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.
Embedding nuclear physics inside the unitary window
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abstract
The large values of the singlet and triplet scattering lengths locate the two-nucleon system close to the unitary limit, the limit in which these two values diverge. As a consequence, the system shows a continuous scale invariance which strongly constrains the values of the observables, a well-known fact already noticed a long time ago. The three-nucleon system shows a discrete scale invariance that can be observed by correlations of the triton binding energy with other observables as the doublet nucleon-deuteron scattering length or the alpha-particle binding energy. The low-energy dynamics of these systems is universal; it does not depend on the details of the particular way in which the nucleons interact. Instead, it depends on a few control parameters, the large values of the scattering lengths and the triton binding energy. Using a potential model with variable strength set to give values to the control parameters, we study the spectrum of $A=2,3,4,6$ nuclei in the region between the unitary limit and their physical values. In particular, we analyze how the binding energies emerge from the unitary limit forming the observed levels.
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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.