Characterizing black hole variability with nonlinear methods: the case of the X-ray Nova 4U 1543-47

TL;DR

This study applies nonlinear analysis techniques to X-ray light curves of the black hole binary 4U 1543-47, revealing spectral state-dependent variability characteristics and detecting nonlinearity only in the very high state, challenging existing models.

Contribution

It introduces the weighted scaling index method to characterize black hole variability and demonstrates its effectiveness in distinguishing spectral states and identifying nonlinearity.

Findings

Weighted scaling index uniquely characterizes spectral states.

Variability is linear in all states except the very high state.

Nonlinearity detection suggests limitations of linear models for QPOs.

Abstract

We investigate the possible nonlinear variability properties of the black hole X-ray nova 4U1543-47 to complement the temporal studies based on linear techniques, and to search for signs of nonlinearity in Galactic black hole (GBH) light curves. First, we apply the weighted scaling index method (WSIM) to characterize the X-ray variability properties of 4U1543-47 in different spectral states during the 2002 outburst. Second, we use surrogate data to investigate whether the variability is nonlinear in any of the different spectral states. The main findings can be summarized as follows. The mean weighted scaling index appears to be able to parametrize uniquely the temporal variability properties of this GBH: the 3 different spectral states of the 2002 outburst of 4U1543-47 are characterized by different and well constrained values. The search for nonlinearity reveals that the variability is linear in all light curves with the notable exception of the very high state. Our results imply that we can use the WSIM to assign a single number, namely the mean weighted scaling index, to a light curve, and in this way discriminate among the different spectral states of a source. The detection of nonlinearity in the VHS, that is characterized by the presence of most prominent QPOs, suggests that intrinsically linear models which have been proposed to account for the low frequency QPOs in GBHs may be ruled out (abridged).