Type II supernovae from the Carnegie Supernova Project-I

II. Physical parameter distributions from hydrodynamical modelling

¹ Instituto de Astrofísica de La Plata (IALP), CCT-CONICET-UNLP, Paseo del Bosque s/n, B1900FWA La Plata, Argentina
e-mail: laureano@carina.fcaglp.unlp.edu.ar
² Facultad de Ciencias Astronómicas y Geofísicas, Universidad Nacional de La Plata, Paseo del Bosque s/n, B1900FWA La Plata, Argentina
³ Universidad Nacional de Río Negro, Sede Andina, Mitre 630, 8400 Bariloche, Argentina
⁴ Kavli Institute for the Physics and Mathematics of the Universe (WPI), The University of Tokyo, 5-1-5 Kashiwanoha, Kashiwa, Chiba 277-8583, Japan
⁵ European Southern Observatory, Alonso de Córdova 3107, Casilla 19, Santiago, Chile
⁶ Vice President and Head of Mission of AURA-O in Chile, Avda. Presidente Riesco 5335 Suite 507, Santiago, Chile
⁷ Hagler Institute for Advanced Studies, Texas A&M University, College Station, TX 77843, USA
⁸ CENTRA-Centro de Astrofísica e Gravitaçäo and Departamento de Física, Instituto Superio Técnico, Universidade de Lisboa, Avenida Rovisco Pais, 1049-001 Lisboa, Portugal
⁹ Data and Artificial Intelligence Initiative, Faculty of Physical and Mathematical Sciences, University of Chile, Chile
¹⁰ Centre for Mathematical Modelling, Faculty of Physical and Mathematical Sciences, University of Chile, Chile
¹¹ Millennium Institute of Astrophysics, Chile
¹² Department of Astronomy, Faculty of Physical and Mathematical Sciences, University of Chile, Chile
¹³ Consejo Nacional de Investigaciones Científicas y Tećnicas (CONICET), Argentina
¹⁴ Department of Physics and Astronomy, Aarhus University, Ny Munkegade 120, 8000 Aarhus C, Denmark
¹⁵ Carnegie Observatories, Las Campanas Observatory, Casilla 601, La Serena, Chile
¹⁶ Finnish Centre for Astronomy with ESO (FINCA), University of Turku, 20014 Turku, Finland
¹⁷ Tuorla Observatory, Department of Physics and Astronomy, University of Turku, 20014 Turku, Finland
¹⁸ Observatories of the Carnegie Institution for Science, 813 Santa Barbara St., Pasadena, CA 91101, USA
¹⁹ Institute for Astronomy, University of Hawaii, 2680 Woodlawn Drive, Honolulu, HI 96822, USA
²⁰ Department of Astronomy, University of California, 501 Campbell Hall, Berkeley, CA 94720-3411, USA
²¹ Institute of Space Sciences (ICE, CSIC), Campus UAB, Carrer de Can Magrans, s/n, 08193 Barcelona, Spain
²² Department of Physics, Florida State University, 77 Chieftan Way, Tallahassee, FL 32306, USA
²³ George P. and Cynthia Woods Mitchell Institute for Fundamental Physics and Astronomy, Department of Physics and Astronomy, Texas A&M University, College Station, TX 77843, USA

Received: 23 August 2021
Accepted: 13 December 2021

Abstract

Linking supernovae to their progenitors is a powerful method for furthering our understanding of the physical origin of their observed differences while at the same time testing stellar evolution theory. In this second study of a series of three papers where we characterise type II supernovae (SNe II) to understand their diversity, we derive progenitor properties (initial and ejecta masses and radius), explosion energy, and ⁵⁶Ni mass and its degree of mixing within the ejecta for a large sample of SNe II. This dataset was obtained by the Carnegie Supernova Project-I and is characterised by a high cadence of SNe II optical and near-infrared light curves and optical spectra that were homogeneously observed and processed. A large grid of hydrodynamical models and a fitting procedure based on Markov chain Monte Carlo methods were used to fit the bolometric light curve and the evolution of the photospheric velocity of 53 SNe II. We infer ejecta masses of between 7.9 and 14.8 M_⊙, explosion energies between 0.15 and 1.40 foe, and ⁵⁶Ni masses between 0.006 and 0.069 M_⊙. We define a subset of 24 SNe (the ‘gold sample’) with well-sampled bolometric light curves and expansion velocities for which we consider the results more robust. Most SNe II in the gold sample (∼88%) are found with ejecta masses in the range of ∼8−10 M_⊙, coming from low zero-age main-sequence masses (9−12 M_⊙). The modelling of the initial-mass distribution of the gold sample gives an upper mass limit of 21.3${}_{-0.4}^{+3.8}$ M_⊙ and a much steeper distribution than that for a Salpeter massive-star initial mass function (IMF). This IMF incompatibility is due to the large number of low-mass progenitors found – when assuming standard stellar evolution. This may imply that high-mass progenitors lose more mass during their lives than predicted. However, a deeper analysis of all stellar evolution assumptions is required to test this hypothesis.