Spectroscopic Properties of Star-Forming Host Galaxies and Type Ia Supernova Hubble Residuals in a Nearly Unbiased Sample
Chris B. D'Andrea, Ravi R. Gupta, Masao Sako, Matt Morris, Robert C., Nichol, Peter J. Brown, Heather Campbell, Matthew D. Olmstead, Joshua A., Frieman, Peter Garnavich, Saurabh W. Jha, Richard Kessler, Hubert Lampeitl,, John Marriner, Donald P. Schneider, Mathew Smith

TL;DR
This study investigates how properties of star-forming host galaxies, such as metallicity and star-formation rate, correlate with Type Ia supernova brightness residuals, revealing potential biases in cosmological measurements.
Contribution
It introduces spectroscopic analysis of host galaxies to directly measure metallicity and star-formation rates, improving understanding of supernova-host correlations.
Findings
Supernovae are ~0.1 magnitudes brighter in high-metallicity hosts.
Significant correlation between Hubble residuals and host galaxy star-formation rate.
Spectroscopic host analysis reduces bias compared to photometric estimates.
Abstract
We examine the correlation between supernova host galaxy properties and their residuals on the Hubble diagram. We use supernovae discovered during the Sloan Digital Sky Survey II - Supernova Survey, and focus on objects at a redshift of z < 0.15, where the selection effects of the survey are known to yield a complete Type Ia supernova sample. To minimize the bias in our analysis with respect to measured host-galaxy properties, spectra were obtained for nearly all hosts, spanning a range in magnitude of -23 < M_r < -17. In contrast to previous works that use photometric estimates of host mass as a proxy for global metallicity, we analyze host-galaxy spectra to obtain gas-phase metallicities and star-formation rates from host galaxies with active star formation. From a final sample of ~ 40 emission-line galaxies, we find that light-curve corrected Type Ia supernovae are ~ 0.1 magnitudes…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
