Zhichen Pu

Towards a Universally Transferable Acceleration Method for Density Functional Theory

Recently, sophisticated deep learning-based approaches have been developed for generating efficient initial guesses to accelerate the convergence of density functional theory (DFT) calculations. While the actual initial guesses are often density matrices (DM), quantities that can convert into densit…