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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A statistical method expresses pair correlations as ensemble averages over single-particle-conditioned kernels, enabling event-by-event reconstruction of rare-particle emission sources, demonstrated on simulated J/ψ data with 13% uncertainty.
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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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Reconstructing rare particle source by femtoscopic correlations
A statistical method expresses pair correlations as ensemble averages over single-particle-conditioned kernels, enabling event-by-event reconstruction of rare-particle emission sources, demonstrated on simulated J/ψ data with 13% uncertainty.