publication . Article . Preprint . Research . Other literature type . 2019

The Photometric LSST Astronomical Time-series Classification Challenge PLAsTiCC : Selection of a Performance Metric for Classification Probabilities Balancing Diverse Science Goals

Malz, Alex; Hložek, Renée; Allam, Tarek; Bahmanyar, Anita; Biswas, Rahul; Dai, Mi; Galbany, Lluís; Ishida, Emille; Jha, Saurabh; Jones, David; ...
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Open Access English
  • Published: 01 Jan 2019
  • Publisher: HAL CCSD
Abstract
International audience; Classification of transient and variable light curves is an essential step in using astronomical observations to develop an understanding of the underlying physical processes from which they arise. However, upcoming deep photometric surveys, including the Large Synoptic Survey Telescope (LSST), will produce a deluge of low signal-to-noise data for which traditional type estimation procedures are inappropriate. Probabilistic classification is more appropriate for such data but is incompatible with the traditional metrics used on deterministic classifications. Furthermore, large survey collaborations like LSST intend to use the resulting cl...
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doi: 10.3847/1538-3881/ab3a2f , 10.17863/cam.45849
Subjects
free text keywords: [PHYS.PHYS.PHYS-INS-DET]Physics [physics]/Physics [physics]/Instrumentation and Detectors [physics.ins-det], [PHYS.ASTR]Physics [physics]/Astrophysics [astro-ph], [ PHYS.PHYS.PHYS-INS-DET ] Physics [physics]/Physics [physics]/Instrumentation and Detectors [physics.ins-det], [ PHYS.ASTR ] Physics [physics]/Astrophysics [astro-ph], data analysis [methods], statistical [methods], variables: general [stars], general [supernovae], surveys, photometric [techniques], Astrophysics - Instrumentation and Methods for Astrophysics, Astrophysics - Cosmology and Nongalactic Astrophysics, Astrophysics - Solar and Stellar Astrophysics, Space and Planetary Science, Astronomy and Astrophysics, methods: data analysis, methods: statistical, stars: variables: general, supernovae: general, techniques: photometric, Time series classification, Methods statistical, Photometry (optics), Light curve, Performance metric, Sextant (astronomical), law.invention, law, Data mining, computer.software_genre, computer, Physics
Related Organizations
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Funded by
EC| SNDTD
Project
SNDTD
Resolving the origins of supernovae: constraining progenitors with integral field spectroscopy
  • Funder: European Commission (EC)
  • Project Code: 839090
  • Funding stream: H2020 | MSCA-IF-EF-ST
, EC| COSMICDAWN
Project
COSMICDAWN
Understanding the Origin of Cosmic Structure
  • Funder: European Commission (EC)
  • Project Code: 306478
  • Funding stream: FP7 | SP2 | ERC
, NSF| Open Exploration of the Time Domain with the Catalina Real-Time Transient Survey
Project
Open Exploration of the Time Domain with the Catalina Real-Time Transient Survey
  • Funder: National Science Foundation (NSF)
  • Project Code: 1313422
  • Funding stream: Directorate for Mathematical & Physical Sciences | Division of Astronomical Sciences
, NSF| Collaborative Research: New Insights from a Systematic Approach to Quasar Variability
Project
Collaborative Research: New Insights from a Systematic Approach to Quasar Variability
  • Funder: National Science Foundation (NSF)
  • Project Code: 1518308
, NSF| The Catalina Real-Time Transient Survey (CRTS)
Project
The Catalina Real-Time Transient Survey (CRTS)
  • Funder: National Science Foundation (NSF)
  • Project Code: 0909182
  • Funding stream: Directorate for Mathematical & Physical Sciences | Division of Astronomical Sciences
View more
Download fromView all 16 versions
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Preprint . 2018
Provider: arXiv.org e-Print Archive
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Article . 2019
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59 references, page 1 of 4

Abraham, S., Aniyan, A. K., Kembhavi, A. K., Philip, N. S., & Vaghmare, K. 2018, MNRAS, 477, 894

Armstrong, D. J., Kirk, J., Lam, K. W. F., et al. 2016, MNRAS, 456, 2260

Bell Burnell, J. 1969, PhD Thesis, Department of Radio Astronomy, Univ. Cambridge, Cambridge doi:10.17863/CAM.4926

Bethapudi, S., & Desai, S. 2018, A&C, 23, 15

Bloom, J. S., Richards, J. W., Nugent, P. E., et al. 2012, PASP, 124, 1175

Brier, G. W. 1950, MWRv, 78, 1

Buitinck, L., Louppe, G., londel, M., et al. 2013, arXiv:1309.0238

Cabrera-Vives, G., Reyes, I., Förster, F., Estévez, P. A., & Maureira, J.-C. 2017, ApJ, 836, 97

Conley, A., Sullivan, M., Hsiao, E. Y., et al. 2008, ApJ, 681, 482

Crown, M. D. 2012, SpWea, 10, S06006

Dieleman, S., Willett, K. W., & Dambre, J. 2015, MNRAS, 450, 1441

Djorgovski, S. G., Donalek, C., Mahabal, A., et al. 2011, arXiv:1110.4655

Djorgovski, S. G., Mahabal, A. A., Donalek, C., et al. 2010, in Proc. 2011 Conf. Intelligent Data Understanding (CIDU 2011), ed. A. N. Srivastava, N. V. Chawla, & A. S. Perera (Washington, DC: NASA), 174

Florios, K., Kontogiannis, I., Park, S.-H., et al. 2018, SoPh, 293, 28

George, D., Shen, H., & Huerta, E. A. 2018, PhRvD, 97, 101501

59 references, page 1 of 4
Related research
Abstract
International audience; Classification of transient and variable light curves is an essential step in using astronomical observations to develop an understanding of the underlying physical processes from which they arise. However, upcoming deep photometric surveys, including the Large Synoptic Survey Telescope (LSST), will produce a deluge of low signal-to-noise data for which traditional type estimation procedures are inappropriate. Probabilistic classification is more appropriate for such data but is incompatible with the traditional metrics used on deterministic classifications. Furthermore, large survey collaborations like LSST intend to use the resulting cl...
Read more
doi: 10.3847/1538-3881/ab3a2f , 10.17863/cam.45849
Subjects
free text keywords: [PHYS.PHYS.PHYS-INS-DET]Physics [physics]/Physics [physics]/Instrumentation and Detectors [physics.ins-det], [PHYS.ASTR]Physics [physics]/Astrophysics [astro-ph], [ PHYS.PHYS.PHYS-INS-DET ] Physics [physics]/Physics [physics]/Instrumentation and Detectors [physics.ins-det], [ PHYS.ASTR ] Physics [physics]/Astrophysics [astro-ph], data analysis [methods], statistical [methods], variables: general [stars], general [supernovae], surveys, photometric [techniques], Astrophysics - Instrumentation and Methods for Astrophysics, Astrophysics - Cosmology and Nongalactic Astrophysics, Astrophysics - Solar and Stellar Astrophysics, Space and Planetary Science, Astronomy and Astrophysics, methods: data analysis, methods: statistical, stars: variables: general, supernovae: general, techniques: photometric, Time series classification, Methods statistical, Photometry (optics), Light curve, Performance metric, Sextant (astronomical), law.invention, law, Data mining, computer.software_genre, computer, Physics
Related Organizations
View more
Funded by
EC| SNDTD
Project
SNDTD
Resolving the origins of supernovae: constraining progenitors with integral field spectroscopy
  • Funder: European Commission (EC)
  • Project Code: 839090
  • Funding stream: H2020 | MSCA-IF-EF-ST
, EC| COSMICDAWN
Project
COSMICDAWN
Understanding the Origin of Cosmic Structure
  • Funder: European Commission (EC)
  • Project Code: 306478
  • Funding stream: FP7 | SP2 | ERC
, NSF| Open Exploration of the Time Domain with the Catalina Real-Time Transient Survey
Project
Open Exploration of the Time Domain with the Catalina Real-Time Transient Survey
  • Funder: National Science Foundation (NSF)
  • Project Code: 1313422
  • Funding stream: Directorate for Mathematical & Physical Sciences | Division of Astronomical Sciences
, NSF| Collaborative Research: New Insights from a Systematic Approach to Quasar Variability
Project
Collaborative Research: New Insights from a Systematic Approach to Quasar Variability
  • Funder: National Science Foundation (NSF)
  • Project Code: 1518308
, NSF| The Catalina Real-Time Transient Survey (CRTS)
Project
The Catalina Real-Time Transient Survey (CRTS)
  • Funder: National Science Foundation (NSF)
  • Project Code: 0909182
  • Funding stream: Directorate for Mathematical & Physical Sciences | Division of Astronomical Sciences
View more
Download fromView all 16 versions
Hyper Article en Ligne
Article . 2019
Provider: Hyper Article en Ligne
HAL-Inserm
Article . 2019
Provider: HAL-Inserm
arXiv.org e-Print Archive
Preprint . 2018
Provider: arXiv.org e-Print Archive
Hal-Diderot
Article . 2019
Provider: Hal-Diderot
View more
59 references, page 1 of 4

Abraham, S., Aniyan, A. K., Kembhavi, A. K., Philip, N. S., & Vaghmare, K. 2018, MNRAS, 477, 894

Armstrong, D. J., Kirk, J., Lam, K. W. F., et al. 2016, MNRAS, 456, 2260

Bell Burnell, J. 1969, PhD Thesis, Department of Radio Astronomy, Univ. Cambridge, Cambridge doi:10.17863/CAM.4926

Bethapudi, S., & Desai, S. 2018, A&C, 23, 15

Bloom, J. S., Richards, J. W., Nugent, P. E., et al. 2012, PASP, 124, 1175

Brier, G. W. 1950, MWRv, 78, 1

Buitinck, L., Louppe, G., londel, M., et al. 2013, arXiv:1309.0238

Cabrera-Vives, G., Reyes, I., Förster, F., Estévez, P. A., & Maureira, J.-C. 2017, ApJ, 836, 97

Conley, A., Sullivan, M., Hsiao, E. Y., et al. 2008, ApJ, 681, 482

Crown, M. D. 2012, SpWea, 10, S06006

Dieleman, S., Willett, K. W., & Dambre, J. 2015, MNRAS, 450, 1441

Djorgovski, S. G., Donalek, C., Mahabal, A., et al. 2011, arXiv:1110.4655

Djorgovski, S. G., Mahabal, A. A., Donalek, C., et al. 2010, in Proc. 2011 Conf. Intelligent Data Understanding (CIDU 2011), ed. A. N. Srivastava, N. V. Chawla, & A. S. Perera (Washington, DC: NASA), 174

Florios, K., Kontogiannis, I., Park, S.-H., et al. 2018, SoPh, 293, 28

George, D., Shen, H., & Huerta, E. A. 2018, PhRvD, 97, 101501

59 references, page 1 of 4
Related research
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