On the nature of the variability power decay towards soft spectral states in X-ray binaries. Case study in Cyg X-1

Astronomy and Astrophysics – Astrophysics

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X-Ray Sources, X-Ray Bursts, Black Holes, Accretion And Accretion Disks, Luminosities, Magnitudes, Effective Temperatures, Colors, And Spectral Classification

Scientific paper

A characteristic feature of the Fourier Power Density Spectrum (PDS) observed from black hole X-ray binaries in low/hard and intermediate spectral states is a broad band-limited noise, characterized by a constant below some frequency (a ``break'' frequency) and a power law above this frequency. It has been shown that the variability of this type can be produced by the inward diffusion of the local driving perturbations in a bounded configuration (accretion disk or corona). In the framework of this model, the perturbation diffusion time t0 is related to the phenomenological break frequency, while the PDS power-law slope above the ``break'' is determined by the viscosity distribution over the configuration. The perturbation diffusion scenario explains the decay of the power of X-ray variability observed in a number of compact sources (containing black hole and neutron star) during an evolution of theses sources from low/hard to high/soft states. We compare the model predictions with the subset of data from Cyg X-1 collected by the Rossi X-ray Time Explorer (RXTE). Our extensive analysis of the Cyg X-1 PDSs demonstrates that the observed integrated power Px decreases approximately as a square root of the characteristic frequency of the driving oscillations νdr. The RXTE observations of Cyg X-1 allow us to infer Pdr and t0 as a function of νdr. Using the inferred dependences of the integrated power of the driving oscillations Pdr and t0 on νdr we demonstrate that the power predicted by the model also decays as Px,diff~νdr-0.5 that is similar to the observed Px behavior. We also apply the basic parameters of observed PDSs, power-law index and low frequency quasiperiodic oscillations, to infer Reynolds (Re) number from the observations using the method developed in our previous paper. Our analysis shows that Re-number increases from values about 10 in low/hard state to that about 70 during the high/soft state.

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