Abstract
Abstract
We show how spectra of Type Ia supernovae (SNe Ia) at maximum light can be used to improve cosmological distance estimates. In a companion article, we used manifold learning to build a three-dimensional parameterization of the intrinsic diversity of SNe Ia at maximum light that we call the “Twins Embedding.” In this article, we discuss how the Twins Embedding can be used to improve the standardization of SNe Ia. With a single spectrophotometrically calibrated spectrum near maximum light, we can standardize our sample of SNe Ia with an rms of 0.101 ± 0.007 mag, which corresponds to 0.084 ± 0.009 mag if peculiar velocity contributions are removed and to 0.073 ± 0.008 mag if a larger reference sample were obtained. Our techniques can standardize the full range of SNe Ia, including those typically labeled as peculiar and often rejected from other analyses. We find that traditional light-curve width + color standardization such as SALT2 is not sufficient. The Twins Embedding identifies a subset of SNe Ia, including, but not limited to, 91T-like SNe Ia whose SALT2 distance estimates are biased by 0.229 ± 0.045 mag. Standardization using the Twins Embedding also significantly decreases host-galaxy correlations. We recover a host mass step of 0.040 ± 0.020 mag compared to 0.092 ± 0.026 mag for SALT2 standardization on the same sample of SNe Ia. These biases in traditional standardization methods could significantly impact future cosmology analyses if not properly taken into account.
Funder
U.S. Department of Energy
National Aeronautics and Space Administration
Agence Nationale de la Recherche
Deutsche Forschungsgemeinschaft
Deutsches Zentrum für Luft- und Raumfahrt
Tsinghua University
National Natural Science Foundation of China
EC ∣ European Research Council
Publisher
American Astronomical Society
Subject
Space and Planetary Science,Astronomy and Astrophysics
Cited by
16 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献