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.
Similarity renormalization group evolution of hypernuclear Hamiltonians
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abstract
Unitary transformations of a Hamiltonian generally induce interaction terms beyond the particle rank present in the untransformed Hamiltonian that have to be captured and included in a many-body calculation. In systems with strangeness such as hypernuclei, the three-body terms induced by the hyperon-nucleon interaction are strong, so their inclusion is crucial. We present in detail a procedure for computing hyperon-nucleon-nucleon interaction terms that are induced during a similarity renormalization group (SRG) flow. The SRG is carried out in a basis spanned by antisymmetric harmonic-oscillator states with respect to three-body Jacobi coordinates. We discuss basis construction, antisymmetrization, numerical evaluation of the flow equations, and separation of the genuine three-body terms. We then use the hypernuclear no-core shell model with SRG-evolved Hamiltonians, addressing the sensitivity of hypernuclear states and hyperon separation energies to changes in the nucleonic Hamiltonian by example of $^7_\Lambda$Li, $^9_\Lambda$Be, $^{11}_\Lambda$B, $^{13}_\Lambda$C, and the hyper-helium chain. We also present a survey of the hyper-hydrogen chain, exploring the structure of hypernuclei with extreme neutron-proton asymmetries.
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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.