Astronomy and Astrophysics – Astronomy
Scientific paper
May 2005
adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2005aas...206.1102t&link_type=abstract
American Astronomical Society Meeting 206, #11.02; Bulletin of the American Astronomical Society, Vol. 37, p.445
Astronomy and Astrophysics
Astronomy
Scientific paper
X-ray variability is a common characteristic of Active Galactic Nuclei (AGN), and it can be used to probe the nuclear region at short time scales. Quantitative analysis of this variability has been difficult due to low signal-to-noise ratios and short time baselines, but serendipitous Chandra data acquired within the last six years have opened the door to such analysis. Cross-correlation of the Chandra archives with QSO/AGN catalogs on NASA's HEASARC website (e.g. Veron, Sloan) yields a sample of 50+ objects that satisfy the following criteria: absolute magnitude M≤ -22.5, proper time baselines greater than 2 hours, and count rates leading to 10% error bars for 8+ flux points on the light curve. The sample includes a range of red-shifts, magnitudes, and type (e.g. radio loud, radio quiet), and hence may yield empirical clues about luminosity or evolutionary trends. As a beginning of such analysis, we present 11 light curves for 9 objects for which the exposure time was greater than 10 hours. The variability was analyzed using three different statistical methods. The Kolmogorov-Smirnov (KS) test proved to be impractical because of the unavoidably small number of data points and the simplistic nature of the test. A χ2 test indicated in most cases that there were significant departures from constant brightness (as expected). Autocorrelation plots were also generated for each light curve. With more work and a larger sample size, these plots can be used to identify any trends in the lightcurve such as whether the variability is stochastic or periodic in nature. This test was useful even with the small number of datapoints available. In future work, more sophisticated analyses based on Fourier series, power density spectra, or wavelets are likely to yield more meaningful and useful results.
Busche J.
Tartamella C.
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