Lightcurve Modelling of 2,205 ZTF DR2 Type~Ia Supernovae: Implications for SN Ia Physics and Cosmology

Abstract

We fit the multi-band light curves of 2,205 Type Ia supernovae (SNe~Ia) from the Zwicky Transient Facility DR2 with a one-zone radioactive decay model with a phenomenological addition to include Fe recombination physics. We find a strong correlation between inferred nickel mass and SALT2 stretch, which within our simplified modelling is linked to larger ejecta masses providing longer diffusion times, providing a physical basis for the brighter-slower relation. SN~Ia in low-mass hosts ($\log_{10}(M_*/M_\odot) < 10$) produce $12\%$ more $^{56}$Ni than those in high-mass hosts ($ΔM_{\rm Ni} = 0.13~M_\odot$), linking the host-galaxy mass step to ejecta properties and hinting at metallicity or age-dependent burning efficiencies. This suggests that standardisation based on physical parameters may remove the mass-step. SN~1991T-like events show higher ejecta masses (median $1.64~M_\odot$ vs. $1.38~M_\odot$ for normals) and produce $30\%$ more $^{56}$Ni, with $84\%$ having super-Chandrasekhar masses. Through Hierarchical modelling of $902$ SNe ($z \leq 0.06$), we find thermonuclear supernovae can be well described by a Gaussian distribution in ejecta mass and nickel mass with $μ_{\rm ej} = 1.26 \pm 0.01~M_\odot$ ($σ_{\rm ej} = 0.33 \pm 0.01~M_\odot$) and $μ_{\rm Ni} = 0.64 \pm 0.06~M_\odot$ ($σ_{\rm Ni} = 0.42 \pm 0.02~M_\odot$), respectively. This leads to inferred fractions of $43 \pm 2\%$ sub-$M_{\rm Ch}$ ($<1.2~M_\odot$), $34 \pm 1\%$ near-$M_{\rm Ch}$ ($1.2$--$1.5~M_\odot$), and $24 \pm 2\%$ super-$M_{\rm Ch}$ ($>1.5~M_\odot$) events. This work provides a step towards holistic physical characterization of the local SN~Ia population, reinforcing the physical basis of SN~Ia standardization while quantifying diversity and environmental dependencies critical for understanding progenitor physics and mitigating systematics in precision cosmology.

Figures (21)

• Figure 1: Summary of the sample analysed in this work, their redshift distribution and subtypes. All classifications are from Rigault2025.
• Figure 2: Top panels: Light curve fits for the same supernova, SN 2020kej for the basic one-zone, extended model discussed in this paper, and the empirical SALT model, respectively. Bottom panels: Representative light curve fits showing good (left), typical (middle), and bad (right) cases based on the evaluated pseudo $\chi^{2}$ using the extended model. The model successfully captures primary peaks, decline rates, and secondary maxima across the diversity of ZTF light curves.
• Figure 3: Top row: Distributions of ejecta mass, nickel mass, and ejecta velocity for 2,205 SNe Ia. Bottom row: Cumulative distributions showing the uncertainty bands ($68\%$ credible interval). The ejecta mass distribution as a median at $1.40~M_\odot$ (Chandrasekhar mass, highlighted in red), demonstrating near-$M_{\rm Ch}$ dominance. The nickel mass distribution has median $1.19~M_\odot$, and ejecta velocity peaks at $\sim$11,000 km s$^{-1}$. We stress that the histograms hide the true uncertainty represented by the individual posteriors, which is reflected partially by the coloured region in the CDF below.
• Figure 4: Left: The SN Ia mass plane ($M_{\rm Ni}$ vs $M_{\rm ej}$), coloured by host galaxy mass. All events respect the physical prior constraint $M_{\rm Ni} < M_{\rm ej}$ (forbidden region shaded red). Gray dotted lines show constant burning efficiency. Right: Burning efficiency $f_{\rm Ni} = M_{\rm Ni}/M_{\rm ej}$ versus ejecta mass. Both panels share the host mass colour bar.
• Figure 5: Violin plots of the physical properties by spectroscopic subtype. Horizontal lines mark median values.