Issue |
A&A
Volume 694, February 2025
ZTF SN Ia DR2
|
|
---|---|---|
Article Number | A2 | |
Number of page(s) | 10 | |
Section | Cosmology (including clusters of galaxies) | |
DOI | https://doi.org/10.1051/0004-6361/202450377 | |
Published online | 14 February 2025 |
ZTF SN Ia DR2: Study of Type Ia supernova light-curve fits
1
Université Claude Bernard Lyon 1, CNRS, IP2I Lyon / IN2P3, IMR 5822, F-69622 Villeurbanne, France
2
Department of Physics, Lancaster University, Lancs LA1 4YB, UK
3
Sorbonne Université, CNRS/IN2P3, LPNHE, F-75005 Paris, France
4
The Oskar Klein Centre, Department of Physics, AlbaNova, SE-106 91 Stockholm, Sweden
5
School of Physics, Trinity College Dublin, College Green, Dublin 2, Ireland
6
National Research Council of Canada, Herzberg Astronomy & Astrophysics Research Centre, 5071 West Saanich Road, Victoria, BC V9E 2E7, Canada
7
Université Clermont Auvergne, CNRS/IN2P3, LPCA, F-63000 Clermont-Ferrand, France
8
DIRAC Institute, Department of Astronomy, University of Washington, 3910 15th Avenue NE, Seattle, WA 98195, USA
9
Aix Marseille Université, CNRS/IN2P3, CPPM, Marseille, France
10
Department of Physics, Duke University, Durham, NC 27708, USA
11
Institute of Astronomy and Kavli Institute for Cosmology, University of Cambridge, Madingley Road, Cambridge CB3 0HA, UK
12
Institute of Space Sciences (ICE-CSIC), Campus UAB, Carrer de Can Magrans, s/n, E-08193 Barcelona, Spain
13
Institut d’Estudis Espacials de Catalunya (IEEC), 08860 Castelldefels (Barcelona), Spain
14
Division of Physics, Mathematics & Astronomy, California Institute of Technology, Pasadena, CA 91125, USA
15
Deutsches Elektronen-Synchrotron DESY, Platanenallee 6, 15738 Zeuthen, Germany
16
Institut für Physik, Humboldt-Universität zu Berlin, Newtonstr. 15, 12489 Berlin, Germany
17
Caltech Optical Observatories, California Institute of Technology, Pasadena, CA 91125, USA
18
The Oskar Klein Centre, Department of Astronomy, Stockholm University, AlbaNova, SE-106 91 Stockholm, Sweden
19
Nordic Optical Telescope, Rambla José Ana Fernández Pérez 7, ES-38711 Breña Baja, Spain
⋆ Corresponding author; m.rigault@ip2i.in2p3.fr
Received:
15
April
2024
Accepted:
5
September
2024
Type Ia supernova (SN Ia) cosmology relies on the estimation of light-curve parameters to derive precision distances, which are used to infer cosmological parameters such as H0, ΩM, ΩΛ, and w. The empirical SALT2 light-curve modeling that relies on only two parameters, a stretch x1 and a color c, has been used by the community for almost two decades. We study the ability of the SALT2 model to fit the nearly 3000 cosmology-grade SN Ia light curves from the second release of the Zwicky Transient Facility (ZTF) cosmology science working group. While the ZTF data were not used to train SALT2, the algorithm models the ZTF SN Ia optical light curves remarkably well, except for light-curve points prior to −10 d from maximum, where the training critically lacks data. We find that the light-curve fitting is robust against the considered choice of phase range, but we show that the [ − 10; +40] d range is optimal in terms of statistics and accuracy. We do not detect any significant features in the light-curve fit residuals that could be connected to the host environment. Potential systematic uncertainties associated tp population differences related to the SN Ia host properties might thus not be accountable for by the inclusion of addition of light-curve parameters. However, a small but significant inconsistency between residuals of blue and red SN Ia strongly suggests the existence of a phase-dependent color term, with potential implications for the use of SNe Ia in precision cosmology. We thus encourage further work in this area to explore this possibility, and we emphasize that SN Ia cosmology must include a SALT2 retraining to accurately model the light curves and avoid biasing the derivation of cosmological parameters.
Key words: supernovae: general / cosmology: observations / dark energy / distance scale
© The Authors 2025
Open Access article, published by EDP Sciences, under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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