Still Accelerating: Type Ia supernova cosmology is robust to host galaxy age evolution
Phil Wiseman, Brodie Popovic, Mark Sullivan, Adam G. Riess, Dan Scolnic, Rebecca C. Chen, Tamara M. Davis, Llu\'is Galbany, Isobel M. Hook, Saurabh W. Jha, Lisa Kelsey, Yukei S. Murakami, Micka\"el Rigault, Benjamin M. Rose, Brian Schmidt, Mat Smith, Maria Vincenzi

TL;DR
This paper argues that the evidence for supernova progenitor age evolution affecting cosmological measurements is negligible, reaffirming the robustness of Type Ia supernova cosmology.
Contribution
It demonstrates that previous claims of age-related luminosity evolution are based on analyses that omit standard corrections and conflated age measures, which are corrected in modern analyses.
Findings
Applying host-galaxy mass correction removes dependence on host age.
Dark Energy Survey data shows no significant redshift evolution of host-mass effect.
Progenitor age difference between nearby and distant supernovae is overstated by factors of three to five.
Abstract
Type Ia supernovae are a cornerstone of modern cosmology, providing first evidence for cosmic acceleration and new tests of dark energy. Son et al. 2025 (S25) claim a strong redshift evolution in standardized supernova luminosities driven by supernova progenitor age, with dramatic cosmological implications: rapidly evolving dark energy, decelerating expansion, and a tension with CDM. We show that the underpinning evidence required for this conclusion -- the supernova progenitor-age dependence, the redshift-dependent age difference, and their combined impact -- is either negligible or relies on effects already corrected for in modern supernova analyses. First, the S25 analysis omits the standard host-galaxy stellar mass correction that captures known environmental dependencies that also correlate with stellar age. Applying this correction to the S25 sample, we find no…
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.
