English

BayeSN-TD: Time Delay and $H_0$ Estimation for Lensed SN H0pe

Cosmology and Nongalactic Astrophysics 2026-04-13 v2

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 ΔTBA=121.97.5+9.5\Delta T_{BA}=121.9^{+9.5}_{-7.5} days and ΔTBC=63.23.3+3.2\Delta T_{BC}=63.2^{+3.2}_{-3.3} days along with absolute magnifications β\beta for each image, βA=2.380.54+0.72\beta_A = 2.38^{+0.72}_{-0.54}, βB=5.271.02+1.25\beta_B=5.27^{+1.25}_{-1.02} and βC=3.930.75+1.00\beta_C=3.93^{+1.00}_{-0.75}. Combining our constraints on time-delays and magnifications with existing lens models of this system, we infer H0=69.37.8+12.6H_0=69.3^{+12.6}_{-7.8} km s1^{-1} Mpc1^{-1}, consistent with previous analysis of this system; incorporating additional constraints based on spectroscopy yields H0=66.85.4+13.4H_0=66.8^{+13.4}_{-5.4} km s1^{-1} Mpc1^{-1}. 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 H0H_0; BayeSN-TD will be a valuable tool for these analyses.

Keywords

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