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.
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