Unravelling accretion flows in AGN and binaries using their complex variability patterns

Lead Research Organisation: University of Southampton
Department Name: Sch of Physics and Astronomy

Abstract

Accretion onto black holes proceeds according to a well observed phenomenology, however, little of the details are presently well understood. One of the least understood aspects is the prevalence and nature of high frequency quasi-periodic oscillations (QPOs), seen at high accretion rates in black hole binaries (BHBs) and only two active galactic nuclei (AGN). The frequency of these QPOs indicates that they likely originate in the region of strong gravity close to the black hole, where effects of general relativity are dominant. Given the mass scaling of the QPO frequencies, AGN allow for a much better (protracted) view of these QPOs yet are extreme rarities. Part 1 of the project is to search the XMM-Newton datasets of the brightest AGN (the PG QSOs) for QPO candidates by energy-slicing the data and by applying a new algorithm to detect coherent signals in noisy data. This technique will also be extended to the vast archives on BHBs (principally RXTE) in an effort to discover more QPOs, understand their prevalence and the nature of the sources when they appear. The latter part of the project will also involve use of the covariance spectrum to unravel how changes in the underlying components of emission may be responsible for the appearance of these QPOs.

Publications

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Studentship Projects

Project Reference Relationship Related To Start End Student Name
ST/R505080/1 01/10/2017 30/09/2021
1952894 Studentship ST/R505080/1 01/10/2017 31/07/2021 Dominic Ashton
 
Title QPO Statistical Analysis Framework 
Description A fully automated, parallel processed, python script to execute statistical tests upon energy-resolved XMM-Newton observational datasets -- from a sample of active galactic nuclei. The framework computes the statistical significance of periodic features (quasi-periodic oscillations) in the Fourier domain, as a test of X-ray variability in AGN. 
Type Of Material Data analysis technique 
Year Produced 2019 
Provided To Others? No  
Impact The discovery of several statistically significant QPO candidates, taking the total known sample from 2 to 7. This has wide implications for the field of understanding accretion flows in AGN.