16 citations · 18 across the 8 of their papers we have counts for
8 papers
How Low Can We Go? Minimum Spectroscopic Requirements For Supernova Subtype Classification
Willow Fox Fortino, Federica B. Bianco, Maryam Modjaz +2
Millions of supernovae will be discovered with the Vera C. Rubin Observatory Legacy Survey of Space and Time (LSST). As a result, spectrographs around the world will have to make d…
On the performance of pre-trained vision transformers for supernova spectral classification using different spectral representations
J. Serrano Bell, P. Gálvez Molina, V. Contreras Rojas +4
The spectroscopic classification of supernovae is a key component of time-domain astronomy and plays an important role in the identification of Type Ia events. The increasing volum…
Microlensify: a Transformer Based Machine Learning Classifier for Microlensing Events Trained on TESS Light Curves
Atousa Kalantari, Somayeh Khakpash, Sedighe Sajadian +3
Microlensing can reveal populations of faint compact objects that are otherwise difficult to detect. Depending on their design, all-sky surveys have the potential to search for the…
ABC-SN: Attention Based Classifier for Supernova Spectra
Willow Fox Fortino, Federica B. Bianco, Pavlos Protopapas +2
While significant advances have been made in photometric classification ahead of the millions of transient events and hundreds of supernovae (SNe) each night that the Vera C. Rubin…
Multi-filter UV to NIR Data-driven Light Curve Templates for Stripped Envelope Supernovae
Somayeh Khakpash, Federica B. Bianco, Maryam Modjaz +4
While the spectroscopic classification scheme for Stripped envelope supernovae (SESNe) is clear, and we know that they originate from massive stars that lost some or all their enve…
Every Datapoint Counts: Stellar Flares as a Case Study of Atmosphere Aided Studies of Transients in the LSST Era
Riley W. Clarke, James R. A. Davenport, John Gizis +8
Due to their short timescale, stellar flares are a challenging target for the most modern synoptic sky surveys. The upcoming Vera C. Rubin Legacy Survey of Space and Time (LSST), a…
Toward automated detection of light echoes in synoptic surveys: considerations on the application of the Deep Convolutional Neural Networks
Xiaolong Li, Federica B. Bianco, Gregory Dobler +7
Light Echoes (LEs) are the reflections of astrophysical transients off of interstellar dust. They are fascinating astronomical phenomena that enable studies of the scattering dust…
Reducing ground-based astrometric errors with Gaia and Gaussian processes
W. F. Fortino, G. M. Bernstein, P. H. Bernardinelli +64
Stochastic field distortions caused by atmospheric turbulence are a fundamental limitation to the astrometric accuracy of ground-based imaging. This distortion field is measurable…