Análise das curvas de luz do CoroT usando diferentes processos comparativos: estimando períodos de rotação estelar
One of the main goals of CoRoT Natal Team is the determination of rotation period for thousand of stars, a fundamental parameter for the study of stellar evolutionary histories. In order to estimate the rotation period of stars and to understand the associated uncertainties resulting, for example, f...
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| Formato: | Dissertação |
| Idioma: | por |
| Publicado em: |
Universidade Federal do Rio Grande do Norte
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| Endereço do item: | https://repositorio.ufrn.br/jspui/handle/123456789/16564 |
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| Resumo: | One of the main goals of CoRoT Natal Team is the determination of rotation period
for thousand of stars, a fundamental parameter for the study of stellar evolutionary
histories. In order to estimate the rotation period of stars and to understand the associated
uncertainties resulting, for example, from discontinuities in the curves and (or)
low signal-to-noise ratio, we have compared three different methods for light curves
treatment. These methods were applied to many light curves with different characteristics.
First, a Visual Analysis was undertaken for each light curve, giving a general
perspective on the different phenomena reflected in the curves. The results obtained
by this method regarding the rotation period of the star, the presence of spots, or the
star nature (binary system or other) were then compared with those obtained by two
accurate methods: the CLEANest method, based on the DCDFT (Date Compensated
Discrete Fourier Transform), and the Wavelet method, based on the Wavelet Transform.
Our results show that all three methods have similar levels of accuracy and
can complement each other. Nevertheless, the Wavelet method gives more information
about the star, from the wavelet map, showing the variations of frequencies over time
in the signal. Finally, we discuss the limitations of these methods, the efficiency to
give us informations about the star and the development of tools to integrate different
methods into a single analysis |
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