Epscor research fellows NSF: developing next-generation electromagnetic models of explosive transient observations

The National Science Foundation Office of Integrative Activities awarded the Regents of the University of Idaho $294,919 on January 15, 2027, under the Integrative Activities program (CFDA 47.083) to develop next-generation electromagnetic models of core-collapse supernovae and explosive transient observations.

The fellowship supports an assistant professor at the University of Idaho and provides training for a graduate student in computational astrophysics. The work centers on developing state-of-the-art three-dimensional radiation-hydrodynamic computational models that resolve the explosive deaths of massive stars as supernovae, producing predictive templates of light from these explosions in anticipation of expanding supernova observational catalogs from instruments including NSF/DOE Rubin Observatory and NASA's Roman Space Telescope. The project integrates machine learning, detailed astrophysics simulations, and big data analysis to optimize observational survey data and establish a citizen-science platform for astronomy survey data modeling. Research deliverables include end-to-end 3D light curve and spectra templates from first-principles simulations to improve parameter estimation of stellar explosions and their environments, and advances in 3D modeling of non-local thermodynamic signatures to resolve degeneracies in parameter inference.

Work is conducted in collaboration with Professor Daniel Kasen at UC Berkeley, with performance taking place in Berkeley, California. The award period extends from January 15, 2027, through December 31, 2028.

Abstract

This research infrastructure improvement (RII) epscor research fellows project provides a fellowship to an assistant professor and training for a graduate student at the university of idaho. This work is conducted in collaboration with professor daniel kasen at UC berkeley. Through the fellowship, the PI will developed state-of-the-art computational models that resolve the explosive deaths of massive STARS as supernovae. These models will provide predictive templates of the light produced by these vigorous explosions in direct anticipation of the exponentially growing catalog of supernova observations with space and ground-based instruments like NSF/DOE rubin obseravatory and NASA?s roman space telescope. This project combines machine learning, detailed astrophysics simulations, and big data to explain and optimize the data gleaned from next-generation observational surveys, trains a student in computational astrophysics, and enables a community citizen-science platform for astronomy survey data modeling. The project will bridge core-collapse supernova modeling with survey observations to advance multi-messenger transient modeling in the 3D ERA. The PI will develop end-to-end 3D radiation-hydrodynamic templates of core-collapse supernova light curves and spectra from first-principles simulations to improve parameter estimation of stellar explosions and their environments across observational mission scales. The project will advance 3D modeling of non-local thermodynamic signatures of supernova to break degeneracies in parameter inference. The project will train a student in data-intensive modeling, develop and sustain collaborations with UC berkeley, national laboratories, and observing missions, enrich the computational astrophysics program at the university of idaho and position IT as a contributor to predictive transient astrophysics. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the foundation's intellectual merit and broader impacts review criteria.- subawards are not planned for this award.