Grassmann Variational Monte Carlo generalizes neural-network excited-state optimization to subspaces and accurately reproduces low-lying spectra of the 2D Heisenberg model.
For a Hermitian operator ˆA and basis Φ of V, the OVM corresponds to eΣ(A)(Φ) = eA(2)(Φ) − eA2(Φ), where eA(2) denotes the OEM for ˆA2 and eA2 = eA · eA
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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.