Related papers: The ZTF Source Classification Project: III. A Cata…

A dataset of 35,608 materials with their topological properties is constructed by combining the density functional theory (DFT) results of Materiae and the Topological Materials Database. Thanks to this, machine-learning approaches are…

We present the first analysis of results from the SuperWASP Variable Stars Zooniverse project, which is aiming to classify 1.6 million phase-folded light curves of candidate stellar variables observed by the SuperWASP all sky survey with…

The rapid increase in serendipitous X-ray source detections requires the development of novel approaches to efficiently explore the nature of X-ray sources. If even a fraction of these sources could be reliably classified, it would enable…

We describe a 22-year survey for variable and transient radio sources, performed with archival images taken with the Molonglo Observatory Synthesis Telescope (MOST). This survey covers $2775 \unit{deg^2}$ of the sky south of $\delta <…

We provide classifications for all 143 million non-repeat photometric objects in the Third Data Release of the Sloan Digital Sky Survey (SDSS) using decision trees trained on 477,068 objects with SDSS spectroscopic data. We demonstrate that…

With large-scale surveys such as the Zwicky Transient Facility (ZTF), it has become possible to obtain a well-sampled light curve spanning the full length of the survey for any discovery within the survey footprint. Similarly, any transient…

We proposed a machine learning approach to identify and distinguish dusty stellar sources employing supervised and unsupervised methods and categorizing point sources, mainly evolved stars, using photometric and spectroscopic data collected…

While optical surveys regularly discover slow transients like supernovae on their own, the most common way to discover extragalactic fast transients, fading away in a few nights, is via follow-up observations of gamma-ray burst and…

Current synoptic sky surveys monitor large areas of the sky to find variable and transient astronomical sources. As the number of detections per night at a single telescope easily exceeds several thousand, current detection pipelines make…

We present an overview and the first data release of ZFIRE, a spectroscopic redshift survey of star-forming galaxies that utilizes the MOSFIRE instrument on Keck-I to study galaxy properties in rich environments at $1.5<z<2.5$. ZFIRE…

Automating real-time anomaly detection is essential for identifying rare transients, with modern survey telescopes generating tens of thousands of alerts per night, and future telescopes, such as the Vera C. Rubin Observatory, projected to…

We present a novel algorithm for scheduling the observations of time-domain imaging surveys. Our Integer Linear Programming approach optimizes an observing plan for an entire night by assigning targets to temporal blocks, enabling strict…

The last couple of decades have seen an emergence of transient detection facilities in various avenues of time domain astronomy which has provided us with a rich dataset of transients. The rates of these transients have implications in star…

The early and complete temporal characterization of optical, fast, transient sources requires continuous and multiband observations over different timescales (hours to months). For time-domain astronomy, using several telescopes to analyze…

We present results from a radio survey for variable and transient sources on 15-min timescales, using the Australian SKA Pathfinder (ASKAP) pilot surveys. The pilot surveys consist of 505 h of observations conducted at around 1 GHz…

We report the first results of a study of variable point sources identified using multi-color time-series photometry from Sloan Digital Sky Survey (SDSS) Stripe 82 over a span of nearly 10 years (1998-2007). We construct a light-curve…

We provide the first results from the complete SNAD adaptive learning pipeline in the context of a broad scope of data from large-scale astronomical surveys. The main goal of this work is to explore the potential of adaptive learning…

We present X-ray point source catalogs obtained from archival Swift observations that have partially or fully covered the 95% confidence error contour of unidentified Fermi sources. In total, 21 out of 37 unidentified Fermi sources have…

Photometric data-driven classification of supernovae becomes a challenge due to the appearance of real-time processing of big data in astronomy. Recent studies have demonstrated the superior quality of solutions based on various machine…

We present RAPID (Real-time Automated Photometric IDentification), a novel time-series classification tool capable of automatically identifying transients from within a day of the initial alert, to the full lifetime of a light curve. Using…