Neural network quantum states, extended to include Lambda hyperons, reproduce hypernuclear separation energies to within roughly 9% and predict the observed proton-radius shrinkage in 7ΛLi.
Solution of the Hyperon Puzzle within a Relativistic Mean-Field Model
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abstract
The equation of state of cold baryonic matter is studied within a relativistic mean-field model with hadron masses and coupling constants depending on the scalar field. All hadron masses undergo a universal scaling, whereas the coupling constants are scaled differently. The appearance of hyperons in dense neutron star interiors is accounted for, however the equation of state remains sufficiently stiff if a reduction of the $\phi$ meson mass is included. Our equation of state matches well the constraints known from analyses of the astrophysical data and the particle production in heavy-ion collisions.
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Hypernuclei with Neural Network Quantum States
Neural network quantum states, extended to include Lambda hyperons, reproduce hypernuclear separation energies to within roughly 9% and predict the observed proton-radius shrinkage in 7ΛLi.