Pierre-Francois Leget (Kavli Institute for Particle Astrophysics and Cosmology, Department of Physics, Stanford University)

"Improved description of SNIa variability for a better understanding of dark energy properties"

Type Ia Supernova (SNIa) standardization for cosmology is based on a well-established observational paradigm that two main effects explain their variability: stretch and color. However, an intrinsic luminosity scatter still exists after standardization, which indicates that the standard scheme lacks some ingredients. We address this issue by exploring the possibility that the intrinsic luminosity scatter leaves an imprint on the supernova spectral time series.

Our approach is to revisit the spectral diversity of SNIa with the help of the Nearby Supernova Factory data consisting of hundreds of spectrophotometric time series, and to build a novel SED model, SUGAR (Supernovae Useful Generator and Reconstructor) extending the principles of the SALT2 model. Our principal findings are that the spectral diversity observed at maximum light exhibits 2 new intrinsic components, and that the color law is confirmed to be compatible with extinction by dust. Taking these new variabilities into account, we are able to derive a SED model which matches closer the observed spectra than SALT2 does, and which improves the standardization.

In this seminar I will first present the current cosmological context, focusing on the state of the art of distance measurements with SNIa. I will then discuss the limitations of the current method which is based on the light curves properties (stretch, color). Finally, I will introduce the SUGAR model developed using Nearby Supernova Factory data and which significantly improves the spectral description of SNIa compared to the current SNIa model SALT2. I will then discuss its consequences for cosmology.