Understanding Type Ia Supernova Distance Biases by Simulating Spectral
  Variations
  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 $\sim10^3$ 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 $\Delta
w=-0.023$ for SN velocity and $\Delta w=0.021$ 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.
