Published February 2025 | Published
Journal Article Open

ZTF SN Ia DR2: Searching for late-time interaction signatures in Type Ia supernovae from the Zwicky Transient Facility

  • 1. ROR icon Trinity College Dublin
  • 2. ROR icon Isaac Newton Group
  • 3. ROR icon Lancaster University
  • 4. ROR icon University of Lyon System
  • 5. ROR icon Deutsches Elektronen-Synchrotron DESY
  • 6. ROR icon Humboldt-Universität zu Berlin
  • 7. ROR icon Laboratoire de Physique Nucléaire et de Hautes Énergies
  • 8. ROR icon Stockholm University
  • 9. ROR icon Institute of Space Sciences
  • 10. ROR icon Institut d'Estudis Espacials de Catalunya
  • 11. ROR icon California Institute of Technology
  • 12. ROR icon Infrared Processing and Analysis Center
  • 13. ROR icon European Southern Observatory
  • 14. ROR icon Millennium Institute of Astrophysics
  • 15. ROR icon National Central University
  • 16. ROR icon University of Southampton
  • 17. ROR icon University of Warsaw
  • 18. ROR icon Queen's University Belfast

Abstract

The nature of the progenitor systems and explosion mechanisms that give rise to Type Ia supernovae (SNe Ia) are still debated. The interaction signature of circumstellar material (CSM) being swept up by the expanding ejecta can constrain the type of system from which it was ejected. However, most previous studies have focussed on finding CSM ejected shortly before the SN Ia explosion, which still resides close to the explosion site resulting in short delay times until the interaction starts. We used a sample of 3628 SNe Ia from the Zwicky Transient Facility (ZTF) that were discovered between 2018 and 2020 and searched for interaction signatures greater than 100 days after peak brightness. By binning the late-time light curve data to push the detection limit as deep as possible, we identified potential late-time rebrightening in three SNe Ia (SN 2018grt, SN 2019dlf, and SN 2020tfc). The late-time optical detections occur between 550 and 1450 d after peak brightness, have mean absolute r-band magnitudes of −16.4 to −16.8 mag, and last up to a few hundred days, which is significantly brighter than the late-time CSM interaction discovered in the prototype, SN 2015cp. The late-time detections in the three objects all occur within 0.8 kpc of the host nucleus and are not easily explained by nuclear activity, another transient at a similar sky position, or data quality issues. This is suggestive of environment or specific progenitor characteristics playing a role in the production of potential CSM signatures in these SNe Ia. Through simulating the ZTF survey, we estimate that < 0.5% of normal SNe Ia display a late-time (> 100 d post peak) strong Hα-dominated CSM interaction. This is equivalent to an absolute rate of 8−4+20 to 54−26+91 Gpc−3 yr−1 assuming a constant SN Ia rate of 2.4 × 10−5 Mpc−3 yr−1 for z ≤ 0.1. Weaker interaction signatures of Hα emission, more similar to the strength seen in SN 2015cp, could be more common but are difficult to constrain with our survey depth.

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

JHT, KM and MD acknowledge support from EU H2020 ERC grant no. 758638. L.G. acknowledges financial support from the Spanish Ministerio de Ciencia e Innovación (MCIN), the Agencia Estatal de Investigación (AEI) 10.13039/501100011033, and the European Social Fund (ESF) “Investing in your future” under the 2019 Ramón y Cajal program RYC2019-027683-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. This work was funded by ANID, Millennium Science Initiative, ICN12_009. 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. MN is supported by the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (grant agreement No. 948381) and by UK Space Agency Grant No. ST/Y000692/1. Y.-L.K. has received funding from the Science and Technology Facilities Council [grant number ST/V000713/1]. TWC acknowledges the Yushan Young Fellow Program by the Ministry of Education, Taiwan for the financial support. 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. This work was supported by the GROWTH project (Kasliwal et al. 2019) funded by the National Science Foundation under Grant No 1545949. The Gordon and Betty Moore Foundation, through both the Data-Driven Investigator Program and a dedicated grant, provided critical funding for SkyPortal. The Legacy Surveys consist of three individual and complementary projects: the Dark Energy Camera Legacy Survey (DECaLS; Proposal ID #2014B-0404; PIs: David Schlegel and Arjun Dey), the Beijing-Arizona Sky Survey (BASS; NOAO Prop. ID #2015A-0801; PIs: Zhou Xu and Xiaohui Fan), and the Mayall z-band Legacy Survey (MzLS; Prop. ID #2016A-0453; PI: Arjun Dey). DECaLS, BASS and MzLS together include data obtained, respectively, at the Blanco telescope, Cerro Tololo Inter-American Observatory, NSF’s NOIRLab; the Bok telescope, Steward Observatory, University of Arizona; and the Mayall telescope, Kitt Peak National Observatory, NOIRLab. Pipeline processing and analyses of the data were supported by NOIRLab and the Lawrence Berkeley National Laboratory (LBNL). The Legacy Surveys project is honored to be permitted to conduct astronomical research on Iolkam Du’ag (Kitt Peak), a mountain with particular significance to the Tohono O’odham Nation. Funding for the SDSS and SDSS-II has been provided by the Alfred P. Sloan Foundation, the Participating Institutions, the National Science Foundation, the U.S. Department of Energy, the National Aeronautics and Space Administration, the Japanese Monbukagakusho, the Max Planck Society, and the Higher Education Funding Council for England. The SDSS Web Site is http://www.sdss.org/. The SDSS is managed by the Astrophysical Research Consortium for the Participating Institutions. The Participating Institutions are the American Museum of Natural History, Astrophysical Institute Potsdam, University of Basel, University of Cambridge, Case Western Reserve University, University of Chicago, Drexel University, Fermilab, the Institute for Advanced Study, the Japan Participation Group, Johns Hopkins University, the Joint Institute for Nuclear Astrophysics, the Kavli Institute for Particle Astrophysics and Cosmology, the Korean Scientist Group, the Chinese Academy of Sciences (LAMOST), Los Alamos National Laboratory, the Max-Planck-Institute for Astronomy (MPIA), the Max-Planck-Institute for Astrophysics (MPA), New Mexico State University, Ohio State University, University of Pittsburgh, University of Portsmouth, Princeton University, the United States Naval Observatory, and the University of Washington. Based on observations made with the Gran Telescopio Canarias (GTC), installed at the Spanish Observatorio del Roque de los Muchachos of the Instituto de Astrofísica de Canarias, on the island of La Palma. This work is (partly) based on data obtained with the instrument OSIRIS, built by a Consortium led by the Instituto de Astrofísica de Canarias in collaboration with the Instituto de Astronomía of the Universidad Autónoma de México. OSIRIS was funded by GRANTECAN and the National Plan of Astronomy and Astrophysics of the Spanish Government. The ztfquery code was funded by the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (grant agreement n°759194 – USNAC, PI: Rigault). This work made use of Astropy (http://www.astropy.org) a community-developed core Python package and an ecosystem of tools and resources for astronomy (Astropy Collaboration 201320182022). Many people have contributed to lmfit. The attribution of credit in a project such as this is difficult to get perfect, and there are no doubt important contributions that are missing or under-represented here. Please consider this file as part of the code and documentation that may have bugs that need fixing. Some of the largest and most important contributions (in approximate order of size of the contribution to the existing code) are from: Matthew Newville wrote the original version and maintains the project. Renee Otten wrote the brute force method, implemented the basin-hopping and AMPGO global solvers, implemented uncertainty calculations for scalar minimizers and has greatly improved the code, testing, and documentation and overall project. Till Stensitzki wrote the improved estimates of confidence intervals, and contributed many tests, bug fixes, and documentation. A. R. J. Nelson added differential_evolution, emcee, and greatly improved the code, docstrings, and overall project. Antonino Ingargiola wrote much of the high level Model code and has provided many bug fixes and improvements. Daniel B. Allan wrote much of the original version of the high level Model code, and many improvements to the testing and documentation. Austen Fox fixed many of the built-in model functions and improved the testing and documentation of these. Michal Rawlik added plotting capabilities for Models. The method used for placing bounds on parameters was derived from the clear description in the MINUIT documentation, and adapted from J. J. Helmus’s Python implementation in leastsqbounds.py. E. O. Le Bigot wrote the uncertainties package, a version of which was used by lmfit for many years, and is now an external dependency. The original AMPGO code came from Andrea Gavana and was adopted for lmfit. The propagation of parameter uncertainties to uncertainties in a Model was adapted from the excellent description at https://www.astro.rug.nl/software/kapteyn/kmpfittutorial.html#confidence-and-prediction-intervals, which references the original work of: J. Wolberg, Data Analysis Using the Method of Least Squares, 2006, Springer. Additional patches, bug fixes, and suggestions have come from Faustin Carter, Christoph Deil, Francois Boulogne, Thomas Caswell, Colin Brosseau, nmearl, Gustavo Pasquevich, Clemens Prescher, LiCode, Ben Gamari, Yoav Roam, Alexander Stark, Alexandre Beelen, Andrey Aristov, Nicholas Zobrist, Ethan Welty, Julius Zimmermann, Mark Dean, Arun Persaud, Ray Osborn, @lneuhaus, Marcel Stimberg, Yoshiera Huang, Leon Foks, Sebastian Weigand, Florian LB, Michael Hudson-Doyle, Ruben Verweij, @jedzill4, @spalato, Jens Hedegaard Nielsen, Martin Majli, Kristian Meyer, @azelcer, Ivan Usov, and many others. The lmfit code obviously depends on, and owes a very large debt to the code in scipy.optimize. Several discussions on the SciPy-user and lmfit mailing lists have also led to improvements in this code. Other software: numpy (Harris et al. 2020), pandas (The pandas development team 2020McKinney et al. 2010), matplotlib (Hunter 2007), sncosmo (Barbary et al. 2021), simsurvey (Feindt et al. 2019a).

Data Availability

The late-time spectrum of SN 2020alm is available at the CDS via anonymous ftp to cdsarc.cds.unistra.fr (130.79.128.5) or via https://cdsarc.cds.unistra.fr/viz-bin/cat/J/A+A/694/A11 The ZTF DR2 photometry is available on GitHub. The binning programme is available at https://github.com/JTerwel/late-timelcbinner. SNAP is available at https://github.com/JTerwel/SuperNova_Animation_Program. The ePESSTO+ photometry is available on the ESO archive.

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Additional details

Created:
February 24, 2025
Modified:
February 24, 2025