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Title: Mining the RATS archive for compact blue stars
Author: Satir, Onur
ISNI:       0000 0004 6495 0275
Awarding Body: Queen's University Belfast
Current Institution: Queen's University Belfast
Date of Award: 2017
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In the age of big surveys where torrents of data accumulate with a speed ever increasing, astronomers need to utilise data mining techniques more and more to find their “needles” in these enormous “haystacks”. In this study, 1 set to find the “needles” that we are interested, compact blue objects (CBOs), in our “haystack”, RATS (RApid Temporal Survey). Here, the word “compact” is used in the manner both “very dense” and “very close” as the binaries in discussion have very short periods, therefore very tight orbits, and composed of very dense objects. Discovering, identifying and studying CBOs (especially Ultra-Compact Binaries - UCBs), will help theoreticians to address some of the key outstanding questions in stellar evolution models. Although the overall model of stellar evolution is reasonably understood, there are still many uncertainties and questions which remain. This study is initiated to exploit the RATS dataset, which has light-curves and colour information of more than 3 million stars. Although the main motivation of the RATS project was to discover rare AM CVn systems, which are very short-period (less than ~65 minutes) double degenerate binary systems with helium dominated spectra, one can find all kinds of objects with a wide range of characteristics in the dataset. 1 have searched for CBOs in the data through their colour, and found 2826 blue objects, containing 384 UCB candidate. We obtained spectra for 17 of these objects using GTC (Grand Telescopio Canarias). The spectral identification resulted in 3 extremely He-rich sdOs, 3 sdBs and 2 B-type (sub)dwarfs, 2 sdOs, 2 DA white dwarfs, 2 QSOs and 3 possible subdwarf and cool dwarf binary systems. As the extremely He-rich sdOs are as rare as AM CVns, we obtained high resolution UVES spectra of two of them and analysed these objects in detail. Finally, I have identified blue variable objects in the RATS archive, and revealed their nature using their colours, light-curves and spectra.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available