PISCOLA: a data-driven transient light-curve fitter. Issue 3 (22nd October 2021)

• Record Type: Journal Article
• Authors: Müller-Bravo, Tomás E; Sullivan, Mark; Smith, Mathew; Frohmaier, Chris; Gutiérrez, Claudia P; Wiseman, Philip; Zontou, Zoe
• Is Part Of: Monthly notices of the Royal Astronomical Society. Volume 512:Issue 3(2022)
• Page Start: 3266
• Page End: 3283
• Publication Date: 2021-10-22
• Subjects: supernovae: general -- cosmology: observations -- distance scale; Astronomy -- Periodicals; Periodicals; 520.5
• DOI: 10.1093/mnras/stab3065
• Languages: English
• ISSNs: 0035-8711

Abstract

ABSTRACT: 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.