Search Results for author: Kaisey S. Mandel

Found 6 papers, 1 papers with code

Real-time Detection of Anomalies in Multivariate Time Series of Astronomical Data

no code implementations15 Dec 2021 Daniel Muthukrishna, Kaisey S. Mandel, Michelle Lochner, Sara Webb, Gautham Narayan

Astronomical transients are stellar objects that become temporarily brighter on various timescales and have led to some of the most significant discoveries in cosmology and astronomy.

Anomaly Detection Astronomy +2

Real-Time Detection of Anomalies in Large-Scale Transient Surveys

no code implementations29 Oct 2021 Daniel Muthukrishna, Kaisey S. Mandel, Michelle Lochner, Sara Webb, Gautham Narayan

We demonstrate our methods' ability to provide anomaly scores as a function of time on light curves from the Zwicky Transient Facility.

Anomaly Detection

Testing the Consistency of Dust Laws in SN Ia Host Galaxies: A BayeSN Examination of Foundation DR1

no code implementations10 Feb 2021 Stephen Thorp, Kaisey S. Mandel, David O. Jones, Sam M. Ward, Gautham Narayan

We train a new version of BayeSN, continuous from 0. 35--0. 95 $\mu$m, which we use to model the properties of SNe Ia in the rest-frame $z$-band, study the properties of dust in their host galaxies, and construct a Hubble diagram of SN Ia distances determined from full $griz$ light curves.

Astrophysics of Galaxies Cosmology and Nongalactic Astrophysics

RAPID: Early Classification of Explosive Transients using Deep Learning

no code implementations29 Mar 2019 Daniel Muthukrishna, Gautham Narayan, Kaisey S. Mandel, Rahul Biswas, Renée Hložek

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.

Classification General Classification +3

The Photometric LSST Astronomical Time-series Classification Challenge (PLAsTiCC): Data set

3 code implementations28 Sep 2018 The PLAsTiCC team, Tarek Allam Jr., Anita Bahmanyar, Rahul Biswas, Mi Dai, Lluís Galbany, Renée Hložek, Emille E. O. Ishida, Saurabh W. Jha, David O. Jones, Richard Kessler, Michelle Lochner, Ashish A. Mahabal, Alex I. Malz, Kaisey S. Mandel, Juan Rafael Martínez-Galarza, Jason D. McEwen, Daniel Muthukrishna, Gautham Narayan, Hiranya Peiris, Christina M. Peters, Kara Ponder, Christian N. Setzer, The LSST Dark Energy Science Collaboration, The LSST Transients, Variable Stars Science Collaboration

The Photometric LSST Astronomical Time Series Classification Challenge (PLAsTiCC) is an open data challenge to classify simulated astronomical time-series data in preparation for observations from the Large Synoptic Survey Telescope (LSST), which will achieve first light in 2019 and commence its 10-year main survey in 2022.

Instrumentation and Methods for Astrophysics Solar and Stellar Astrophysics

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