Logo
ScienceStack
Table of Contents
Fetching ...
Sign In

Normal or transitional? The evolution and properties of two type Ia supernovae in the Virgo cluster

L. Izzo, C. Gall, N. Khetan, N. Earl, J. Hjorth, W. B. Hoogendam, Y. Q. Ni, A. Sedgewick, S. M. Ward, Y. Zenati, K. Auchettl, S. Bhattacharjee, S. Benetti, M. Branchesi, E. Cappellaro, A. Catapano, K. C. Chambers, D. A. Coulter, K. W. Davis, M. Della Valle, S. Dhawan, T. de Boer, G. Dimitriadis, R. J. Foley, M. Fulton, H. Gao, W. J. Hon, M. E. Huber, D. O. Jones, C. D. Kilpatrick, C. C. Lin, T. B. Lowe, E. A. Magnier, K. S. Mandel, R. Margutti, G. Narayan, P. Ochner, Y. C. Pan, A. Reguitti, C. Rojas-Bravo, M. Siebert, S. J. Smartt, K. W. Smith, S. Srivastav, J. J. Swift, K. Taggart, G. Terreran, S. Thorp, L. Tomasella, R. J. Wainscoat

TL;DR

The paper investigates two nearby SNe Ia in Virgo, SN 2020ue and SN 2020nlb, to understand photometric–spectroscopic diversity and its implications for cosmology. By combining dense multi-wavelength photometry, extensive spectroscopy, and advanced modeling (SNooPy, BayeSN, GP fits, Arnett-style Ni mass estimates, and TARDIS spectral synthesis), the authors demonstrate that SN 2020nlb is an intrinsically red but normal SN Ia, while SN 2020ue is photometrically transitional yet spectroscopically CN-like. They derive similar $^{56}$Ni masses for both ($\sim0.4\,M_{\odot}$) and find no host Na I D absorption, arguing for intrinsic color variations and a nuanced view of the transitional boundary. The results highlight the critical role of spectroscopy in constructing homogeneous SN Ia samples for precision cosmology and suggest that spectroscopic diagnostics can reveal underlying progenitor differences even when photometry alone places events near sub-class boundaries.

Abstract

Type Ia supernovae (SNe Ia) are among the most precise cosmological distance indicators used to study the expansion history of the Universe. The vast increase of SN Ia data due to large-scale astrophysical surveys has led to the discovery of a wide variety of SN Ia sub-classes, such as transitional and fast-declining SNe Ia. However, their distinct photometric and spectroscopic properties differentiate them from the population of normal SNe Ia such that their use as cosmological tools remains challenged. Here, we present a high-cadenced photometric and spectroscopic dataset of two SNe Ia, SNe 2020ue and 2020nlb, which were discovered in the nearby Virgo cluster of galaxies. Our study shows that SN 2020nlb is a normal SN Ia whose unusually red color is intrinsic, arising from a lower photospheric temperature rather than interstellar reddening, providing clear evidence that color diversity among normal SNe Ia can have a physical origin. In contrast, SN 2020ue has photometric properties, such as color evolution and light-curve decay rate, similar to those of transitional SNe, spectroscopically it is more aligned with normal SNe Ia. This is evident from spectroscopic indicators such as the pseudo-equivalent width of \ion{Si}{II} lines. Thus, such SNe Ia that are photometrically at the edge of the standard normal SNe Ia range may be missed in cosmological SNe Ia samples. Our results highlight that spectroscopic analysis of SNe Ia around peak brightness is crucial for identifying intrinsic color variations and constructing a more complete and physically homogeneous SN Ia sample for precision cosmology.

Normal or transitional? The evolution and properties of two type Ia supernovae in the Virgo cluster

TL;DR

The paper investigates two nearby SNe Ia in Virgo, SN 2020ue and SN 2020nlb, to understand photometric–spectroscopic diversity and its implications for cosmology. By combining dense multi-wavelength photometry, extensive spectroscopy, and advanced modeling (SNooPy, BayeSN, GP fits, Arnett-style Ni mass estimates, and TARDIS spectral synthesis), the authors demonstrate that SN 2020nlb is an intrinsically red but normal SN Ia, while SN 2020ue is photometrically transitional yet spectroscopically CN-like. They derive similar Ni masses for both () and find no host Na I D absorption, arguing for intrinsic color variations and a nuanced view of the transitional boundary. The results highlight the critical role of spectroscopy in constructing homogeneous SN Ia samples for precision cosmology and suggest that spectroscopic diagnostics can reveal underlying progenitor differences even when photometry alone places events near sub-class boundaries.

Abstract

Type Ia supernovae (SNe Ia) are among the most precise cosmological distance indicators used to study the expansion history of the Universe. The vast increase of SN Ia data due to large-scale astrophysical surveys has led to the discovery of a wide variety of SN Ia sub-classes, such as transitional and fast-declining SNe Ia. However, their distinct photometric and spectroscopic properties differentiate them from the population of normal SNe Ia such that their use as cosmological tools remains challenged. Here, we present a high-cadenced photometric and spectroscopic dataset of two SNe Ia, SNe 2020ue and 2020nlb, which were discovered in the nearby Virgo cluster of galaxies. Our study shows that SN 2020nlb is a normal SN Ia whose unusually red color is intrinsic, arising from a lower photospheric temperature rather than interstellar reddening, providing clear evidence that color diversity among normal SNe Ia can have a physical origin. In contrast, SN 2020ue has photometric properties, such as color evolution and light-curve decay rate, similar to those of transitional SNe, spectroscopically it is more aligned with normal SNe Ia. This is evident from spectroscopic indicators such as the pseudo-equivalent width of \ion{Si}{II} lines. Thus, such SNe Ia that are photometrically at the edge of the standard normal SNe Ia range may be missed in cosmological SNe Ia samples. Our results highlight that spectroscopic analysis of SNe Ia around peak brightness is crucial for identifying intrinsic color variations and constructing a more complete and physically homogeneous SN Ia sample for precision cosmology.

Paper Structure

This paper contains 21 sections, 21 figures, 8 tables.

Table of Contents

  1. Introduction
  2. Observations
  3. Discovery, classification and host galaxy
  4. Photometry
  5. Spectroscopy
  6. Photometric Analysis
  7. Peak brightness and intrinsic extinction
  8. Bolometric light curves
  9. SN explosion and rise-time to peak brightness
  10. The ejected mass of $^{56}$Ni
  11. Color evolution
  12. Spectral evolution
  13. Pseudo-equivalent widths
  14. Time-resolved analysis
  15. Spectral synthesis analysis
  16. ...and 6 more sections

Figures (21)

  • Figure 1: A trichromy image made using $BVr$ single filter images obtained with the Asiago Schmidt telescope a few days after the SN discoveries. The positions of SN 2020ue (left panel) and SN 2020nlb (right panel) in their respective host galaxies are marked using white indicators. Courtesy of Giovanni Benetti (DFA, University of Padova).
  • Figure 2: Light curve evolution of SN 2020ue (left panel) and SN 2020nlb (right panel). Data from different facilities are shown with different symbols, with colors corresponding to different filters: Swift-UVOT data are shown with diamond markers, Copernico-AFOSC and NOT-ALFOSC (for SN 2020ue) and Pan-STARRS (for SN 2020nlb) data with triangles, Swope and Thacher data with squares, LCO data with circles, OASDG data with plus markers. Both light curves have not been corrected for Galactic reddening.
  • Figure 3: Optical spectral series of SN 2020ue. Spectra were obtained with the Copernico 1.82m and Galileo 1.22m in Asiago, and the FLOYDS telescopes during the first 50 days of the SN evolution (left panel) and up to 390 days from the $B$-band maximum (right panel).
  • Figure 4: Optical spectral series of SN 2020nlb. Spectra were obtained with the NOT, the FLOYDS, and the KAST telescopes.
  • Figure 5: SNooPy fits (black curves) of Swift-UVOT and Pan-STARRS $gri$ data of SN 2020ue (left panel) and SN 2020nlb (right panel). The fits were obtained using the max-model light curve model function and the $s_{BV}$ stretch-color parameter.
  • ...and 16 more figures