The complex-step derivative approximation
University of Toronto · Stanford University
Abstract
The complex-step derivative approximation and its application to numerical algorithms are presented. Improvements to the basic method are suggested that further increase its accuracy and robustness and unveil the connection to algorithmic differentiation theory. A general procedure for the implementation of the complex-step method is described in detail and a script is developed that automates its implementation. Automatic implementations of the complex-step method for Fortran and C/C++ are presented and compared to existing algorithmic differentiation tools. The complex-step method is tested in two large multidisciplinary solvers and the resulting sensitivities are compared to results given by finite…
Citation impact
- FWCI
- 10.42
- Percentile
- 100%
- References
- 34
Authors
3Topics & keywords
- Automatic differentiation
- Maintainability
- Robustness (evolution)
- Computer science
- Implementation
- Fortran
- Python (programming language)
- Algorithm