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nucl-th2024★ 2 cited
Bayesian model mixing with multi-reference energy density functional
Aman Sharma, Nicolas Schunck, Kyle Wendt
Reliably predicting nuclear properties across the entire chart of isotopes is important for applications ranging from nuclear astrophysics to superheavy science to nuclear technolo…
nucl-th2024★ 1 cited
Learning nuclear cross sections across the chart of nuclides with graph neural networks
Hongjun Choi, Sinjini Mitra, Jason Brodksy +6
In this work, we explore the use of deep learning techniques to learn how nuclear cross sections change as we add or remove protons and neutrons. As a proof of principle, we focus…