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Published January 20, 2023 | Published
Journal Article Open

The Hydrogen-poor Superluminous Supernovae from the Zwicky Transient Facility Phase I Survey. II. Light-curve Modeling and Characterization of Undulations

Abstract

We present analysis of the light curves (LCs) of 77 hydrogen-poor superluminous supernovae (SLSNe I) discovered during the Zwicky Transient Facility Phase I operation. We find that the majority (67%) of the sample can be fit equally well by both magnetar and ejecta–circumstellar medium (CSM) interaction plus ⁵⁶Ni decay models. This implies that LCs alone cannot unambiguously constrain the physical power sources for an SLSN I. However, 23% of the sample show inverted V-shape, steep-declining LCs or features of long rise and fast post-peak decay, which are better described by the CSM+Ni model. The remaining 10% of the sample favors the magnetar model. Moreover, our analysis shows that the LC undulations are quite common, with a fraction of 18%–44% in our gold sample. Among those strongly undulating events, about 62% of them are found to be CSM-favored, implying that the undulations tend to occur in the CSM-favored events. Undulations show a wide range in energy and duration, with median values (and 1σ errors) being as 1.7%^(+1.5%)_(-0.7%) E_(rad,total) and 28.8^(+14.1)_(-9.1) days, respectively. Our analysis of the undulation timescales suggests that intrinsic temporal variations of the central engine can explain half of the undulating events, while CSM interaction (CSI) can account for the majority of the sample. Finally, all of the well-observed He-rich SLSNe Ib either have strongly undulating LCs or the LCs are much better fit by the CSM+Ni model. These observations imply that their progenitor stars have not had enough time to lose all of the He-envelopes before supernova explosions, and H-poor CSM are likely to present in these events.

Additional Information

© 2023. The Author(s). Published by the American Astronomical Society. Original content from this work may be used under the terms of the Creative Commons Attribution 4.0 licence. Any further distribution of this work must maintain attribution to the author(s) and the title of the work, journal citation and DOI. We thank Dr. Weili Lin from Tsinghua University for useful discussions of CSM modeling of SLSN I LCs. This work is 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 for Science, the Oskar Klein Center at Stockholm University, the University of Maryland, the University of Washington (UW), Deutsches ElektronenSynchrotron 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 Caltech Optical Observatories (COO), IPAC, and UW. The SED machine is based upon work supported by the National Science Foundation under grant No. 1106171. The ZTF forcedphotometry service was funded under the Heising-Simons Foundation grant No. 12540303 (PI: Graham). The Liverpool Telescope is operated on the island of La Palma by Liverpool John Moores University in the Spanish Observatorio del Roque de los Muchachos of the Instituto de Astrofisica de Canarias with financial support from the UK Science and Technology Facilities Council. The Nordic Optical Telescope is owned in collaboration by the University of Turku and Aarhus University, and operated jointly by Aarhus University, the University of Turku, and the University of Oslo, representing Denmark, Finland, and Norway, the University of Iceland and Stockholm University at the Observatorio del Roque de los Muchachos, La Palma, Spain, of the Instituto de Astrofisica de Canarias. This research has made use of data obtained through the High Energy Astrophysics Science Archive Research Center Online Service, provided by the NASA/Goddard Space Flight Center. This work was supported by the GROWTH project funded by the National Science Foundation under grant No. 1545949. Z.C. acknowledges support from the China Scholarship Council. T.K. acknowledges support from the Swedish National Space Agency and the Swedish Research Council. S.S. acknowledges support from the G.R.E.A.T research environment, funded by Vetenskapsrådet, the Swedish Research Council, project number 2016-06012. T.-W.C. acknowledges the EU Funding under Marie Skłodowska-Curie grant H2020-MSCA-IF-2018-842471. A.G.-Y. acknowledges support from the EU via the European Research Council grant No. 725161, the Israeli Science Foundation through the excellence center of the George Washington University, an IMOS space infrastructure grant and the Binational US-Israeli Scince Foundation/Transformative and the German-Israeli Science Foundation grants, as well as the André Deloro Institute for Advanced Research in Space and Optics, the Schwartz/Reisman Collaborative Science Program, and the Norman E Alexander Family M Foundation ULTRASAT Data Center Fund, Minerva, and Yeda-Sela. R.L. acknowledges support from a Marie Skłodowska-Curie Individual Fellowship within the Horizon 2020 European Union (EU) Framework Programme for Research and Innovation (H2020-MSCA-IF2017-794467). The work of X.W. is supported by the National Natural Science Foundation of China (NSFC grants 12033003 and 11633002), the Major State Basic Research Development Program (grant 2016YFA0400803), the Scholar Program of Beijing Academy of Science and Technology (DZ:BS202002), and the Tencent XPLORER Prize. Software: SESNspectraLib (Bianco et al. 2016), Scikit-learn (Pedregosa et al. 2011), MOSFiT (Guillochon et al. 2018), dynesty (Speagle 2020).

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Additional details

Created:
August 22, 2023
Modified:
October 25, 2023