Neural-network quantum states applied to HAL QCD meson-nucleon potentials predict bound states for phi at A>=2, J/psi at A>=4, and eta_c at A>=6, with binding energies from tens of MeV to sub-MeV scales.
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hep-ph 2years
2026 2verdicts
UNVERDICTED 2representative citing papers
Neural-network quantum states are used to compute spectra of fully-heavy multiquarks in a non-relativistic quark model, claiming to overcome dimensionality issues with superior accuracy over prior approximations.
citing papers explorer
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Meson-Nucleus Bound States with Neural-Network Quantum States
Neural-network quantum states applied to HAL QCD meson-nucleon potentials predict bound states for phi at A>=2, J/psi at A>=4, and eta_c at A>=6, with binding energies from tens of MeV to sub-MeV scales.
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Fully-heavy multiquarks in neural-network quantum states
Neural-network quantum states are used to compute spectra of fully-heavy multiquarks in a non-relativistic quark model, claiming to overcome dimensionality issues with superior accuracy over prior approximations.