1 code implementation • 15 Jul 2022 • George Stein, Uros Seljak, Vanessa Bohm, G. Aldering, P. Antilogus, C. Aragon, S. Bailey, C. Baltay, S. Bongard, K. Boone, C. Buton, Y. Copin, S. Dixon, D. Fouchez, E. Gangler, R. Gupta, B. Hayden, W. Hillebrandt, M. Karmen, A. G. Kim, M. Kowalski, D. Kusters, P. F. Leget, F. Mondon, J. Nordin, R. Pain, E. Pecontal, R. Pereira, S. Perlmutter, K. A. Ponder, D. Rabinowitz, M. Rigault, D. Rubin, K. Runge, C. Saunders, G. Smadja, N. Suzuki, C. Tao, R. C. Thomas, M. Vincenzi
We construct a physically-parameterized probabilistic autoencoder (PAE) to learn the intrinsic diversity of type Ia supernovae (SNe Ia) from a sparse set of spectral time series.
no code implementations • 27 Feb 2020 • B. M. Rose, D. Rubin, A. Cikota, S. E. Deustua, S. Dixon, A. Fruchter, D. O. Jones, A. G. Riess, D. M. Scolnic
We reanalyze this sample of hosts using both the original method and a Bayesian hierarchical model and find after a fuller accounting of the uncertainties the significance of a dependence on age to be $\leq2\sigma$ and $\sim1\sigma$ after the removal of a single poorly-sampled SN Ia.
Cosmology and Nongalactic Astrophysics Astrophysics of Galaxies