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Published May 2025 | Version Published
Journal Article Open

ZTF SN Ia DR2: Improved SN Ia colors through expanded dimensionality with SALT3+

Creators

  • 1. ROR icon Stockholm University
  • 2. Institute for Astronomy, University of Hawai'i, 640 N. Aohoku Pl., Hilo, HI, 96720, USA
  • 3. ROR icon University of Chicago
  • 4. ROR icon Trinity College Dublin
  • 5. ROR icon University of Cambridge
  • 6. ROR icon Institute of Space Sciences
  • 7. ROR icon Institut d'Estudis Espacials de Catalunya
  • 8. ROR icon Claude Bernard University Lyon 1
  • 9. ROR icon Lancaster University
  • 10. ROR icon Lawrence Berkeley National Laboratory
  • 11. ROR icon University of California, Berkeley
  • 12. ROR icon Humboldt-Universität zu Berlin
  • 13. ROR icon University of Clermont Auvergne
  • 14. ROR icon California Institute of Technology
  • 15. ROR icon Center for Particle Physics of Marseilles

Abstract

Context. Type Ia supernovae (SNe Ia) are a key probe in modern cosmology, as they can be used to measure luminosity distances at gigaparsec scales. Models of their light curves are used to project heterogeneous observed data onto a common basis for analysis.

Aims. The SALT model currently used for SN Ia cosmology describes SNe as having two sources of variability, accounted for by a color parameter c, and a “stretch” parameter x1. We extend the model to include an additional parameter we label x2, to investigate the cosmological impact of currently unaddressed light-curve variability.

Methods. We constructed a new SALT model, that we dub “SALT3+”. This model was trained by an improved version of the SALTshaker code, using training data combining a selection of the second data release of cosmological SNe Ia from the Zwicky Transient Facility and the existing SALT3 training compilation.

Results. We find additional, coherent variability in supernova light curves beyond SALT3. Most of this variation can be described as phase-dependent variation in g − r and r − i color curves, correlated with a boost in the height of the secondary maximum in i-band. These behaviors correlate with spectral differences, particularly in line velocity. We find that fits with the existing SALT3 model tend to address this excess variation with the color parameter, leading to less informative measurements of supernova color. We find that neglecting the new parameter in light-curve fits leads to a trend in Hubble residuals with x2 of 0.039 ± 0.005 mag, representing a potential systematic uncertainty. However, we find no evidence of a bias in current cosmological measurements.

Conclusions. We conclude that extended SN Ia light-curve models promise mild improvement in the accuracy of color measurements, and corresponding cosmological precision. However, models with more parameters are unlikely to substantially affect current cosmological results.

Copyright and License

© 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.

Acknowledgement

The authors thank Daniel Kasen for useful discussion. 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. SED Machine is based upon work supported by the National Science Foundation under Grant No. 1106171 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. AG acknowledges support from the Swedish Research Council, project 2020-03444. ST was supported by funding from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programmes (grant agreement no. 101018897 CosmicExplorer). T.E.M.B. acknowledges financial support from the Spanish Ministerio de Ciencia e Innovación (MCIN), the Agencia Estatal de Investigación (AEI) 10.13039/501100011033, and the European Union Next Generation EU/PRTR funds under the 2021 Juan de la Cierva program FJC2021-047124-I and 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. JHT 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. UB is supported by the H2020 European Research Council grant no. 758638 We acknowledge the University of Chicago’s Research Computing Center for their support of this work. 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). GD is supported by the H2020 European Research Council grant no. 758638. 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). KM is supported by the H2020 European Research Council grant no. 758638. PN acknowledges support from the DOE under grant DE-AC02-05CH11231, Analytical Modeling for Extreme-Scale Computing Environments. Y.-L.K. has received funding from the Science and Technology Facilities Council [grant number ST/V000713/1].

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Additional details

Funding

National Science Foundation
AST-1440341
National Science Foundation
1106171
Knut and Alice Wallenberg Foundation
KAW 2018.0067
European Research Council
101018897
Ministerio de Ciencia, Innovación y Universidades
10.13039/501100011033
European Union Next Generation
FJC2021-047124-I
European Union Next Generation
PID2020-115253GA-I00
Centro Superior de Investigaciones Cientificas
20215AT016
Centro Superior de Investigaciones Cientificas
CEX2020-001058-M
European Research Council
758638
Research Computing Center, University of Chicago
European Research Council
759194
United States Department of Energy
DE-AC02-05CH11231
Science and Technology Facilities Council
ST/V000713/1

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Caltech groups
Infrared Processing and Analysis Center (IPAC)
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Published