Models and Simulations for the Photometric LSST Astronomical Time Series Classification Challenge (PLAsTiCC). (arXiv:1903.11756v1 [astro-ph.HE])
<a href="http://arxiv.org/find/astro-ph/1/au:+Kessler_R/0/1/0/all/0/1">R. Kessler</a>, <a href="http://arxiv.org/find/astro-ph/1/au:+Narayan_G/0/1/0/all/0/1">G. Narayan</a>, <a href="http://arxiv.org/find/astro-ph/1/au:+Avelino_A/0/1/0/all/0/1">A. Avelino</a>, <a href="http://arxiv.org/find/astro-ph/1/au:+Bachelet_E/0/1/0/all/0/1">E. Bachelet</a>, <a href="http://arxiv.org/find/astro-ph/1/au:+Biswas_R/0/1/0/all/0/1">R. Biswas</a>, <a href="http://arxiv.org/find/astro-ph/1/au:+Brown_P/0/1/0/all/0/1">P. J. Brown</a>, <a href="http://arxiv.org/find/astro-ph/1/au:+Chernoff_D/0/1/0/all/0/1">D. F. Chernoff</a>, <a href="http://arxiv.org/find/astro-ph/1/au:+Connolly_A/0/1/0/all/0/1">A. J. Connolly</a>, <a href="http://arxiv.org/find/astro-ph/1/au:+Dai_M/0/1/0/all/0/1">M. Dai</a>, <a href="http://arxiv.org/find/astro-ph/1/au:+Daniel_S/0/1/0/all/0/1">S. Daniel</a>, <a href="http://arxiv.org/find/astro-ph/1/au:+Stefano_R/0/1/0/all/0/1">R. Di Stefano</a>, <a href="http://arxiv.org/find/astro-ph/1/au:+Drout_M/0/1/0/all/0/1">M. R. Drout</a>, <a href="http://arxiv.org/find/astro-ph/1/au:+Galbany_L/0/1/0/all/0/1">L. Galbany</a>, <a href="http://arxiv.org/find/astro-ph/1/au:+Gonzalez_Gaitan_S/0/1/0/all/0/1">S. González-Gaitán</a>, <a href="http://arxiv.org/find/astro-ph/1/au:+Graham_M/0/1/0/all/0/1">M. L. Graham</a>, <a href="http://arxiv.org/find/astro-ph/1/au:+Hlozek_R/0/1/0/all/0/1">R. Hložek</a>, <a href="http://arxiv.org/find/astro-ph/1/au:+Ishida_E/0/1/0/all/0/1">E. E. O. Ishida</a>, <a href="http://arxiv.org/find/astro-ph/1/au:+Guillochon_J/0/1/0/all/0/1">J. Guillochon</a>, <a href="http://arxiv.org/find/astro-ph/1/au:+Jha_S/0/1/0/all/0/1">S. W. Jha</a>, <a href="http://arxiv.org/find/astro-ph/1/au:+Jones_D/0/1/0/all/0/1">D. O. Jones</a>, <a href="http://arxiv.org/find/astro-ph/1/au:+Mandel_K/0/1/0/all/0/1">K. S. Mandel</a>, <a href="http://arxiv.org/find/astro-ph/1/au:+Muthukrishna_D/0/1/0/all/0/1">D. Muthukrishna</a>, <a href="http://arxiv.org/find/astro-ph/1/au:+OGrady_A/0/1/0/all/0/1">A. O'Grady</a>, <a href="http://arxiv.org/find/astro-ph/1/au:+Peters_C/0/1/0/all/0/1">C. M. Peters</a>, <a href="http://arxiv.org/find/astro-ph/1/au:+Pierel_J/0/1/0/all/0/1">J. R. Pierel</a>, <a href="http://arxiv.org/find/astro-ph/1/au:+Ponder_K/0/1/0/all/0/1">K. A. Ponder</a>, <a href="http://arxiv.org/find/astro-ph/1/au:+Prsa_A/0/1/0/all/0/1">A. Prša</a>, <a href="http://arxiv.org/find/astro-ph/1/au:+Rodney_S/0/1/0/all/0/1">S. Rodney</a>, <a href="http://arxiv.org/find/astro-ph/1/au:+Villar_V/0/1/0/all/0/1">V. A. Villar</a>
We describe the simulated data sample for the “Photometric LSST Astronomical
Time Series Classification Challenge” (PLAsTiCC), a publicly available
challenge to classify transient and variable events that will be observed by
the Large Synoptic Survey Telescope (LSST), a new facility expected to start in
the early 2020s. The challenge was hosted by Kaggle, ran from 2018 Sep 28 to
2018 Dec 17, and included 1,094 teams competing for prizes. Here we provide
details of the 18 transient and variable source models, which were not revealed
until after the challenge, and release the model libraries at
https://doi.org/10.5281/zenodo.2612896. We describe the LSST Operations
Simulator used to predict realistic observing conditions, and we describe the
publicly available SNANA simulation code used to transform the models into
observed fluxes and uncertainties in the LSST passbands (ugrizy). Although
PLAsTiCC has finished, the publicly available models and simulation tools are
being used within the astronomy community to further improve classification,
and to study contamination in photometrically identified samples of type Ia
supernova used to measure properties of dark energy. Our simulation framework
will continue serving as a platform to improve the PLAsTiCC models, and to
develop new models.
We describe the simulated data sample for the “Photometric LSST Astronomical
Time Series Classification Challenge” (PLAsTiCC), a publicly available
challenge to classify transient and variable events that will be observed by
the Large Synoptic Survey Telescope (LSST), a new facility expected to start in
the early 2020s. The challenge was hosted by Kaggle, ran from 2018 Sep 28 to
2018 Dec 17, and included 1,094 teams competing for prizes. Here we provide
details of the 18 transient and variable source models, which were not revealed
until after the challenge, and release the model libraries at
https://doi.org/10.5281/zenodo.2612896. We describe the LSST Operations
Simulator used to predict realistic observing conditions, and we describe the
publicly available SNANA simulation code used to transform the models into
observed fluxes and uncertainties in the LSST passbands (ugrizy). Although
PLAsTiCC has finished, the publicly available models and simulation tools are
being used within the astronomy community to further improve classification,
and to study contamination in photometrically identified samples of type Ia
supernova used to measure properties of dark energy. Our simulation framework
will continue serving as a platform to improve the PLAsTiCC models, and to
develop new models.
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