AGN Variability in the UKIDSS Ultra Deep Survey

Elmer, Elizabeth (2021) AGN Variability in the UKIDSS Ultra Deep Survey. PhD thesis, University of Nottingham.

PDF (This is the corrected version of my thesis) (Thesis - as examined) - Requires a PDF viewer such as GSview, Xpdf or Adobe Acrobat Reader
Available under Licence Creative Commons Attribution.
Download (7MB) | Preview


One of the defining characteristics of Active Galactic Nuclei (AGN) is the variations observed in their fluxes. In this thesis, we present the first attempt to select AGN using long-term near-infrared (NIR) variability. By analysing the K-band light curves of all the galaxies in the UKIDSS Ultra Deep Survey (UDS), the deepest NIR survey over ~1 sq degree, we have isolated 393 variable AGN candidates. In order to minimise any contamination, known galactic stars were removed from the catalogue before the selection was run, and we took care to suppress any spurious variations due to atmospheric seeing. A comparison to other selection techniques shows that only half of the variable sources are also selected using either deep Chandra X-ray imaging or IRAC colour selection, suggesting that using NIR variability can locate AGN that are missed by more standard selection techniques. In particular, we find that long-term K-band variability identifies AGN at low luminosities and in host galaxies with low stellar masses, many of which appear relatively X-ray quiet.

We then present how the variability selection can be extended to also select AGN from analysis of the J-band light curves. Through this analysis, we showed that a further population of AGN is found using this bluer waveband. When this new sample is combined with those selected in the K-band, we select a total of 595 variable AGN: 177 of these are selected as variable in both bands, 230 are only variable in the J-band, and 188 are only variable in the K-band. By comparing these three populations of AGN, we discovered that their host galaxies have systematically different properties. In general, those detected as variable in both bands are bright, quasar-like AGN, those selected in J are hosted in bluer galaxies, and the K-band only sample have redder, more passive galaxy colours. In particular, a subset of variables only selected in the K-band have properties consistent with dust-obscured AGN.

Once we had obtained this combined sample of AGN that vary in the NIR, we went on to examine the light curves themselves. Information on the structure around AGN has long been derived from measuring lags in their varying light output at different wavelengths. In most accretion disk models we predict that the infrared light emerges further from the central black hole than the optical light, potentially even probing reprocessed radiation in any surrounding dusty torus. In practice, this has proved challenging because high quality data are required to detect such variability, and the observations must stretch over a long period to probe the likely month-scale lags in variability. In addition, large numbers of sources would need to be observed to start searching for any patterns in such lags. Here, we show that the UDS, built up from repeated observations over almost a decade, provides an ideal data set for such a study. For 96 sources identified as strongly-varying AGN within its square-degree field, we find that the K-band light curves systematically lag the J-band light curves by an average of around a month. The lags become smaller at higher redshift, consistent with the band shift to optical rest-frame emission. The less luminous AGN also display shorter lags, as would be expected if their physical size scales with luminosity.

Item Type: Thesis (University of Nottingham only) (PhD)
Supervisors: Almaini, Omar
Merrifield, Michael
Keywords: Active Galactic Nuclei, AGN, near-infrared (NIR) variability, galaxies
Subjects: Q Science > QB Astronomy
Faculties/Schools: UK Campuses > Faculty of Science > School of Physics and Astronomy
Item ID: 66187
Depositing User: Elmer, Elizabeth
Date Deposited: 31 Dec 2021 04:40
Last Modified: 31 Dec 2021 04:40

Actions (Archive Staff Only)

Edit View Edit View