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.
Robledo Moreno, G
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An unbiased time-dependent variational Monte Carlo method is introduced via self-normalized importance sampling on a cutoff-deformed Born distribution, with a complementary tensor cross interpolation approach explored.
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Time-dependent variational Monte Carlo without bias
An unbiased time-dependent variational Monte Carlo method is introduced via self-normalized importance sampling on a cutoff-deformed Born distribution, with a complementary tensor cross interpolation approach explored.