Grassmann Variational Monte Carlo generalizes neural-network excited-state optimization to subspaces and accurately reproduces low-lying spectra of the 2D Heisenberg model.
These can then be ob- tained from the operator matrices as their traces nor- malized by 1 /N
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Grassmann Variational Monte Carlo with neural wave functions
Grassmann Variational Monte Carlo generalizes neural-network excited-state optimization to subspaces and accurately reproduces low-lying spectra of the 2D Heisenberg model.