Draft version May 6, 2021 Typeset using LATEX twocolumn style in AASTeX63 The Twins Embedding of Type Ia Supernovae II: Improving Cosmological Distance Estimates K. Boone ,1, 2, 3 G. Aldering,1 P. Antilogus ,4 C. Aragon ,1, 5 S. Bailey,1 C. Baltay ,6 S. Bongard,4 C. Buton ,7 Y. Copin ,7 S. Dixon ,1, 2 D. Fouchez ,8 E. Gangler ,7, 9 R. Gupta ,1 B. Hayden ,1, 10 W. Hillebrandt,11 A. G. Kim ,1 M. Kowalski ,12, 13 D. Küsters,2, 13 P.-F. Léget ,4 F. Mondon,9 J. Nordin ,1, 12 R. Pain ,4 E. Pecontal,14 R. Pereira,7 S. Perlmutter ,1, 2 K. A. Ponder ,2 D. Rabinowitz,6 M. Rigault ,12, 7 D. Rubin ,1, 15 K. Runge,1 C. Saunders ,1, 2, 16, 17 G. Smadja ,7 N. Suzuki,1, 18 C. Tao,19, 8 S. Taubenberger ,11 R. C. Thomas,1, 20 M. Vincenzi,1, 21 The Nearby Supernova Factory 1Physics Division, Lawrence Berkeley National Laboratory, 1 Cyclotron Road, Berkeley, CA, 94720, USA 2Department of Physics, University of California Berkeley, 366 LeConte Hall MC 7300, Berkeley, CA, 94720-7300, USA 3DIRAC Institute, Department of Astronomy, University of Washington, 3910 15th Ave NE, Seattle, WA, 98195, USA 4Laboratoire de Physique Nucléaire et des Hautes Energies, CNRS/IN2P3, Sorbonne Université, Université de Paris, 4 place Jussieu, 75005 Paris, France 5College of Engineering, University of Washington 371 Loew Hall, Seattle, WA, 98195, USA 6Department of Physics, Yale University, New Haven, CT, 06250-8121, USA 7Univ Lyon, Univ Claude Bernard Lyon 1, CNRS, IP2I Lyon / IN2P3, UMR 5822, F-69622, Villeurbanne, France 8Aix Marseille Univ, CNRS/IN2P3, CPPM, Marseille, France 9Université Clermont Auvergne, CNRS/IN2P3, Laboratoire de Physique de Clermont, F-63000 Clermont-Ferrand, France 10Space Telescope Science Institute, 3700 San Martin Drive Baltimore, MD, 21218, USA 11Max-Planck-Institut für Astrophysik, Karl-Schwarzschild-Str. 1, D-85748 Garching, Germany 12Institut für Physik, Humboldt-Universitat zu Berlin, Newtonstr. 15, 12489 Berlin, Germany 13DESY, D-15735 Zeuthen, Germany 14Centre de Recherche Astronomique de Lyon, Université Lyon 1, 9 Avenue Charles André, 69561 Saint Genis Laval Cedex, France 15Department of Physics, University of Hawaii, 2505 Correa Rd, Honolulu, HI, 96822, USA 16Princeton University, Department of Astrophysics, 4 Ivy Lane, Princeton, NJ, 08544, USA 17Sorbonne Universités, Institut Lagrange de Paris (ILP), 98 bis Boulevard Arago, 75014 Paris, France 18Kavli Institute for the Physics and Mathematics of the Universe (WPI), The University of Tokyo Institutes for Advanced Study, The University of Tokyo, 5-1-5 Kashiwanoha, Kashiwa, Chiba 277-8583, Japan 19Tsinghua Center for Astrophysics, Tsinghua University, Beijing 100084, China 20Computational Cosmology Center, Computational Research Division, Lawrence Berkeley National Laboratory, 1 Cyclotron Road MS 50B-4206, Berkeley, CA, 94720, USA 21Institute of Cosmology and Gravitation, University of Portsmouth, Portsmouth, PO1 3FX, UK (Accepted March 4, 2021) Submitted to ApJ ABSTRACT arXiv:2105.02204v1 [astro-ph.CO] 5 May 2021 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 parametrization 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 0.073 ± 0.008 mag if a larger Corresponding author: Kyle Boone [email protected] 2 Boone et al. 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 ± 0.024 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. Keywords: Type Ia supernovae — Standard candles — Observational cosmology 1. INTRODUCTION of the host galaxies of SNe Ia. These correlations are Type Ia supernovae (SNe Ia) have proven to be one typically modeled as a “host step” where SNe Ia with of the strongest probes of cosmology. SNe Ia can be ob- a given host property below some threshold have a sys- served out to far distances, and they can be used as stan- tematic offset in their measured distances compared to dardizable candles to infer the distances to them. The SNe Ia above this threshold. SALT2-standardized dis- first distance measurements with reasonably sized sam- tances have been shown to have “host steps” of ∼0.1 mag ples of high-redshift SNe Ia led to the initial discovery of when comparing SNe Ia from host galaxies with different the accelerating expansion of the universe (Riess et al. masses, metallicities, local colors, local star-formation 1998; Perlmutter et al. 1999). Subsequent studies have rates or global star-formation rates (Kelly et al. 2010; now accumulated over 1,000 spectroscopically-confirmed Sullivan et al. 2010; Gupta et al. 2011; D’Andrea et al. SNe Ia, providing increasingly strong constraints on cos- 2011; Rigault et al. 2013, 2015, 2018; Childress et al. mological parameters (Knop et al. 2003; Riess et al. 2013; Hayden et al. 2013; Roman et al. 2018). As galaxy 2004; Astier et al. 2006; Kowalski et al. 2008; Suzuki properties evolve with redshift, correlations of the peak et al. 2012; Betoule et al. 2014; Scolnic et al. 2018; Brout brightness of SNe Ia with their host-galaxy properties et al. 2019; Jones et al. 2019). would need to be well-understood to produce robust cos- mological measurements. 1.1. SNe Ia as Standard Candles The correlations of distance estimates to SNe Ia with host-galaxy properties are also of interest for the mea- At a fixed distance, the observed peak brightnesses of surements of the Hubble constant with SNe Ia. These SNe Ia in the B-band have a dispersion of ∼0.4 mag. To measurements rely on the assumption that SNe Ia in use SNe Ia as distance estimators for cosmology, sev- hosts with Cepheids have similar luminosity distribu- eral corrections need to be applied to their observed tions as the larger sample of SNe Ia (Riess et al. 2016, peak brightnesses. Phillips(1993) showed that the peak 2019; Rigault et al. 2015). If SNe Ia in Cepheid-hosting brightnesses of SNe Ia are tightly correlated with the galaxies have different luminosities than the larger pop- rate of decline of their light curves, commonly referred to ulation SNe Ia, then the measurements of the Hubble as the “light curve width”. Riess et al.(1996) and Tripp constant would be biased. Host-galaxy properties are (1998) showed that the color of the light curve, mea- simply a proxy for some diversity of SNe Ia that is not sured as the difference between the peak brightnesses in captured by current standardization methods. Ideally, the B and V bands, is also highly correlated with the new standardization techniques could be developed that peak brightnesses of SNe Ia. By combining information identify this diversity using properties of the SNe Ia from the width and color of a SN Ia light curve, the dis- themselves rather than properties of their host galax- persion in the corrected peak brightnesses of the SNe Ia ies. is reduced to ∼0.15 mag. The SALT2 model (Guy et al. Several different techniques have been proposed to im- 2007, 2010; Betoule et al. 2014) is one of several im- prove standardization of SNe Ia. One option is to add plementing these two corrections. SALT2 models the additional components to a linear model like SALT2. spectral energy distribution of SNe Ia, and is used to es- Saunders et al.(2018) built a seven-component linear timate distances to SNe Ia in most modern cosmological model (SNEMO) that is capable of parametrizing ad- analyses. ditional diversity in the light curves of SNe Ia com- When distance estimates to SNe Ia are corrected using pared to SALT2, and standardizes SNe Ia to within only light curve width and color, we find that the dis- 0.113 ± 0.007 mag. Alternatively, Léget et al.(2020) tance estimates are correlated with various properties Twins Embedding II 3 built a three-component linear model by first performing oped in Article I to build the Twins Embedding. We de- a PCA decomposition of the spectral features of SNe Ia scribe several new standardization techniques that take near maximum light and then using the resulting PCA advantage of this new parameter space in Section3. In coefficients to build a linear SED model. Another option Section4, we compare all of these different standardiza- is to incorporate additional information beyond optical tion techniques, and show the limitations of traditional light curves into the standardization procedure. The SALT2 distance estimation. In the same Section, we brightnesses of SNe Ia in the NIR are less sensitive to also examine how distances estimated with all of these the intrinsic diversity of SNe Ia (Kasen 2006) and effects different standardization techniques correlate with prop- such as astrophysical dust: the corrected peak bright- erties of the SNe Ia host galaxies.