Related papers: Characterization of Dwarf Novae Using SDSS Colors

We developed a Deep Convolutional Neural Network (CNN), used as a classifier, to estimate photometric redshifts and associated probability distribution functions (PDF) for galaxies in the Main Galaxy Sample of the Sloan Digital Sky Survey…

We present a method which uses cuts in colour-colour and reduced proper motion-colour space to select white dwarfs without the recourse to spectroscopy while allowing an adjustable compromise between completeness and efficiency. Rather than…

SDSS-V is carrying out a dedicated survey for white dwarfs, single and in binaries, and we report the analysis of the spectroscopy of cataclysmic variables (CVs) and CV candidates obtained during the final plug plate observations of SDSS.…

A method is presented for automated photometric classification of supernovae (SNe) as Type-Ia or non-Ia. A two-step approach is adopted in which: (i) the SN lightcurve flux measurements in each observing filter are fitted separately; and…

Stars exhibit a range of variability periods that depend on their mass, age, and evolutionary stage. For space-based photometric data, convolutional neural networks (CNNs) have demonstrated success in recovering and measuring periodic…

We present extensive spectroscopy and photometry of the dwarf nova V630 Cassiopeiae. A late-type (K4-5) absorption spectrum is easily detectable, from which we derive the orbital parameters. We find a spectroscopic period of P=2.56387 +/-…

Large-scale astronomical surveys have the potential to capture data on large numbers of strongly gravitationally lensed supernovae (LSNe). To facilitate timely analysis and spectroscopic follow-up before the supernova fades, an LSN needs to…

We have examined the optical/X-ray light curves of seven well-observed recurrent novae, V745 Sco, M31N 2008-12a, LMC N 1968, U Sco, RS Oph, LMC N 2009a, T Pyx, and one recurrent nova candidate LMC N 2012a. Six novae out of the eight show a…

A wide range of practically important problems is nowadays efficiently solved using artificial neural networks. This gave momentum to intensive development of their optical implementations, among which, the so-called diffractive neural…

In astrophysics, we often aim to estimate one or more parameters for each member object in a population and study the distribution of the fitted parameters across the population. In this paper, we develop novel methods that allow us to take…

We present a data-driven approach to automatically detect L dwarfs from Sloan Digital Sky Survey(SDSS) images using an improved Faster R-CNN framework based on deep learning. The established L dwarf automatic detection (LDAD) model…

Using a machine learning (ML) method, we mine DB white dwarfs (DBWDs) from the Sloan Digital Sky Survey (SDSS) Data Release (DR) 12 and DR14. The ML method consists of two parts: feature extraction and classification. The least absolute…

The Dwarf Nova Oscillations observed in Cataclysmic Variable (CV) stars are interpreted in the context of a Low Inertia Accretor model, in which accretion on to an equatorial belt of the white dwarf primary causes the belt to vary its…

We present a synthetic spectral analysis of nearly the entire far ultraviolet International Ultraviolet Explorer (IUE) archive of spectra of dwarf novae in or near outburst. The study includes 46 systems of all dwarf nova subtypes both…

Gravitationally lensed supernovae (SNe) are extremely rare and fade quickly; as a result, they are challenging to detect. To identify lensed SNe in large imaging datasets, current surveys primarily rely on the {\it magnification} effect of…

Studies of cosmology, galaxy evolution, and astronomical transients with current and next-generation wide-field imaging surveys like the Rubin Observatory Legacy Survey of Space and Time (LSST) are all critically dependent on estimates of…

The ongoing optical time-domain astronomy surveys are routinely reporting fifty transient candidates per night. Here, I investigate the demographics of astronomical transients and supernova classifications reported to the Transient Name…

The abundance of gaps in satellite image time series often complicates the application of deep learning models such as convolutional neural networks for spatiotemporal modeling. Based on previous work in computer vision on image inpainting,…

We systematically surveyed period variations of superhumps in SU UMa-type dwarf novae based on newly obtained data and past publications. In many systems, the evolution of superhump period are found to be composed of three distinct stages:…

We present the discovery of 17 double white dwarf (WD) binaries from our on-going search for extremely low mass (ELM) <0.3 Msun WDs, objects that form from binary evolution. Gaia parallax provides a new means of target selection that we use…