82 citations · 101 across the 10 of their papers we have counts for
12 papers
AT2025agpz in Rubin commissioning data: distinguishing a luminous interacting supernova from nuclear transients in compact galaxies
C. R. Angus, M. Quilt, H. F. Stevance +37
The Vera C. Rubin Observatory's Legacy Survey of Space and Time will discover unprecedented numbers of rare, long-lived optical transients, many of which will be too faint or too n…
ATLAS100 -- I. A volume-limited sample of supernovae and related transients within 100 Mpc
Shubham Srivastav, Stephen J. Smartt, Thomas Moore +29
We present ATLAS100 -- a sample of 1729 supernovae and other explosive optical transients within Mpc observed by the ATLAS survey over a span of 5.75 years from 2017 Sep…
AT2024lhc and AT2024kmq in the landscape of featureless tidal disruption events
Yuhan Yao, Ryan Chornock, Andrew Mummery +39
We study AT2024kmq and AT2024lhc, two tidal disruption events (TDEs) with blue featureless spectra associated with high-mass black holes (). Both even…
Attention-Based Preprocessing Framework for Improving Rare Transient Classification
Xinyue Sheng, Tuan Dung Pham, Zichi Zhang +2
With large numbers of transients discovered by current and future imaging surveys, machine learning is increasingly applied to light curve and host galaxy properties to select even…
MALLORN: Many Artificial LSST Lightcurves based on Observations of Real Nuclear transients
Dylan Magill, Matt Nicholl, Vysakh Anilkumar +10
The Vera C. Rubin Observatory's 10-Year Legacy Survey of Space and Time (LSST) is expected to produce a hundredfold increase in the number of transients we observe. However, there…
The La Silla Schmidt Southern Survey
Adam A. Miller, Natasha S. Abrams, Greg Aldering +75
We present the La Silla Schmidt Southern Survey (LS4), a new wide-field, time-domain survey to be conducted with the 1 m ESO Schmidt telescope. The 268 megapixel LS4 camera mosaics…
NEural Engine for Discovering Luminous Events (NEEDLE): identifying rare transient candidates in real time from host galaxy images
Xinyue Sheng, Matt Nicholl, Ken W. Smith +6
Known for their efficiency in analyzing large data sets, machine learning classifiers are widely used in wide-field sky surveys. The upcoming Vera C. Rubin Observatory Legacy of Ti…
Unprecedented early flux excess in the hybrid 02es-like type Ia supernova 2022ywc indicates interaction with circumstellar material
Shubham Srivastav, T. Moore, M. Nicholl +20
We present optical photometric and spectroscopic observations of the 02es-like type Ia supernova (SN) 2022ywc. The transient occurred in the outskirts of an elliptical host galaxy…
AT2022aedm and a new class of luminous, fast-cooling transients in elliptical galaxies
M. Nicholl, S. Srivastav, M. D. Fulton +49
We present the discovery and extensive follow-up of a remarkable fast-evolving optical transient, AT2022aedm, detected by the Asteroid Terrestrial impact Last Alert Survey (ATLAS).…
Stochastic Recurrent Neural Networks for Modelling Astronomical Time Series: Advantages and Limitations
Xinyue Sheng, Matt Nicholl, Nicholas Ross
This paper reviews the Stochastic Recurrent Neural Network (SRNN) as applied to the light curves of Active Galactic Nuclei by Sheng et al. (2022). Astronomical data have inherent l…
The Birth of a Relativistic Jet Following the Disruption of a Star by a Cosmological Black Hole
Dheeraj R. Pasham, Matteo Lucchini, Tanmoy Laskar +63
A black hole can launch a powerful relativistic jet after it tidally disrupts a star. If this jet fortuitously aligns with our line of sight, the overall brightness is Doppler boos…
LSST Cadence Strategy Evaluations for AGN Time-series Data in Wide-Fast-Deep Field
Xinyue Sheng, Nicholas Ross, Matt Nicholl
Machine learning is a promising tool to reconstruct time-series phenomena, such as variability of active galactic nuclei (AGN), from sparsely-sampled data. Here we use three Contin…