ner_tags: O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B-Wavelength I-Wavelength O O O O O O O O O O O O O O O
tokens: arises due to propagating fluctuations in the accretion flow. In this picture, slower fluctuations arise in the outer regions of the flow, and as they propagate inwards, more rapid fluctuations are added. Variability at a given frequency is produced at a characteristic radius, so includes the spectrum produced at that radius, but then it propagates inwards so it is the sum of different spectral components at all radii interior to that where the characteristic frequency of the component is generated. This is shown schematically shown in Fig. 5 , where the sketch is of a gradually stratified flow, with each region contributing a harder spectrum as the radius decreases, rather than the two component model used above. A fundamental assumption of this picture is that smaller radii correspond to harder spectra. We will discuss this in Section 4 . Figure 5. Cartoon picture showing the disc (grey) and regions of the inner accretion flow contributing to each variability component. The cartoon image of Fig. 5 reveals a model-independent way to extract the spectra as a function of radius. By studying the difference between the variability spectra, we can attempt to isolate the spectrum which is characteristic of the radius at which each variability component is produced. As described above, the highest frequencies are expected to be the ‘cleanest’, i.e. only present in the innermost region and thereby modulating the emission from the fewest emission components. This is supported by our result that the spectrum of L 3 is well-fit by a single pure Comptonization component. L 2 has a lower frequency, and it should therefore contain the same contributions as L 3 , as well as emission from larger radii. To isolate the emission in the regions successively further out, we rescaled the L 3 spectrum to match that from L 2 in the highest energy bin (where the contribution is dominated by the innermost region), and then subtracted the L 3 spectrum. This is the maximum contribution from the hard innermost region, so this spectrum is the softest that can be characteristic of the region where L 2 is produced. Similarly, we rescaled and subtracted the spectrum of L 2 from L 1 . The results are shown in Fig. 6 . Figure 6. Spectra of each variability component after subtracting the contribution from higher frequencies (smaller radii). Colours and symbols are the same as in Fig. 2 . While the data points have large uncertainties, some general features can still be distinguished. The spectrum characteristic of the largest radii (red squares) is the softest, and is subtly different to the shape of the soft Comptonization in our two-component fits. The spectrum which can be associated with L 2 (green circles) is appreciably harder than that of L 1 , while that of L 3 is well described by a single hard Comptonization component with high electron temperature and seed photons around a few keV (as above). These results suggest a more complex flow than in our two component model