Understanding Type Ia Supernova Distance Biases by Simulating Spectral Variations

Abstract

In the next decade, transient searches from the Vera C. Rubin Observatory and the Nancy Grace Roman Space Telescope will increase the sample of known Type Ia Supernovae (SN Ia) from ∼10 3 to 10 5 . With this reduction of statistical uncertainties on cosmological measurements, new methods are needed to reduce systematic uncertainties. Characterizing the underlying spectroscopic evolution of SN Ia remains a major systematic uncertainty in current cosmological analyses, motivating a new simulation tool for the next era of SN Ia cosmology: Build Your Own Spectral Energy Distribution (byosed). byosed is used within the SNANA framework to simulate light curves by applying spectral variations to model SEDs, enabling flexible testing of possible systematic shifts in SN Ia distance measurements. We test the framework by comparing a nominal Roman SN Ia survey simulation using a baseline SED model to simulations using SEDs perturbed with byosed, and investigate the impact of neglecting specific SED features in the analysis. These features include semi-empirical models of two possible, predicted relationships: between SN ejecta velocity and light curve observables, and a redshift-dependent relationship between SN Hubble residuals and host galaxy mass. We analyze each byosed simulation using the SALT2 & BBC framework, and estimate changes in the measured value of the dark energy equation-of-state parameter, w. We find a difference of ∆w = −0.023 for SN velocity and ∆w = 0.021 for redshift-evolving host mass when compared to simulations without these features. By using byosed for SN Ia cosmology simulations, future analyses (e.g., Rubin and Roman SN Ia samples) will have greater flexibility to constrain or reduce such SN Ia modeling uncertainties.

The Foundation Supernova Survey: Photospheric Velocity Correlations in Type Ia Supernovae

“…Understanding the origin of these sample differences, whether they are related to selection effects or not, is of clear importance. Pierel et al (2020) show that, if uncorrected, the HR offset between velocity subsamples found by S20 could be a leading systematic uncertainty in future supernova surveys aiming at precision cosmology, such as from the Nancy Grace Roman Space Telescope (Hounsell et al 2018). If, on the other hand, supernova cosmology samples are more similar to the Foundation objects, the effect may be muted.…”

SALT3: An Improved Type Ia Supernova Model for Measuring Cosmic Distances

“…This simulation does not exactly reproduce the data set because of random fluctuations in photometric noise and intrinsic scatter, and also because the underlying SALT2 model formalism is an approximation as discussed in Pierel et al (2020). Nonetheless the simulation is very similar to the data and is therefore sufficient for testing SALTshaker, as illustrated in Figure 3 for a representative low-z SN Ia.…”

“…As regularization can bias the model surfaces by over-smoothing them (Mosher et al 2014), we tune the weights to ensure that the regularization terms do not contribute significantly to the total χ 2 . Further work to determine how this regularization scheme affects the model and to choose optimal model configurations will require applying our training and analysis framework to simulations (Dai et al in prep;Pierel et al 2020).…”

“…The BYOSED code (Pierel et al 2020) implements a range of simulated effects to a base SED template, such as perturbations to line velocity, multiple sources of reddening with distinct effects, and correlations of host galaxy properties with the SN Ia SED. Future work could perform the SALTshaker method on a BYOSEDproduced training sample with such underlying effects.…”

“…To characterize and correct for such untrained effects, it is essential to perform training studies on simulated data that incorporates a broad range of physical effects. Therefore, in parallel with the the SALT3 development our team has developed a more general SED-simulation framework described in Pierel et al (2020).…”