P. Henneberger

Bio: P. Henneberger is an academic researcher from Dresden University of Technology. The author has contributed to research in topics: Automatic differentiation & Stiff equation. The author has an hindex of 1, co-authored 1 publications receiving 31 citations.

High-Order Stiff ODE Solvers via Automatic Differentiation and Rational Prediction

Abstract: A class of higher order methods is investigated which can be viewed as implicit Taylor series methods based on Hermite quadratures. Improved automatic differentiation techniques for the claculation of the Taylor-coefficients and their Jacobians are used. A new rational predictor is used which can allow for larger step sizes on stiff problems.

Solving Ordinary Differential Equations

Abstract: Initial-value ordinary differential equation solution via variable order Adams method (SIVA/DIVA) package is collection of subroutines for solution of nonstiff ordinary differential equations. There are versions for single-precision and double-precision arithmetic. Requires fewer evaluations of derivatives than other variable-order Adams predictor/ corrector methods. Option for direct integration of second-order equations makes integration of trajectory problems significantly more efficient. Written in FORTRAN 77.

Automatic Differentiation Of Algorithms: From Simulation To Optimization

Abstract: Automatic Differentiation (AD) is a maturing computational technology. It has become a mainstream tool used by practicing scientists and computer engineers. The rapid advance of hardware computing power and AD tools has enabled practitioners to generate derivative enhanced versions of their code for a broad range of applications in applied research and development. Automatic Differentiation of Algorithms provides a comprehensive and authoritative survey of all recent developments, new techniques, and tools for AD use.

A Software Package for the Numerical Integration of ODEs by Means of High-Order Taylor Methods

Abstract: This paper revisits the Taylor method for the numerical integration of initial value problems of Ordinary Differential Equations (ODEs). The main goal is to present a computer program that outputs a specific numerical integrator for a given set of ODEs. The generated code includes a function to compute the jet of derivatives of the solution up to a given order plus adaptive selection of order and step size at run time. The package provides support for several extended precision arithmetics, including user-defined types. The paper discusses the performance of the resulting integrator in some examples, showing that it is very competitive in many situations. This is especially true for integrations that require extended precision arithmetic. The main drawback is that the Taylor method is an explicit method, so it has all the limitations of these kind of schemes. For instance, it is not suitable for stiff systems.

Computing rigorous bounds on the solution of an initial value problem for an ordinary differential equation

Abstract: Compared to standard numerical methods for initial value problems (IVPs) for ordinary differential equations (ODEs), validated (also called interval) methods for IVPs for ODEs have two important advantages: if they return a solution to a problem, then (1) the problem is guaranteed to have a unique solution, and (2) an enclosure of the true solution is produced. To date, the only effective approach for computing guaranteed enclosures of the solution of an IVP for an ODE has been interval methods based on Taylor series. This thesis derives a new approach, an interval Hermite-Obreschkoff (IHO) method, for computing such enclosures. Compared to interval Taylor series (ITS) methods, for the same order and stepsize, our IHO scheme has a smaller truncation error and better stability. As a result, the IHO method allows larger stepsizes than the corresponding ITS methods, thus saving computation time. In addition, since fewer Taylor coefficients are required by IHO than ITS methods, the IHO method performs better than the ITS methods when the function for computing the right side contains many terms. The stability properties of the ITS and IHO methods are investigated. We show as an important by-product of this analysis that the stability of an interval method is determined not only by the stability function of the underlying formula, as in a standard method for an IVP for an ODE, but also by the associated formula for the truncation error. This thesis also proposes a Taylor series method for validating existence and uniqueness of the solution, a simple stepsize control, and a program structure appropriate for a large class of validated ODE solvers.