Shortening the Baseline: Characterising Type Ia Supernovae Using Δm10(X)
Abstract
An explorative study of Type Ia Supernovae (SNe Ia) light curves is presented. Δmt(X) decline-rate metrics are used to evaluate alternative characterisations of light curve diversity and the Luminosity-Width Relation (LWR). Using a sample of 362 SNe Ia from the Carnegie Supernova Project (CSP-I and CSP-II), Gaussian Process regression is used to fit B- and g-band light curves and measure decline-rates across multiple post-maximum timescales. The LWR is calibrated using a clean subsample of SNe Ia with host-independent distance moduli and Fitzpatrick (1999) reddening corrections. Decline-rates Δm10(B) and Δm10(g) are found to capture the LWR effectively, while mitigating the severe degeneracy that affects longer timescales for fast-declining (Δm15(B) ≥ 1.6 mag) events. Continuous, piecewise linear models are presented that seamlessly anchor the transition between normal and fast-declining regimes. The decline-rate Δm10(X) closely approximates the results of the more complex colour-stretch parameters, requiring less post-maximum temporal coverage than Δm15(B) or sBV, and offers an even greater sensitivity for slow decliners. Δm10(B) provides a precise and practical tool for large-scale photometric surveys and real-time observer classification.photometric surveys and real-time observer classification.
Versions
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BibTeX
@misc{velasco2026shortening,
title = {{Shortening the Baseline: Characterising Type Ia Supernovae Using $Δm_10(X)$}},
author = {Joel M. Velasco and Paolo A. Mazzali and Christopher Ashall and Christopher R. Burns and Mark M. Phillips and Lluis Galbany and Nidia Morrell and Maximilian D. Stritzinger and Peter Hoeflich and Eric Y. Hsiao and Syed A. Uddin},
howpublished = {arXiv},
year = {2026},
month = oct,
doi = {10.48550/arxiv.2610.10815},
eprint = {2610.10815},
archivePrefix = {arXiv},
url = {https://arxiv.org/abs/2610.10815},
}
RIS
TY - UNPB
TI - Shortening the Baseline: Characterising Type Ia Supernovae Using Δm_10(X)
AU - Joel M. Velasco
AU - Paolo A. Mazzali
AU - Christopher Ashall
AU - Christopher R. Burns
AU - Mark M. Phillips
AU - Lluis Galbany
AU - Nidia Morrell
AU - Maximilian D. Stritzinger
AU - Peter Hoeflich
AU - Eric Y. Hsiao
AU - Syed A. Uddin
PY - 2026
DA - 2026/10/07
PB - arXiv
DO - 10.48550/arxiv.2610.10815
UR - https://arxiv.org/abs/2610.10815
AB - An explorative study of Type Ia Supernovae (SNe Ia) light curves is presented. Δm_t(X) decline-rate metrics are used to evaluate alternative characterisations of light curve diversity and the Luminosity-Width Relation (LWR). Using a sample of 362 SNe Ia from the Carnegie Supernova Project (CSP-I and CSP-II), Gaussian Process regression is used to fit B- and g-band light curves and measure decline-rates across multiple post-maximum timescales. The LWR is calibrated using a clean subsample of SNe Ia with host-independent distance moduli and Fitzpatrick (1999) reddening corrections. Decline-rates Δm_10(B) and Δm_10(g) are found to capture the LWR effectively, while mitigating the severe degeneracy that affects longer timescales for fast-declining (Δm_15(B) ≥ 1.6 mag) events. Continuous, piecewise linear models are presented that seamlessly anchor the transition between normal and fast-declining regimes. The decline-rate Δm_10(X) closely approximates the results of the more complex colour-stretch parameters, requiring less post-maximum temporal coverage than Δm_15(B) or s_BV, and offers an even greater sensitivity for slow decliners. Δm_10(B) provides a precise and practical tool for large-scale photometric surveys and real-time observer classification.photometric surveys and real-time observer classification.
ER -