Principal component analysis of the x-ray spectra of blazars

Abstract

Principal Component Analysis (PCA) is applied to a variety of blazars to examine X-ray spectral variability. Data from nine different objects are analysed in two ways: long-term, which examines variability trends across years or decades, and short-term, which looks at variability within a single observation. The results are then compared to simulated spectra in order to identify the physical components that they correspond to. It is found that long-term variability for all objects is dominated by changes in a single power law component. The primary component is responsible for more than 84 per cent of the variability in every object, while the second component is responsible for at least 3 per cent. Short-term variability is less clear-cut, with no obvious physical analogue for some of the PCA results. We discuss the simulation process, and specifically remark on the consequences of the breakdown of the linearity assumption of PCA and how it manifests in the real data.