Analytical derivation shows mutual relations between density, magnetic, and pairing susceptibilities in the Hubbard model, revealing a degeneracy between d-wave pairing and d-density wave instabilities near the metal-insulator transition that is lifted by frustration.
Zhang, Coexistence of superconductivity with par- tially filled stripes in the hubbard model, Science384, 10.1126/science.adh7691 (2024)
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SCALE and ACE are new convolutional backflow architectures for Neural Quantum States that deliver O(N^3) scaling with high accuracy and over 40x speedup on Hubbard and t-J models up to 32x32 lattices.
Real-time dynamics in the 2D Hubbard model show thermalization of double occupancy below a critical U_c but clear breakdown of thermalization above it.
Transformer wave functions for the J1-J2 Heisenberg model exhibit size-independent power-law decay of V-score with compute, with the exponent decreasing as frustration increases.
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.
Broad regions of horizontal and vertical spin stripes appear at low temperature in the Hubbard model, with wavelengths that vary nonlinearly with hole doping and are highly sensitive to the ratio of nearest- and next-nearest-neighbor hoppings.
A quantics tensor train solver resolves the Gross-Pitaevskii equation across seven orders of magnitude in length scale in one dimension and on grids larger than a trillion points in two dimensions.
citing papers explorer
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On Degeneracies of Density, Magnetic, and Pairing Responses: How Competing Orders Echo Underlying Symmetries in the Hubbard Model
Analytical derivation shows mutual relations between density, magnetic, and pairing susceptibilities in the Hubbard model, revealing a degeneracy between d-wave pairing and d-density wave instabilities near the metal-insulator transition that is lifted by frustration.
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Pareto Frontier of Neural Quantum States: Scalable, Affordable, and Accurate Convolutional Backflow for Strongly Correlated Lattice Fermions
SCALE and ACE are new convolutional backflow architectures for Neural Quantum States that deliver O(N^3) scaling with high accuracy and over 40x speedup on Hubbard and t-J models up to 32x32 lattices.
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Breakdown of Thermalization from Real-Time Dynamics in the Two-Dimensional Hubbard Model
Real-time dynamics in the 2D Hubbard model show thermalization of double occupancy below a critical U_c but clear breakdown of thermalization above it.
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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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Spin-stripes in the Hubbard model: a combined DMFT and Bethe-Salpeter analysis
Broad regions of horizontal and vertical spin stripes appear at low temperature in the Hubbard model, with wavelengths that vary nonlinearly with hole doping and are highly sensitive to the ratio of nearest- and next-nearest-neighbor hoppings.