ZTF SN Ia DR2: Simulations and volume-limited sample

Creators: Amenouche, M. (Corresponding)^{1, 2}; Rosnet, P. (Corresponding)²; Smith, M. (Corresponding)³; Rigault, M.⁴; Aubert, M.²; Barjou-Delayre, C.²; Burgaz, U.⁵; Carreres, B.^{6, 7}; Dimitriadis, G.⁵; Feinstein, F.⁶; Galbany, L.^{8, 9}; Ginolin, M.⁴; Goobar, A.¹⁰; Harvey, L.⁵; Johansson, J.¹⁰; Kim, Y.-L.³; Maguire, K.⁵; Müller-Bravo, T. E.^{8, 9}; Nordin, J.¹¹; Nugent, P.^{12, 13}; Racine, B.⁶; Rosselli, D.⁶; Regnault, N.¹⁴; Sollerman, J.¹⁰; Terwel, J. H.⁵; Townsend, A.¹¹; Groom, S. L.^{15, 16}; Kulkarni, S. R.¹⁵; Kasliwal, M.¹⁵; Laher, R. R.^{15, 16}; Purdum, J.¹⁵

1. National Research Council Canada
2. University of Clermont Auvergne
3. Lancaster University
4. Claude Bernard University Lyon 1
5. Trinity College Dublin
6. Center for Particle Physics of Marseilles
7. Duke University
8. Institute of Space Sciences
9. Institut d'Estudis Espacials de Catalunya
10. Stockholm University
11. Humboldt-Universität zu Berlin
12. Lawrence Berkeley National Laboratory
13. University of California, Berkeley
14. Laboratoire de Physique Nucléaire et de Hautes Énergies
15. California Institute of Technology
16. Infrared Processing and Analysis Center

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Abstract

Type Ia supernovae (SNe Ia) constitute a historical probe for deriving cosmological parameters through the fit of the Hubble-Lemaître diagram, that is, the SN Ia distance modulus versus their redshift. In the era of precision cosmology, realistic simulation of SNe Ia for any survey entering an Hubble-Lemaître diagram is a key tool for addressing observational systematics, such as the Malmquist bias. As the distance modulus of SNe Ia is derived from the fit of their light curves, a robust simulation framework is required. In this paper, we present the performances of the simulation framework skysurvey with the aim to reproduce the Zwicky Transient Facility (ZTF) SN Ia DR2, which covers the first phase of the ZTF and ran from March 2018 to December 2020. The ZTF SN Ia DR2 sample corresponds to almost 3000 classified SNe Ia of cosmological quality. We simulated individual light curves of the ZTF SN Ia DR2 sample to confirm the validity of the framework while taking the observing conditions and instrument performances into account. After the ZTF SN Ia DR2 selection criteria were applied, we found that the simulated fluxes and associated uncertainties agre well with the measured uncertainties when the sky-noise deduced from the observed science magnitude limits is corrected for by a factor 1.23 for the g band, 1.17 for the r band, and 1.20 for the i band. In addition, we accounted for an error floor of 2.5%, 3.5%, and 6% of the flux level in the g, r, and i bands, respectively. Furthermore a redshift dependence of the SALT2 light-curve parameters (stretch and colour) was conducted to deduce the redshift limit that defines a volume-limited sample, that is, an unbiased SNe Ia sample. We found that the ZTF SN Ia DR2 volume-limited sample is characterized by z ≤ 0.06. This volume-limited sample of about 1000 SNe Ia is unique, and an astrophysical analysis can be carried out based on it, or the standardisation procedure can be tested with unprecedented precision (these analyses are presented in companion papers).

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 Grant No. AST-1440341 and a collaboration including Caltech, IPAC, the Weizmann Institute of Science, the Oskar Klein Center at Stockholm University, the University of Maryland, the University of Washington, Deutsches Elektronen-Synchrotron and Humboldt University, Los Alamos National Laboratories, the TANGO Consortium of Taiwan, the University of Wisconsin at Milwaukee, and Lawrence Berkeley National Laboratories. Operations are conducted by COO, IPAC, and UW. The ZTF forced-photometry service was funded under the Heising-Simons Foundation grant #12540303 (PI: Graham). SED Machine is based upon work supported by the National Science Foundation under Grant No. 1106171 This work was supported by the GROWTH project (Kasliwal et al. 2019) funded by the National Science Foundation under Grant No 1545949. This project has received funding from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (grant agreement n 759194 – USNAC). P.R. acknowledges the support received from the Agence Nationale de la Recherche of the French government through the program ANR-21-CE31-0016-03. UB is supported by the H2020 European Research Council grant no. 758638 GD is supported by the H2020 European Research Council grant no. 758638 L.G. acknowledges financial support from AGAUR, CSIC, MCIN and AEI 10.13039/501100011033 under projects PID2020-115253GA-I00, PIE 20215AT016, CEX2020-001058-M, and 2021-SGR-01270. This work has been supported by the research project grant “Understanding the Dynamic Universe” funded by the Knut and Alice Wallenberg Foundation under Dnr KAW 2018.0067 and the Vetenskapsrådet, the Swedish Research Council, project 2020-03444 LH is funded by the Irish Research Council under grant number GOIPG/2020/1387 Y.-L.K. has received funding from the Science and Technology Facilities Council [grant number ST/V000713/1] KM is supported by the H2020 European Research Council grant no. 758638. T.E.M.B. 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, and from Centro Superior de Investigaciones Científicas (CSIC) under the PIE project 20215AT016 and the program Unidad de Excelencia María de Maeztu CEX2020-001058-M. JHT is supported by the H2020 European Research Council grant no. 758638.

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