Speaker
Description
Variable stars are stars whose brightness varies with time when observed from Earth. The change in brightness may
be due to changes in star’s luminosity, and obstructions in the amount of light that reaches Earth. Studying variable
stars helps understand stellar evolution and properties. The project aims to search for and classify variable stars using
photometric time-series data from the Kepler database. By applying Fourier analysis, it seeks to identify variability
periods and classify stars based on their frequency spectra. The ultimate goal is to determine their physical properties,
including luminosities, absolute magnitudes, and distances, contributing to a deeper understanding of stellar variability
and its implications for stellar astrophysics. The data utilized in this paper is from K2 database (Mikulski Archive
Space Telescope) which was published by the Nainitial-Cape survey stars. A total of eight stars were retrieved from
the K2 database (Mikulski Archive for Space Telescopes). Each star was analyzed to determine the underlying cause
of its variability and to identify potential associations with known variable stars. Light curves were examined for
distinct varability patterns, and Fourier analysis was performed to extract amplitude and frequency values, allowing
for precise determination of each star’s variation period. Additionally, the spectral classification of each star from the
literature was utilized to correlate observed variability with previously identified variable stars. The calculated periods
facilitated distinguishing between variability due to stellar pulsation or rotation, based on whether the periods exceeded
the typical pulsation period for each star’s spectral type. Noise reduction, including prewhitening, was applied to all
data sets to extract other frequencies of significant amplitudes. Results confirmed that the observed variability across
the sample could be attributed to either pulsation or rotational phenomena. This research successfully achieved its
objective of identifying and categorizing variable stars using photometric data from the Kepler database. Among the
eight stars analyzed, three variable stars were identified and classified as Delta Scuti, Cepheids, and RV Tauri types.
These findings contribute to the growing catalog of known variable stars and provide a foundation for future studies
on their physical and evolutionary properties
| Apply for student award at which level: | Honours |
|---|---|
| Consent on use of personal information: Abstract Submission | Yes, I ACCEPT |
