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A Population of Short-Period Variable Quasars from PTF as Supermassive Black Hole Binary Candidates

Supermassive black hole binaries (SMBHBs) are the natural consequence of galaxy mergers and should form frequently in galactic nuclei. Especially at sub-parsec separations, where the binary evolution is slow, SMBHBs should be fairly abundant. However, the observational evidence remains elusive.
In this thesis, we focus on periodic variability of quasars as a potential signature of compact SMBHBs. First, we present a systematic search for periodic variability in the photometric database of the Palomar Transient Factory. Our search in a large sample of ~35,000 quasars returned 50 candidates, 33 of which remain significant after the reanalysis of extended light curves including data from the Catalina Real-Time Transient Survey and the intermediate PTF. Our candidates have periods of a few hundred days.
Next, we focus on independent signatures that could verify the binary nature of the candidates. We present a case study of quasar PKS 1302-102, the first candidate that emerged from the large time-domain surveys. We search for multiple periodic components in the variability with a characteristic frequency pattern predicted by hydrodynamical simulations of circumbinary disks. We do not find compelling evidence for a secondary period.
Additionally, in compact SMBHBs, relativistic Doppler boost should be significant and may dominate the variability. This model was suggested as a smoking-gun signature for quasar PKS 1302-102, since it is not expected in quasars with a single BH and it offers a robust prediction, which can be tested with multi-wavelength data. With a control sample of non-periodic quasars, we test whether this signature is distinct from the intrinsic multi-wavelength variability of quasars. We concluded that the Doppler boost does not provide a sharp test for SMBHBs.

Identiferoai:union.ndltd.org:columbia.edu/oai:academiccommons.columbia.edu:10.7916/D88S52C3
Date January 2017
CreatorsCharisi, Maria
Source SetsColumbia University
LanguageEnglish
Detected LanguageEnglish
TypeTheses

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