Section: Application Domains

Automatic Differentiation

Automatic Differentiation of programs gives sensitivities or gradients, that are useful for many types of applications:

• optimum shape design under constraints, multidisciplinary optimization, and more generally any algorithm based on local linearization,

• inverse problems, such as parameter estimation and in particular 4Dvar data assimilation in climate sciences (meteorology, oceanography),

• first-order linearization of complex systems, or higher-order simulations, yielding reduced models for simulation of complex systems around a given state,

• mesh adaptation and mesh optimization with gradients or adjoints,

• equation solving with the Newton method,

• sensitivity analysis, propagation of truncation errors.