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arXiv · 2605.30944

Neural-network excited states of $A=4$ nuclei and hypernuclei

Zi-Xiao Zhang·Yi-Long Yang·Xiao-Lu Qian·Wan-Bing He·Peng-Wei Zhao·Bing-Nan Lu·Yu-Gang Ma
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Abstract

We present the first variational Monte Carlo study of nuclear and hypernuclear excited states within the neural-network quantum states (NQS) framework. We implement both the overlap penalty (OP) and natural excited state (NES) methods to compute low-lying excitation spectra. To address the spin contamination in hypernuclear calculations, we propose a quantum number targeting (QNT) technique for the OP method. Both the OP-QNT and NES methods can reproduce diagonal observables, such as energies and spatial structures, in excellent agreement with rigorous benchmarks. We further provide, to our knowledge, the first \textit{ab initio} calculation of the $M1$ transition strength for $^{4}_{\Lambda}\mathrm{H}$. The calculated transition strength is consistent with the weak-coupling limit, exhibiting a $\sim$1.3\% suppression. This work demonstrates that NQS can be elevated from ground-state solvers to practical tools for nuclear and hypernuclear spectroscopy.

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Zi-Xiao Zhang, Yi-Long Yang, Xiao-Lu Qian, Wan-Bing He, Peng-Wei Zhao, Bing-Nan Lu, Yu-Gang Ma. 2026-05-29. Neural-network excited states of $A=4$ nuclei and hypernuclei. https://doi.org/10.1016/j.physletb.2026.140911

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