Identification of Spines in Nonlinear Fourier Spectra for the Periodic Nonlinear Schrödinger Equation

Internship WI5118 - Report

Student Report (2022)
Author(s)

C. Kitsios (TU Delft - Electrical Engineering, Mathematics and Computer Science)

Contributor(s)

S. Wahls – Mentor (TU Delft - Team Sander Wahls)

Faculty
Electrical Engineering, Mathematics and Computer Science
Copyright
© 2022 Christos Kitsios
More Info
expand_more
Publication Year
2022
Language
English
Copyright
© 2022 Christos Kitsios
Graduation Date
02-03-2022
Awarding Institution
Delft University of Technology
Programme
['Applied Mathematics']
Faculty
Electrical Engineering, Mathematics and Computer Science
Reuse Rights

Other than for strictly personal use, it is not permitted to download, forward or distribute the text or part of it, without the consent of the author(s) and/or copyright holder(s), unless the work is under an open content license such as Creative Commons.

Abstract

The nonlinear Fourier transform for the focusing
periodic nonlinear Schrodinger equation is investigated. This paper is focused
on the approximation of the spines in the nonlinear spectrum using results from
Floquet theory. Algorithms for the numerical computation of the spines based on
the Fourier collocation method are being examined and a new algorithm is
presented. The new algorithm developed during the project computes the spines
by tracking sign changes of the function ς=(Δ(.)) in the area ℜ<( Δ (.))| < 1, where delta is the Floquet discriminant. The new algorithm is
successfully applied to examples where both the modified Fourier collocation
method and the method implemented in the FNFT software library fail. In
addition, the spine points that are numerically computed by the new algorithm
are equally distributed along the curve, while using the other algorithms the
computed points are clustered around the periodic eigenvalues. Finally, the
algorithm provides information on which spectrum points belong to the same
spine. The pseudocode and the MATLAB source code of the algorithm developed are
provided.



Files

Report_C._Kitsios.pdf
(pdf | 1.36 Mb)
License info not available