Speaker
Description
Next generation transient discovery surveys require accurate real-time analysis of evolving transients for followup prioritization from other surveys. SELDON (Supernova Explosions Learned by Deep ODE Networks) is a transient foundation model designed with this capability in mind, and more. Our model not only provides classifications and forecasts for the future evolution of transient light-curves – providing estimates for optimal follow-up observing windows – but also approximates the underlying spectral energy distribution, redshift, and even some characteristics of the observing instrument itself. The architecture itself offers a flexible approach to multi-modal astrophysical data analysis, with physically motivated decoding built upon both intrinsic physical properties of transient evolution as well as the physical engineering behind the observing instrument itself, and time-invariant latent representations of transients that can be adapted for downstream tasks.