223 citations · 1.2k across the 33 of their papers we have counts for
3 papers · 1 filter
Constraining Nuclear Mass Models Using r-process Observables with Multi-objective Optimization
Mengke Li, Matthew Mumpower, Nicole Vassh +2
Predicting nuclear masses is a longstanding challenge. One path forward is machine learning (ML) which trains on experimental data, but can suffer large errors when extrapolating t…
Classifying metal-poor stars with machine learning using nucleosynthesis calculations
Nicole Vassh, Yilin Wang, Richard M. Woloshyn +4
We apply the capabilities of machine learning (ML) to discern patterns in order to classify metal-poor stars. To do so, we train an ML model on a bank of nucleosynthesis calculatio…
Multidisciplinary Science in the Multimessenger Era
Eric Burns, Christopher L. Fryer, Ivan Agullo +82
Astrophysical observations of the cosmos allow us to probe extreme physics and answer foundational questions on our universe. Modern astronomy is increasingly operating under a hol…