From the 1 of 4 linked papers with an AI index.
4 papers
Automatically distinguishing Rubin transients from AGN using variability metrics
Dylan Magill, Matt Nicholl, Philip Wiseman +7
Stochastic variability of active galactic nuclei (AGN) can produce contaminants in the search for explosive extragalactic transients (such as supernovae and tidal disruption events…
Uncertainty-Aware Tidal Disruption Event Classification : A Host-Agnostic Probabilistic Random Forest Approach
Vysakh Anilkumar, Sjoert van Velzen, Marek Kowalski +1
The paper introduces a host‑agnostic, uncertainty‑aware classification framework using a Probabilistic Random Forest to identify tidal disruption events from photometric light curv…
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…
Modelling variability power spectra of active galaxies from irregular time series
Mehdy Lefkir, Simon Vaughan, Daniela Huppenkothen +2
A common feature of Active Galactic Nuclei (AGN) is their random variations in brightness across the whole emission spectrum, from radio to -rays. Studying the nature and origi…