Better redshifts from supernova spectra
We are currently assembling a new supernova sample to constrain cosmology.
Redshifts are usually determined from the galaxies that host the supernovae, but some hosts are too faint. This project aims to improve the accuracy and precision of redshifts obtained from supernovae.
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DEBASS - The ultimate low redshift supernova sample for cosmology
Unlocking the mystery of dark energy is one of the key goals of observational cosmology. The LambdaCDM model, in which the dark energy equation-of-state parameter is exactly -1, has so far survived the enormous improvement in constraints achieved since the original discovery of the accelerating universe using type Ia supernovae (SNe Ia) as standard candles. However, recent results from the Dark Energy Survey (DES) and the Dark Energy Spectroscopic Instrument (DESI) are putting the LambdaCDM model under pressure [1,2]. Both experiments provide hints that dark energy varies with time. If verified, this would rule out Einstein's cosmological constant as the reason for the accelerating universe
While this is a tantalising development, the slight disagreement with Einstein's cosmological constant seen in recent results may be driven by the low-redshift SN sample that anchors the Hubble diagram. The SNe Ia come from a variety of historical external surveys. The uncertain calibration of these surveys may be driving the result. To reduce the systematic uncertainty related to the low-redshift sample, we need to replace it with a larger, modern, and more precisely calibrated sample of low-redshift SNe Ia. We are currently assembling this sample. It is called DEBASS.
To place SNe Ia on the Hubble diagram, we need a redshift of the SN or its host galaxy. While redshifts from the host are more precise and accurate than redshifts from the SN, not all hosts are bright enough to measure a redshift.
This project aims to improve the accuracy and precision of redshifts from the SNe, so that they can be used to constrain cosmological parameters.
The project consists of the following elements
- using light curve and phase information to constrain the best fitting spectral templates and redshifts
- determining statistical and systematic errors in the measreument
Refs:
[1] DES Collaboration et al. 2024,ApJ, 973, 14:
[2] DESI Collaboration et al. 2025, arXiV 2503.14738