Neural networks learn the score of the probability density on Bohmian trajectories to recover exact Schrödinger dynamics via self-consistent minimization for nodeless wave functions, demonstrated on double-well splitting and Morse chain vibrations.
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A variational nodal partition decomposes correlation energy into E_sym containing dynamic and strong correlation and E_stat isolating the antisymmetric sign-structure component as an energy penalty from node constraint.
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Quantum Dynamics via Score Matching on Bohmian Trajectories
Neural networks learn the score of the probability density on Bohmian trajectories to recover exact Schrödinger dynamics via self-consistent minimization for nodeless wave functions, demonstrated on double-well splitting and Morse chain vibrations.
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From Wavefunction Sign Structure to Static Correlation
A variational nodal partition decomposes correlation energy into E_sym containing dynamic and strong correlation and E_stat isolating the antisymmetric sign-structure component as an energy penalty from node constraint.