• Corpus ID: 235367854

Using differentiable programming to obtain an energy and density-optimized exchange-correlation functional

@inproceedings{Dick2021UsingDP,
  title={Using differentiable programming to obtain an energy and density-optimized exchange-correlation functional},
  author={Sebastian Dick and Marivi Fern{\'a}ndez-Serra},
  year={2021}
}
Using an end-to-end differentiable implementation of the Kohn-Sham self-consistent field equations, we obtain an accurate neural network-based exchange and correlation (XC) functional of the electronic density. The functional is optimized using information on both energy and density while exact constraints are enforced through an appropriate neural network architecture. We evaluate our model against different families of XC approximations and show that, for non-empirical functionals, there is a… 
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