Algorithmic differentiation for plane-wave DFT: materials design, error control and learning model parameters
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We present a differentiation framework for plane-wave density-functional theory (DFT) that combines the strengths of forward-mode algorithmic differentiation (AD) and density-functional perturbation theory (DFPT). In the resulting AD-DFPT framework derivatives... ...
