (2012Ap.....55..536A, 2012arXiv 1212.6707A) and compared to that obtained using common…
A simple, yet general, formalism for the optimized linear combination of astrophysical images is constructed and demonstrated. The formalism allows the user to combine multiple undersampled images to provide oversampled output at high…
Tuning a complex simulation code refers to the process of improving the agreement of a code calculation with respect to a set of experimental data by adjusting parameters implemented in the code. This process belongs to the class of inverse…
Context. A defining characteristic of active galactic nuclei (AGN) that distinguishes them from other astronomical sources is their stochastic variability, which is observable across the entire electromagnetic spectrum. Upcoming optical…
We suggest a new algorithm to remove systematic effects in a large set of lightcurves obtained by a photometric survey. The algorithm can remove systematic effects, like the ones associated with atmospheric extinction, detector efficiency,…
We present a GUI-based interactive Python program, VIMAP, which generates radio spectral index maps of active galactic nuclei (AGN) from Very Long Baseline Interferometry (VLBI) maps obtained at different frequencies. VIMAP is a handy tool…
The improvement of the calibration relation for determining the size of the broad-line region from the observed optical luminosity of active galactic nuclei (AGN) is a necessary task to study fundamental parameters of distant AGNs such as…
The Sloan Digital Sky Survey Reverberation Mapping (SDSS-RM) program monitors 849 active galactic nuclei (AGN) both spectroscopically and photometrically. The photometric observations used in this work span over four years and provide an…
The central engines of Active Galactic Nuclei (AGNs) are powered by accreting supermassive black holes, and while AGNs are known to play an important role in galaxy evolution, the key physical processes occur on scales that are too small to…
We present the first evidence that adaptive learning techniques can boost the discovery of unusual objects within astronomical light curve data sets. Our method follows an active learning strategy where the learning algorithm chooses…
We present Stellar Locus Regression (SLR), a method of directly adjusting the instrumental broadband optical colors of stars to bring them into accord with a universal stellar color-color locus, producing accurately calibrated colors for…
Traditional artificial-star tests are widely applied to photometry in crowded stellar fields. However, to obtain reliable binary fractions (and their uncertainties) of remote, dense, and rich star clusters, one needs to recover huge numbers…