---
description: 'The Photometric LSST Astronomical Time-Series Classification Challenge
  (PLAsTiCC) is a community-wide challenge to spur development of algorithms to classify
  astronomical transients. The Large Synoptic Survey Telescope (LSST) will discover
  tens of thousands of transient phenomena every single night. To deal with this massive
  onset of data, automated algorithms to classify and sort astronomical transients
  are crucial.


  PLAsTiCC, based on the highly successful Supernova Photometric Classification Challenge,
  will consist of a set of realistic LSST simulations of a variety of transient and
  variable phenomena. The challenge will be publicly available on a popular data science
  platform, encouraging algorithm submissions from outside the Astronomy community.

  '
homepage: https://zenodo.org/records/2539456
version: 0.0.1
citation: "@article{Kessler_2019,\n   title={Models and Simulations for the Photometric\
  \ LSST Astronomical Time Series Classification Challenge (PLAsTiCC)},\n   volume={131},\n\
  \   ISSN={1538-3873},\n   url={http://dx.doi.org/10.1088/1538-3873/ab26f1},\n  \
  \ DOI={10.1088/1538-3873/ab26f1},\n   number={1003},\n   journal={Publications of\
  \ the Astronomical Society of the Pacific},\n   publisher={IOP Publishing},\n  \
  \ author={Kessler, R. and Narayan, G. and Avelino, A. and Bachelet, E. and Biswas,\
  \ R. and Brown, P. J. and Chernoff, D. F. and Connolly, A. J. and Dai, M. and Daniel,\
  \ S. and Stefano, R. Di and Drout, M. R. and Galbany, L. and González-Gaitán, S.\
  \ and Graham, M. L. and Hložek, R. and Ishida, E. E. O. and Guillochon, J. and Jha,\
  \ S. W. and Jones, D. O. and Mandel, K. S. and Muthukrishna, D. and O’Grady, A.\
  \ and Peters, C. M. and Pierel, J. R. and Ponder, K. A. and Prša, A. and Rodney,\
  \ S. and Villar, V. A.},\n   year={2019},\n   month=jul, pages={094501} }\n"
dataset_info:
  config_name: train_only
  features:
  - name: lightcurve
    sequence:
    - name: band
      dtype: string
    - name: flux
      dtype: float32
    - name: flux_err
      dtype: float32
    - name: time
      dtype: float32
  - name: hostgal_photoz
    dtype: float32
  - name: hostgal_specz
    dtype: float32
  - name: redshift
    dtype: float32
  - name: obj_type
    dtype: string
  - name: object_id
    dtype: string
  splits:
  - name: train
    num_bytes: 20200662
    num_examples: 1000
  download_size: 2087385
  dataset_size: 20200662
configs:
- config_name: train_only
  data_files:
  - split: train
    path: train_only/train-*
---

# Plasticc Dataset

CC BY 4.0

The Photometric LSST Astronomical Time-Series Classification Challenge (PLAsTiCC) is a community-wide challenge to spur development of algorithms to classify astronomical transients. The Large Synoptic Survey Telescope (LSST) will discover tens of thousands of transient phenomena every single night. To deal with this massive onset of data, automated algorithms to classify and sort astronomical transients are crucial.

PLAsTiCC, based on the highly successful Supernova Photometric Classification Challenge, will consist of a set of realistic LSST simulations of a variety of transient and variable phenomena. The challenge will be publicly available on a popular data science platform, encouraging algorithm submissions from outside the Astronomy community.


@article{Kessler_2019,
   title={Models and Simulations for the Photometric LSST Astronomical Time Series Classification Challenge (PLAsTiCC)},
   volume={131},
   ISSN={1538-3873},
   url={http://dx.doi.org/10.1088/1538-3873/ab26f1},
   DOI={10.1088/1538-3873/ab26f1},
   number={1003},
   journal={Publications of the Astronomical Society of the Pacific},
   publisher={IOP Publishing},
   author={Kessler, R. and Narayan, G. and Avelino, A. and Bachelet, E. and Biswas, R. and Brown, P. J. and Chernoff, D. F. and Connolly, A. J. and Dai, M. and Daniel, S. and Stefano, R. Di and Drout, M. R. and Galbany, L. and González-Gaitán, S. and Graham, M. L. and Hložek, R. and Ishida, E. E. O. and Guillochon, J. and Jha, S. W. and Jones, D. O. and Mandel, K. S. and Muthukrishna, D. and O’Grady, A. and Peters, C. M. and Pierel, J. R. and Ponder, K. A. and Prša, A. and Rodney, S. and Villar, V. A.},
   year={2019},
   month=jul, pages={094501} }