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 T₁₀=121. 9^+9. 5-₇. ₅ days and T₁₂=63. 2^+3. 2-₃. ₃ days along with absolute magnifications β for each image, A = 2. 38^+0. 72-₀. ₅₄, B=5. 27^+1. 25-₁. ₀₂ and 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. 3^+12. 6-₇. ₈ km s−1 Mpc−1, consistent with previous analysis of this system; incorporating additional constraints based on spectroscopy yields H₀=66. 8^+13. 4-₅. ₄ km s−1 Mpc−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 H0; BayeSN-TD will be a valuable tool for these analyses. The BayeSN-TD code is available at https: //github. com/bayesn/bayesn-td.
Grayling et al. (2026) studied this question.