Neural network quantum states compute Efimov bound states for 3-6 boson systems and mass-imbalanced fermions at unitarity, matching known energies and reproducing scale invariance and wave function features.
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QERNEL is a single conditioned neural wavefunction that variationally solves families of many-electron Hamiltonians in moiré heterobilayers and identifies the quantum liquid-crystal phase transition.
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Neural-network quantum states for solving few-body problems: application to Efimov physics
Neural network quantum states compute Efimov bound states for 3-6 boson systems and mass-imbalanced fermions at unitarity, matching known energies and reproducing scale invariance and wave function features.
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QERNEL: a Scalable Large Electron Model
QERNEL is a single conditioned neural wavefunction that variationally solves families of many-electron Hamiltonians in moiré heterobilayers and identifies the quantum liquid-crystal phase transition.
- Enhancing Neural-Network Variational Monte Carlo through Basis Transformation