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.
This method has been shown to be effective in representing continuous signals and complex function mappings in the context of implicit neural representations [192]
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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.