Strong Dependence of Type Ia Supernova Standardization on the Local Specific Star Formation Rate

TL;DR

This study demonstrates that the local environment of Type Ia supernovae, quantified by the local specific star formation rate (LsSFR), strongly correlates with progenitor age and significantly affects standardized SN brightness. By measuring LsSFR within 1 kpc of each SN and classifying events into young vs old progenitor groups, the authors reveal a substantial brightness offset, $\Delta_Y$, between the two populations that persists even when incorporating traditional lightcurve corrections and a global mass step. Incorporating LsSFR as a third standardization parameter dramatically reduces Hubble residual dispersion (from $\sim0.142$ mag to $\sim0.129$ mag) and shows that roughly 70% of the global mass-step variation is tied to progenitor age. The results imply that neglecting LsSFR-related biases could bias dark energy inferences, especially the evolution parameter $w_a$, at high redshift, and highlight the need to measure and correct for LsSFR in current and future SN Ia cosmology surveys, including JWST, LSST, Euclid, and WFIRST. $\Delta_Y$ is robust to dust and metallicity considerations, and the approach provides a practical pathway to refine SN Ia standardization across redshift.

Abstract

As part of an on-going effort to identify, understand and correct for astrophysics biases in the standardization of Type Ia supernovae (SNIa) for cosmology, we have statistically classified a large sample of nearby SNeIa into those located in predominantly younger or older environments. This classification is based on the specific star formation rate measured within a projected distance of 1kpc from each SN location (LsSFR). This is an important refinement compared to using the local star formation rate directly as it provides a normalization for relative numbers of available SN progenitors and is more robust against extinction by dust. We find that the SNeIa in predominantly younger environments are DY=0.163\pm0.029 mag (5.7 sigma) fainter than those in predominantly older environments after conventional light-curve standardization. This is the strongest standardized SN Ia brightness systematic connected to host-galaxy environment measured to date. The well-established step in standardized brightnesses between SNeIa in hosts with lower or higher total stellar masses is smaller at DM=0.119\pm0.032 mag (4.5 sigma), for the same set of SNeIa. When fit simultaneously, the environment age offset remains very significant, with DY=0.129\pm0.032 mag (4.0 sigma), while the global stellar mass step is reduced to DM=0.064\pm0.029 mag (2.2 sigma). Thus, approximately 70% of the variance from the stellar mass step is due to an underlying dependence on environment-based progenitor age. Standardization using only the SNeIa in younger environments reduces the total dispersion from 0.142\pm0.008 mag to 0.120\pm0.010 mag. We show that as environment ages evolve with redshift a strong bias on measurement of the dark energy equation of state parameters can develop. Fortunately, data to measure and correct for this effect is likely to be available for many next-generation experiments. [abstract shorten]

Figures (8)

• Figure 1: Illustration of a fit to the H$\alpha + {\rm [\ion{N}{II}]}{\,\lambda\lambda6548,6584}$ emission line complex for the host of SNF20060912-004, a typical moderate signal-to-noise case. The gray line shows the emission line spectrum of the local host. The grey band represents its uncertainty, centered around zero. The thick blue line shows the best posterior estimation. The thin blue lines represent 100 realizations from the posterior distribution, illustrating the fit uncertainties. A posterior density sampling in the H$\alpha$ versus [NII] flux plane is displayed as an inset.
• Figure 2: Illustration of how local stellar mass is derived, for the case of a typical moderate signal-to-noise case -- the host of SNF20060912-004. Left:$(g-i)$ color distributions: the histogram shows the likelihood distribution measured from the individual $g$ and $i$ magnitude distributions shown in the inset plot (where the open green histogram represents $g$ and the filled brown histogram represents $i$). The dashed line shows the prior distribution and the filled blue envelope shows the reconstruction of the $(g-i)$ posterior distribution. Right: The posterior distribution of the local stellar mass; the vertical grey solid line indicates the median of the distribution and the two dashed lines show the 16th and 84th percentile values.
• Figure 3: Illustration of how measurement uncertainties taken from posterior distributions for local SFR and local stellar mass are used to construct the posterior distribution for LsSFR. Top left: the local $\log(\mathrm{SFR})$; Lower left: the local $\log(\mathrm{M_*/M_\odot})$ (see also Fig. \ref{['fig:mass_measurement']}); Right: the resulting local $\log(\mathrm{sSFR})$. The vertical grey solid lines indicate the median of each distribution, and the two dashed lines delimit the 16th to 84th percentile range. On the LsSFR plot, the thick vertical black line shows $\log(\mathrm{LsSFR_{cut}})=-10.8$. This figure again exemplifies a moderate signal to noise ratio case using the host galaxy for SNF20060912-004.
• Figure 4: SALT2.4$x_1$ (top) and color "c" (bottom) lightcurve parameters as a function of $\log(\mathrm{LsSFR})$. The marker-color represents the probability for a supernova to have a younger/prompt progenitor (${\mathcal{P}}_Y$, see color-bar). The histograms on the right are ${\mathcal{P}}_Y$-weighted marginalization of SNe Ia lightcurve parameters: toward left for the older/delayed distributions and toward right for the younger/prompt distributions.
• Figure 5: SN Ia Hubble residuals, $\Delta M_B^{corr}$, as a function of $\log(\mathrm{LsSFR})$, calculated from a conventional linear standardization using SALT2.4 lightcurve parameters. The plot symbols and histograms follow the rules of Fig. \ref{['fig:lssfr_lcparam']}. In the main panel and in the histogram-panel, the two horizontal bands show the weighted average of $\Delta M_B^{corr}$ per progenitor age group. The width of each band represents the corresponding error on the mean, and their offset illustrates the Hubble residual offset between the two age groups. The error bars on $\Delta M_B^{corr}$ include the measurement, SALT2.4 systematic, and residual dispersions from the maximum-likelihood fit to each population.