open access publication

Article, 2024

Type Ia Supernova Progenitor Properties and their Host Galaxies

The Astrophysical Journal, ISSN 0004-637X, 1538-4357, Volume 969, 2, Page 80, 10.3847/1538-4357/ad4702

Contributors

Chakraborty, Sudeshna 0000-0003-2183-148X (Corresponding author) [1] Sadler, Benjamin [2] Hoeflich, Peter 0000-0002-4338-6586 [1] Hsiao, Eric Y 0000-0003-1039-2928 [1] Phillips, Mark M 0000-0003-2734-0796 [3] Burns, C. R. [4] Diamond, Tiara R 0000-0002-0805-1908 [1] Dominguez, I. [5] Galbany, Lluís 0000-0002-1296-6887 [6] [7] Uddin, Syed Ashraf 0000-0002-9413-4186 [8] Ashall, C. [9] Krisciunas, Kevin L 0000-0002-6650-694X [10] Kumar, Sahana 0000-0001-8367-7591 [1] Mera, Tyco Brahe [1] Morrell, Nidia Irene 0000-0003-2535-3091 [3] Baron, E. [11] [12] [13] Contreras, Carlos 0000-0001-6293-9062 [3] Stritzinger, Maximilian David 0000-0002-5571-1833 [14] Suntzeff, Nicholas B 0000-0002-8102-181X [10]

Affiliations

  1. [1] Florida State University
  2. [NORA names: United States; America, North; OECD];
  3. [2] Western Governors University
  4. [NORA names: United States; America, North; OECD];
  5. [3] Las Campanas Observatory
  6. [NORA names: Chile; America, South; OECD];
  7. [4] Carnegie Mellon University
  8. [NORA names: United States; America, North; OECD];
  9. [5] University of Granada
  10. [NORA names: Spain; Europe, EU; OECD];

Abstract

We present an eigenfunction method to analyze 161 visual light curves (LCs) of Type Ia supernovae (SNe Ia) obtained by the Carnegie Supernova Project to characterize their diversity and host-galaxy correlations. The eigenfunctions are based on the delayed-detonation (DD) scenario using three parameters: the LC stretch s determined by the amount of deflagration burning governing the 56Ni production, the main-sequence mass M MS of the progenitor white dwarf controlling the explosion energy, and its central density ρ c shifting the 56Ni distribution. Our analysis tool (Supernova Parameter Analysis Tool) extracts the parameters from observations and projects them into physical space using their allowed ranges (M MS ≤ 8 M ⊙, ρ c ≤ 7–8 × 109 g cm−3). The residuals between fits and individual LC points are ≈1%–3% for ≈92% of objects. We find two distinct M MS groups corresponding to a fast (≈4–65 Myr) and a slow(≈200–500 Myr) stellar evolution. Most underluminous SNe Ia have hosts with low star formation but high M MS, suggesting slow evolution times of the progenitor system. 91T-like SNe show very similar LCs and high M MS and are correlated to star formation regions, making them potentially important tracers of star formation in the early Universe out to z ≈ 4–11. Some ∼6% outliers with nonphysical parameters using DD scenarios can be attributed to superluminous SNe Ia and subluminous SNe Ia with hosts of active star formation. For deciphering the SNe Ia diversity and high-precision SNe Ia cosmology, the importance is shown for LCs covering out to ≈60 days past maximum. Finally, our method and results are discussed within the framework of multiple explosion scenarios, and in light of upcoming surveys.

Keywords

Carnegie, Carnegie Supernova Project, DD scenario, Ia supernovae, Myr, R c, SNe, SNe Ia, Supernova Project, Type Ia supernovae, University, active star formation, amount, analysis, analysis tools, correlation, cosmology, curves, days past maximum, deflagration, distribution, diversity, dwarf, early universe, eigenfunction method, eigenfunctions, energy, evolution, evolution time, explosion, explosion energy, explosion scenarios, formation, formation region, framework, group, host, light curves, low star formation, m-MS, maximum, method, nonphysical parameters, objective, observations, outliers, parameters, physical space, point, production, progenitor system, progenitor white dwarf, progenitors, project, range, region, residues, results, scenarios, space, star formation, star formation regions, stellar evolution, stretch s, supernova, survey, system, time, tools, tracer, tracers of star formation, type, visual light curve, white dwarfs

Funders

  • Ministry of Economy, Industry and Competitiveness
  • Directorate for Mathematical & Physical Sciences

Data Provider: Digital Science