ZTF SN Ia DR2: Study of Type Ia supernova light-curve fits

Creators: Rigault, M. (Corresponding)¹; Smith, M.^{1, 2}; Regnault, N.³; Kenworthy, W. D.⁴; Maguire, K.⁵; Goobar, A.⁴; Dimitriadis, G.⁵; Johansson, J.⁴; Amenouche, M.⁶; Aubert, M.⁷; Barjou-Delayre, C.⁷; Bellm, E. C.⁸; Burgaz, U.⁵; Carreres, B.^{9, 10}; Copin, Y.¹; Deckers, M.⁵; de Jaeger, T.³; Dhawan, S.¹¹; Feinstein, F.⁹; Fouchez, D.⁹; Galbany, L.^{12, 13}; Ginolin, M.¹; Graham, M. J.¹⁴; Kim, Y.-L.²; Kowalski, M.^{15, 16}; Kuhn, D.³; Kulkarni, S. R.¹⁴; Müller-Bravo, T. E.^{12, 13}; Nordin, J.¹⁶; Popovic, B.¹; Purdum, J.¹⁴; Rosnet, P.⁷; Rosselli, D.⁹; Racine, B.⁹; Ruppin, F.¹; Sollerman, J.¹⁷; Terwel, J. H.⁵; Townsend, A.¹⁶

1. Claude Bernard University Lyon 1
2. Lancaster University
3. Laboratoire de Physique Nucléaire et de Hautes Énergies
4. AlbaNova
5. Trinity College Dublin
6. National Research Council Canada
7. University of Clermont Auvergne
8. University of Washington
9. Center for Particle Physics of Marseilles
10. Duke University
11. University of Cambridge
12. Institute of Space Sciences
13. Institut d'Estudis Espacials de Catalunya
14. California Institute of Technology
15. Deutsches Elektronen-Synchrotron DESY
16. Humboldt-Universität zu Berlin
17. Stockholm University

Abstract

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, Ω_M, Ω_Λ, 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.

Copyright and License

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.

Acknowledgement

Based on observations obtained with the Samuel Oschin Telescope 48-inch and the 60-inch Telescope at the Palomar Observatory as part of the Zwicky Transient Facility project. ZTF is supported by the National Science Foundation under Grants No. AST-1440341 and AST-2034437 and a collaboration including current partners Caltech, IPAC, the Weizmann Institute of Science, the Oskar Klein Center at Stockholm University, the University of Maryland, Deutsches Elektronen-Synchrotron and Humboldt University, the TANGO Consortium of Taiwan, the University of Wisconsin at Milwaukee, Trinity College Dublin, Lawrence Livermore National Laboratories, IN2P3, University of Warwick, Ruhr University Bochum, Northwestern University and former partners the University of Washington, Los Alamos National Laboratories, and Lawrence Berkeley National Laboratories. Operations are conducted by COO, IPAC, and UW. SED Machine is based upon work supported by the National Science Foundation under Grant No. 1106171 The ZTF forced-photometry service was funded under the Heising-Simons Foundation grant #12540303 (PI: Graham). This project has received funding from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation program (grant agreement n 759194 - USNAC). This project is supported by the H2020 European Research Council grant no. 758638. This work has been supported by the Agence Nationale de la Recherche of the French government through the program ANR-21-CE31-0016-03. L.G. acknowledges financial support from the Spanish Ministerio de Ciencia e Innovación (MCIN) and the Agencia Estatal de Investigación (AEI) 10.13039/501100011033 under the PID2020-115253GA-I00 HOSTFLOWS project, from Centro Superior de Investigaciones Científicas (CSIC) under the PIE project 20215AT016 and the program Unidad de Excelencia María de Maeztu CEX2020-001058-M, and from the Departament de Recerca i Universitats de la Generalitat de Catalunya through the 2021-SGR-01270 grant. Y.-L.K. has received funding from the Science and Technology Facilities Council [grant number ST/V000713/1]. This work has been enabled by support from the research project grant ‘Understanding the Dynamic Universe’ funded by the Knut and Alice Wallenberg Foundation under Dnr KAW 2018.0067. SD acknowledges support from the Marie Curie Individual Fellowship under grant ID 890695 and a Junior Research Fellowship at Lucy Cavendish College. We thank the Heising-Simons Foundation for supporting the research program of SRK.

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