A physics-guided neural network maps density functional theory potential energy landscapes to interacting boson model parameters for rare-earth nuclei, yielding spectra that reflect structural evolution.
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Microscopic derivation of the interacting boson model parameters with machine learning
A physics-guided neural network maps density functional theory potential energy landscapes to interacting boson model parameters for rare-earth nuclei, yielding spectra that reflect structural evolution.