This PhD thesis consists of a summary and seven papers, where various applications of auto-validated computations are studied.In the first paper we describe a rigorous method to determine unknown parameters in a system of ordinary differential equations from measured data with known bounds on the noise of the measurements.Papers II, III, IV, and V are concerned with Abelian integrals. In Paper II, we construct an auto-validated algorithm to compute Abelian integrals. In Paper III we investigate, via an example, how one can use this algorithm to determine the possible configurations of limit cycles that can bifurcate from a given Hamiltonian vector field. In Paper IV we construct an example of a perturbation of degree five of a Hamiltonian vector field of degree five, with 27 limit cycles, and in Paper V we construct an example of a perturbation of degree seven of a Hamiltonian vector field of degree seven, with 53 limit cycles. These are new lower bounds for the maximum number of limit cycles that can bifurcate from a Hamiltonian vector field for those degrees.In Papers VI, and VII, we study a certain kind of normal form for real hyperbolic saddles, which is numerically robust…
Contents
1 Introduction
1.1 Interval analysis
1.2 Automatic diļ¬erentiation
1.3 Some applications
2 Summary of the papers
2.1 PaperI
2.2 PaperII
2.3 PaperIII
2.4 PaperI
2.5 Paper
2.6 PaperVI
2.7 PaperVII
Summary
Acknowledgement
Bibliography
Author: Johnson, Tomas
Source: Uppsala University Library
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