2022MNRAS.512.3266M -
Mon. Not. R. Astron. Soc., 512, 3266-3283 (2022/May-3)
PISCOLA: a data-driven transient light-curve fitter.
MULLER-BRAVO T.E., SULLIVAN M., SMITH M., FROHMAIER C., GUTIERREZ C.P., WISEMAN P. and ZONTOU Z.
Abstract (from CDS):
Forthcoming time-domain surveys, such as the Rubin Observatory Legacy Survey of Space and Time, will vastly increase samples of supernovae (SNe) and other optical transients, requiring new data-driven techniques to analyse their photometric light curves. Here, we present the 'Python for Intelligent Supernova-COsmology Light-curve Analysis' (PISCOLA ), an open source data-driven light-curve fitter using Gaussian Processes that can estimate rest-frame light curves of transients without the need for an underlying light-curve template. We test PISCOLA on large-scale simulations of type Ia SNe (SNe Ia) to validate its performance, and show it successfully retrieves rest-frame peak magnitudes for average survey cadences of up to 7 d. We also compare to the existing SN Ia light-curve fitter SALT2 on real data, and find only small (but significant) disagreements for different light-curve parameters. As a proof-of-concept of an application of PISCOLA, we decomposed and analysed the PISCOLA rest-frame light curves of SNe Ia from the Pantheon SN Ia sample with Non-Negative Matrix Factorization. Our new parametrization provides a similar performance to existing light-curve fitters such as SALT2. We further derived a SN Ia colour law from PISCOLA fits over ∼3500-7000 Å, and find agreement with the SALT2 colour law and with reddening laws with total-to-selective extinction ratio RV <= 3.1.
Abstract Copyright:
© 2021 The Author(s) Published by Oxford University Press on behalf of Royal Astronomical Society
Journal keyword(s):
supernovae: general - cosmology: observations - distance scale
Simbad objects:
4
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