Introduces representability-aware neural networks for predicting and variationally optimizing 2-RDMs, achieving high accuracy and competitive energies versus exact diagonalization in a fractional Chern insulator model of twisted bilayer MoTe2.
We use (i) R-value accuracy and (ii) normalized overlap, as scores defining the NN accuracy at predicting the large-sizen-RDM
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Representability-Aware Neural Networks for Reduced Density Matrices: Application to Fractional Chern Insulators
Introduces representability-aware neural networks for predicting and variationally optimizing 2-RDMs, achieving high accuracy and competitive energies versus exact diagonalization in a fractional Chern insulator model of twisted bilayer MoTe2.