BayeSN-TD: Time Delay and $H_0$ Estimation for Lensed SN H0pe
Abstract
We present BayeSN-TD, an enhanced implementation of the probabilistic type Ia supernova (SN Ia) BayeSN SED model, designed for fitting multiply-imaged, gravitationally lensed type Ia supernovae (glSNe Ia). BayeSN-TD fits for magnifications and time-delays across multiple images while marginalising over an achromatic, Gaussian process-based treatment of microlensing, to allow for time-dependent deviations from a typical SN Ia SED caused by gravitational lensing by stars in the lensing system. BayeSN-TD is able to robustly infer time delays and produce well-calibrated uncertainties, even when applied to simulations based on a different SED model and incorporating chromatic microlensing, strongly validating its suitability for time-delay cosmography. We then apply BayeSN-TD to publicly available photometry of the glSN Ia SN H0pe, inferring time delays between images BA and BC of days and days along with absolute magnifications for each image, , and . Combining our constraints on time-delays and magnifications with existing lens models of this system, we infer km s Mpc, consistent with previous analysis of this system; incorporating additional constraints based on spectroscopy yields km s Mpc. While this is not yet precise enough to draw a meaningful conclusion with regard to the `Hubble tension', upcoming analysis of SN H0pe with more accurate photometry enabled by template images, and other glSNe, will provide stronger constraints on ; BayeSN-TD will be a valuable tool for these analyses.
Cite
@article{arxiv.2510.11719,
title = {BayeSN-TD: Time Delay and $H_0$ Estimation for Lensed SN H0pe},
author = {M. Grayling and S. Thorp and K. S. Mandel and M. Pascale and J. D. R. Pierel and E. E. Hayes and C. Larison and A. Agrawal and G. Narayan},
journal= {arXiv preprint arXiv:2510.11719},
year = {2026}
}
Comments
21 pages, 11 figures, 4 tables. Accepted by MNRAS. BayeSN-TD code available at github.com/bayesn/bayesn-td