Related papers: Real-bogus classification for the Zwicky Transient…
The Zwicky Transient Facility (ZTF) survey generates real-time alerts for optical transients, variables, and moving objects discovered in its wide-field survey. We describe the ZTF alert stream distribution and processing (filtering)…
The Zwicky Transient Facility (ZTF) is performing a three-day cadence survey of the visible Northern sky (~3$\pi$). The transient candidates found in this survey are announced via public alerts. As a supplementary product ZTF is also…
Efficient identification and follow-up of astronomical transients is hindered by the need for humans to manually select promising candidates from data streams that contain many false positives. These artefacts arise in the difference images…
We present Tails, an open-source deep-learning framework for the identification and localization of comets in the image data of the Zwicky Transient Facility (ZTF), a robotic optical time-domain survey currently in operation at the Palomar…
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…
The Zwicky Transient Facility (ZTF) has been observing the entire northern sky since the start of 2018 down to a magnitude of 20.5 ($5 \sigma$ for 30s exposure) in $g$, $r$, and $i$ filters. Over the course of two years, ZTF has obtained…
The Zwicky Transient Facility is a new robotic-observing program, in which a newly engineered 600-MP digital camera with a pioneeringly large field of view, 47~square degrees, will be installed into the 48-inch Samuel Oschin Telescope at…
We present a study of the potential for Convolutional Neural Networks (CNNs) to enable separation of astrophysical transients from image artifacts, a task known as "real-bogus" classification without requiring a template subtracted (or…
Ongoing large-scale optical time-domain surveys, such as the Zwicky Transient Facility (ZTF), are producing alerts at unprecedented rates. Analysis of transient sources has so far followed two distinct paths: archival analysis of data on…
At present time Robotic observatory making is of current importance. Having a large field of view and being able to point at anywhere, Robotic astronomical systems are indispensable when they looking for transients like grb, supernovae…
Fermi Gamma-ray Space Telescope has detected a diverse range of gamma-ray transients since its launch in 2008. Over the years, Fermi has accumulated an extensive public archive of transient events. Traditional classification methods for…
A reexamination of period finding algorithms is prompted by new large area astronomical sky surveys that can identify billions of individual sources having a thousand or more observations per source. This large increase in data necessitates…
Wide-field time domain facilities detect transient events in large numbers through difference imaging. For example, Zwicky Transient Facility produces alerts for hundreds of thousands of transient events per night, a rate set to be dwarfed…
Exploration of time domain is now a vibrant area of research in astronomy, driven by the advent of digital synoptic sky surveys. While panoramic surveys can detect variable or transient events, typically some follow-up observations are…
We present Robbie: a general work-flow for the detection and characterization of radio variability and transient events in the image domain. Robbie is designed to work in a batch processing paradigm with a modular design so that components…
The detection of gravitational waves has inaugurated the era of gravitational astronomy and opened new avenues for the multimessenger study of cosmic sources. Thanks to their sensitivity, the Advanced LIGO and Advanced Virgo interferometers…
We present results from applying the SNAD anomaly detection pipeline to the third public data release of the Zwicky Transient Facility (ZTF DR3). The pipeline is composed of 3 stages: feature extraction, search of outliers with machine…
Machine learning has become essential for automated classification of astronomical transients, but current approaches face significant limitations: classifiers trained on simulations struggle with real data, models developed for one survey…
We present a novel pipeline that uses a convolutional neural network (CNN) to improve the detection capability of near-Earth asteroids (NEAs) in the context of planetary defense. Our work aims to minimize the dependency on human…
Robotic wide-field time-domain surveys, such as the Zwicky Transient Facility and the Asteroid Terrestrial-impact Last Alert System, capture dozens of transients each night. The workflows for discovering and classifying transients in survey…