Canonical mapping of quantum-dot-superconductor clusters enables neural quantum-state calculations that reveal trivial singlet, Heisenberg-like, and critical regimes with 1D gaplessness and 2D triplet states.
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Three Transformer backflow fermionic wave functions for the finite-doping Hubbard model converge, after accuracy improvements, to the same state with coexisting superconducting and stripe orders, demonstrating that variational energy is insufficient to identify the ground state.
Neural quantum states yield Born-Oppenheimer and non-Born-Oppenheimer energies for high-pressure atomic hydrogen that match or beat prior projector Monte Carlo results up to 128 atoms while avoiding symmetry assumptions and mass-scale issues.
Minimum number of terms for exact antisymmetry in a class of TPFs grows exponentially with dimension, shown via CP rank of antisymmetric tensors.
citing papers explorer
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Correlated States in Quantum Dot Clusters Coupled to a Common Superconductor
Canonical mapping of quantum-dot-superconductor clusters enables neural quantum-state calculations that reveal trivial singlet, Heisenberg-like, and critical regimes with 1D gaplessness and 2D triplet states.
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Beyond Variational Bias: Resolving Intertwined Orders in the Hubbard Model
Three Transformer backflow fermionic wave functions for the finite-doping Hubbard model converge, after accuracy improvements, to the same state with coexisting superconducting and stripe orders, demonstrating that variational energy is insufficient to identify the ground state.
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Neural Wave Functions for High-Pressure Atomic Hydrogen
Neural quantum states yield Born-Oppenheimer and non-Born-Oppenheimer energies for high-pressure atomic hydrogen that match or beat prior projector Monte Carlo results up to 128 atoms while avoiding symmetry assumptions and mass-scale issues.