Investigation of the bar structure in our galaxy
2022
0 views
0 downloads
Advisor: Doç. Dr. Esma Yaz Gökçe
Abstract (EN)
The Galaxy we live in contains many structures. Even if these structures were discovered half a century ago, how they were formed, how they evolve and their structural parameters are not well-known. To reveal the structure of our Galaxy, it is important to have a good understanding of all these structures. The Galactic bar is one of these structures. It was thought that the Galactic bar structure plays an important role in the formation of warping and flaring in the Galaxy. Investigating the bar structure is important for understanding of the formation and evolution of the Milky Way. Therefore, the PhD thesis is made use of the most recent and precise infrared photometric data (WISE, VVV, and UKIDSS) that allow us to observe distant sources in the Galactic plane, where the total extinction is maximum. In the thesis, the distance of the Sun from the center of the Galaxy using the red clump stars, the position angle of the bar structure, the half-length of the bar, half-length of the bulge are estimated R0 = 8.0±0.5 kpc, φ = 39.4°±0.8°, rbar = 4.1 ± 0.1 kpc, and rbulge = 3.0±0.2 kpc, respectively. Since the results found in the thesis were obtained using more accurate and big data, an important contribution has been made to the literature.
Author
Dr. Şivan Duran
How to Cite
Şivan Duran (Doctorate thesis). Investigation of the bar structure in our galaxy, 2022, İstanbul University.
License
Tüm Hakları Saklıdır
This work is shared under the specified license terms.
More theses from İstanbul University
- In the covid 19 pandemic of female employees at a university hospital attitudes and affecting factors in nutrition of 9 months-6 years old children(2022)
- The perception of the right-wing movements in Turkey as to the 27 May Coup: 1960-1980(2020)
- Economic and social life in the Ottoman Empire according to the 1890 year's news of La Turquie Newspaper(2022)
- Land regime in the Umayyads period(2022)
- Merkel hücreli karsinomda tanısal ve prognostik belirteçler(2022)
- Use of machine learning methods in classification of respiratory system diseases(2021)