Disorder-aware neural quantum states provide the first microscopic evidence for a pinned hole Wigner crystal near ν=2/3 that accounts for reentrant integer quantum Hall physics and reveals an electron-hole asymmetry in crystallization.
Artificial intelligence for quantum matter: Finding a needle in a haystack.arXiv preprint arXiv:2507.13322,
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WF-Bench is a new benchmark for neural network wavefunctions that matches them to diverse quantum many-body targets and derives empirical scaling laws for representability based on system size and model parameters like determinant count and depth.
Fermi Sets achieve universal approximation of fermionic wavefunctions using K antisymmetric bases times symmetric neural networks, where K equals 1 in 1D, 2 in 2D, and grows linearly with particle number in higher dimensions.
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.
citing papers explorer
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Crystallization in the Fractional Quantum Hall Regime with Disorder-Aware Neural Quantum States
Disorder-aware neural quantum states provide the first microscopic evidence for a pinned hole Wigner crystal near ν=2/3 that accounts for reentrant integer quantum Hall physics and reveals an electron-hole asymmetry in crystallization.
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WF-Bench: A Benchmark for Neural Network WaveFunction Expressivity and Scaling Laws
WF-Bench is a new benchmark for neural network wavefunctions that matches them to diverse quantum many-body targets and derives empirical scaling laws for representability based on system size and model parameters like determinant count and depth.
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Fermi Sets: Universal and interpretable neural architectures for fermions
Fermi Sets achieve universal approximation of fermionic wavefunctions using K antisymmetric bases times symmetric neural networks, where K equals 1 in 1D, 2 in 2D, and grows linearly with particle number in higher dimensions.
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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.