TY - THES A1 - Gholami Ghadikolaei, Iraj T1 - Data analysis of continuous gravitational waves T1 - Daten Analyse der kontinuierlichen Gravitationswellen N2 - This thesis describes two main projects; the first one is the optimization of a hierarchical search strategy to search for unknown pulsars. This project is divided into two parts; the first part (and the main part) is the semi-coherent hierarchical optimization strategy. The second part is a coherent hierarchical optimization strategy which can be used in a project like Einstein@Home. In both strategies we have found that the 3-stages search is the optimum strategy to search for unknown pulsars. For the second project we have developed a computer software for a coherent Multi-IFO (Interferometer Observatory) search. To validate our software, we have worked on simulated data as well as hardware injected signals of pulsars in the fourth LIGO science run (S4). While with the current sensitivity of our detectors we do not expect to detect any true Gravitational Wave signals in our data, we can still set upper limits on the strength of the gravitational waves signals. These upper limits, in fact, tell us how weak a signal strength we would detect. We have also used our software to set upper limits on the signal strength of known isolated pulsars using LIGO fifth science run (S5) data. N2 - Diese Dissertation besteht aus zwei Projekten: Im ersten Projekt wird die Optimierung einer hierarchischen Strategie zum Auffinden von 'unbekannten' Pulsaren beschrieben. Der erste Teil besteht dabei aus einer semi-kohärenten und der zweite Teil aus einer kohärenten Optimierungsstrategie, wie sie in Projekten wie Einstein@Home verwendet werden kann. In beiden Ansätzen erwies sich eine 3-Stufensuche als optimale Suchstrategie für 'unbekannte' Pulsare. Für das zweite Projekt entwickelten wir eine Software für eine kohärente Multi-IFO (Interferometer Observatory) Suche. Zum Validieren der Software verwendeten wir sowohl simulierte Daten als auch Hardware induzierte Signale von Pulsaren aus dem vierten 'LIGO Science run' (S4). Wir erwarten nicht, mit der aktuellen Empfindlichkeit unserer Detektoren echte GW- Signale aufzunehmen, können jedoch obere Grenzen für die Stärke der Gravitationswellen-Signale bestimmen. Diese oberen Grenzen geben uns an, wie schwach ein gerade noch detektierbares Signal werden kann. Ferner benutzten wir die Software um eine obere Grenze für bekannte, isolierte Pulsare zu bestimmen, wobei wir Daten aus dem fünften 'LIGO Science run (S5) verwendeten. KW - Daten Analyse KW - Gravitationswellen KW - Upper Limit KW - Gravitational Wave KW - data analysis KW - Upper Limit Y1 - 2007 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus-18800 ER - TY - THES A1 - Thiel, Marco T1 - Recurrences : exploiting naturally occurring analogues N2 - In der vorliegenden Arbeit wird die Wiederkehr im Phasenraum ausgenutzt. Dabei werden drei Hauptresultate besprochen. 1. Die Wiederkehr erlaubt die Vorhersagbarkeit des Systems zu quantifizieren. 2. Die Wiederkehr enthaelt (unter bestimmten Voraussetzungen) sämtliche relevante Information über die Dynamik im Phasenraum 3. Die Wiederkehr erlaubt die Erzeugung dynamischer Ersatzdaten. N2 - Recurrence plots, a rather promising tool of data analysis, have been introduced by Eckman et al. in 1987. They visualise recurrences in phase space and give an overview about the system's dynamics. Two features have made the method rather popular. Firstly they are rather simple to compute and secondly they are putatively easy to interpret. However, the straightforward interpretation of recurrence plots for some systems yields rather surprising results. For example indications of low dimensional chaos have been reported for stock marked data, based on recurrence plots. In this work we exploit recurrences or ``naturally occurring analogues'' as they were termed by E. Lorenz, to obtain three key results. One of which is that the most striking structures which are found in recurrence plots are hinged to the correlation entropy and the correlation dimension of the underlying system. Even though an eventual embedding changes the structures in recurrence plots considerably these dynamical invariants can be estimated independently of the special parameters used for the computation. The second key result is that the attractor can be reconstructed from the recurrence plot. This means that it contains all topological information of the system under question in the limit of long time series. The graphical representation of the recurrences can also help to develop new algorithms and exploit specific structures. This feature has helped to obtain the third key result of this study. Based on recurrences to points which have the same ``recurrence structure'', it is possible to generate surrogates of the system which capture all relevant dynamical characteristics, such as entropies, dimensions and characteristic frequencies of the system. These so generated surrogates are shadowed by a trajectory of the system which starts at different initial conditions than the time series in question. They can be used then to test for complex synchronisation. T2 - Recurrences : exploiting naturally occurring analogues KW - Wiederkehrdiagramme KW - Rekurrenzen KW - Datenanalyse KW - Surrogates KW - recurrence plots KW - recurrences KW - data analysis KW - surrogates Y1 - 2004 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-0001633 ER -