Spectrophotometric templates for core collapse supernovae and their application in simulations of time-domain surveys

M. Vincenzi*, M. Sullivan, R. E. Firth, C. P. Gutiérrez, C. Frohmaier, M. Smith, C. Angus, R. C. Nichol

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

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The design and analysis of time-domain sky surveys requires the ability to simulate accurately realistic populations of core collapse supernova (SN) events. We present a set of spectral time-series templates designed for this purpose, for both hydrogen-rich (type II, IIn, IIb) and stripped envelope (types Ib, Ic, Ic-BL) core collapse supernovae. We use photometric and spectroscopic data for 67 core collapse supernovae from the literature, and for each generate a time-series spectral template. The techniques used to build the templates are fully data-driven with no assumption of any parametric form or model for the light curves. The template-building code is open-source, and can be applied to any transient for which well-sampled multi-band photometry and multiple spectroscopic observations are available. We extend these spectral templates into the near-ultraviolet to λ ≃ 1600Å using observer-frame ultraviolet photometry. We also provide a set of templates corrected for host galaxy dust extinction, and provide a set of luminosity functions that can be used with our spectral templates in simulations. We give an example of how these templates can be used by integrating them within the popular SNANA, and simulating core collapse supernovae in photometrically-selected cosmological type Ia supernova samples, prone to contamination from core collapse events.
Original languageEnglish
Pages (from-to)5802-5821
Number of pages20
JournalMonthly Notices of the Royal Astronomical Society
Issue number4
Early online date20 Sept 2019
Publication statusPublished - 1 Nov 2019


  • astro-ph.HE
  • supernovae: general
  • methods: statistical
  • methods: data analysis
  • RCUK
  • STFC
  • ST/P006760/1
  • ST/N002504/1


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