Photometric classification and redshift estimation of LSST Supernovae-Reference-Cited by-同舟云学术

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Photometric classification and redshift estimation of LSST Supernovae

Published:2018-04-19 Issue:3 Volume:477 Page:4142-4151
ISSN:0035-8711
Container-title:Monthly Notices of the Royal Astronomical Society
language:en
Short-container-title:

Author:

Dai Mi¹^ORCID,Kuhlmann Steve²,Wang Yun³,Kovacs Eve²

Affiliation:

1. Department of Physics & Astronomy, Rutgers, The State University of New Jersey, 136 Frelinghuysen Rd, Piscataway, NJ 08854, USA

2. Argonne National Laboratory, 9700 South Cass Avenue, Lemont, IL 60439, USA

3. IPAC, California Institute of Technology, Mail Code 314-6, 1200 East California Boulevard, Pasadena, CA 91125, USA

Publisher

Oxford University Press (OUP)

Subject

Space and Planetary Science,Astronomy and Astrophysics

Link

http://academic.oup.com/mnras/article-pdf/477/3/4142/24816725/sty965.pdf

Reference25 articles.

1. The core-collapse rate from the Supernova Legacy Survey

2. Photometric selection of Type Ia supernovae in the Supernova Legacy Survey

3. SUPERNOVA SIMULATIONS AND STRATEGIES FOR THE DARK ENERGY SURVEY

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1. Forecasting supernova observations with the CSST: I. Photometric samples;Science China Physics, Mechanics & Astronomy;2024-09-03

2. Multiview Symbolic Regression;Proceedings of the Genetic and Evolutionary Computation Conference;2024-07-14

3. Photo-zSNthesis: Converting Type Ia Supernova Lightcurves to Redshift Estimates via Deep Learning;The Astrophysical Journal;2023-09-01

4. Using Host Galaxy Photometric Redshifts to Improve Cosmological Constraints with Type Ia Supernovae in the LSST Era;The Astrophysical Journal;2023-02-01

5. Concerning colour: The effect of environment on type Ia supernova colour in the dark energy survey;Monthly Notices of the Royal Astronomical Society;2022-12-19

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