Hi all,

Tomorrow Tere will talk at group meeting. See below for the title and abstract.

Best,

Ian

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Automatic Differentiation in Quantum Chemistry: Gaussian Basis Set Optimization

Abstract: The calculation of derivatives are present in most of the Quantum Chemistry algorithms. Often the analytical form and implementation of derivatives is a daunting task. Automatic Differentiation offers a way to get derivatives easier by reusing the code to compute the function with an accuracy of machine precision. In this talk, I will discuss how to use this tool to get gradients of the Hartree-Fock energy of all the variables included in the Gaussian basis set, exponents, and localization of the center of them. And, we will see the advantages and disadvantages of some Automatic Differentiation libraries to do this duty, specifically, TensorFlow, algopy, and autograd.