Revisiting algorithms for generating surrogate time series

The method of surrogates is one of the key concepts of nonlinear data analysis. Here, we demonstrate that commonly used algorithms for generating surrogates often fail to generate truly linear time series. Rather, they create surrogate realizations with Fourier phase correlations leading to non-detections of nonlinearities. We argue that reliable surrogates can only be generated, if one tests separately for static and dynamic nonlinearities.

Search for non-Gaussianities in the WMAP data with the Scaling Index Method

In the recent years, non-Gaussianity and statistical isotropy of the Cosmic Microwave Background (CMB) was investigated with various statistical measures, first and foremost by means of the measurements of the WMAP satellite. In this Review, we focus on the analyses that were accomplished with a measure of local type, the so-called Scaling Index Method (SIM). The SIM is able to detect structural characteristics of a given data set, and has proven to be highly valuable in CMB analysis. It was used for comparing the data set with simulations as well as surrogates, which are full sky maps generated by randomisation of previously selected features of the original map. During these investigations, strong evidence for non-Gaussianities as well as asymmetries and local features could be detected. In combination with the surrogates approach, the SIM detected the highest significances for non-Gaussianity to date.

Scale-dependent non-Gaussianities in the WMAP data as identified by using surrogates and scaling indices

We present a model-independent investigation of the WMAP data with respect to scale- dependent non-Gaussianities (NGs) by employing the method of constrained randomization. For generating so-called surrogate maps a shuffling scheme is applied to the Fourier phases of the original data, which allows to test for the presence of higher order correlations (HOCs) on well-defined scales. Using scaling indices as test statistics we find highly significant signatures for non-Gaussianities when considering all scales. We test for NGs in the bands l = [2,20], l = [20,60], l = [60,120] and l = [120,300]. We find highly significant signatures for non-Gaussianities and ecliptic hemispherical asymmetries for l = [2, 20]. We also obtain highly significant deviations from Gaussianity for the band l = [120,300]. The result for the full l-range can be interpreted as a superposition of the signatures found in the bands l = [2, 20] and l = [120, 300]. We find remarkably similar results when analyzing different ILC-like maps. We perform a set of tests to investigate if the detected anomalies can be explained by systematics. While no test can convincingly rule out the intrinsic nature of the anomalies for the low l case, the ILC map making procedure and/or residual noise in the maps can also lead to NGs at small scales. Our investigations prove that there are phase correlations in the WMAP data of the CMB. In the absence of an explanation in terms of Galactic foregrounds or known systematic artefacts, the signatures at low l must so far be taken to be cosmological at high significance. These findings strongly disagree with predictions of isotropic cosmologies with single field slow roll inflation. The task is now to elucidate the origin of the phase correlations and to understand the physical processes leading to these scale-dependent non-Gaussianities - if systematics as cause for them must be ruled out.

Probing non-Gaussianities on Large Scales in WMAP5 and WMAP7 Data using Surrogates

Probing Gaussianity represents one of the key questions in modern cosmology, because it allows to discriminate between different models of inflation. We test for large-scale non-Gaussianities in the cosmic microwave background (CMB) in a model-independent way. To this end, so-called first and second order surrogates are generated by first shuffling the Fourier phases belonging to the scales not of interest and then shuffling the remaining phases for the length scales under study. Using scaling indices as test statistics we find highly significant signatures for both non-Gaussianities and asymmetries on large scales for the WMAP data of the CMB. We find remarkably similar results when analyzing different ILC-maps based on the WMAP five and seven year data. Such features being independent from the map-making procedure would disfavor the fundamental principle of isotropy as well as canonical single-field slow-roll inflation - unless there is some undiscovered systematic error in the collection or reduction of the CMB data or yet unknown foreground contributions.

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

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).

Non-Gaussian Signatures in the five-year WMAP data as identified with isotropic scaling indices

We continue the analysis of non-Gaussianities in the CMB by means of the scaling index method (SIM, Raeth, Schuecker & Banday 2007) by applying this method on the 5-year WMAP data. We compare each of the results with 1000 Monte Carlo simulations mimicing the Gaussian properties of the best fit $Lambda CDM$-model. Based on the scaling indices, scale-dependent empirical probability distributions, moments of these distributions and $chi^2$-combinations of them are calculated, obtaining similar results as in the former analysis of the 3-year data: We derive evidence for non-Gaussianity with a probability of up to 97.3% for the mean when regarding the KQ75-masked full sky and summing up over all considered length scales by means of a diagonal $chi^2$-statistics. Looking at only the northern or southern hemisphere, we obtain up to 98.5% or 96.6%, respectively. For the standard deviation, these results appear as 95.6% for the full sky (99.7% north, 89.4% south) and for a $chi^2$-combination of both measurements as 97.4% (99.1% north, 95.5% south). By performing an analysis of rotated hemispheres, we detect an obvious asymmetry in the data. In addition to these investigations, we present a method of filling the mask with Gaussian noise to eliminate boundary effects caused by the mask. With the help of this technique, we identify several local features on the map, of which the most significant one turns out to be the well-known cold spot. When excluding all these spots from the analysis, the deviation from Gaussianity increases, which shows that the discovered local anomalies are not the reason of the global detection of non-Gaussianity, but actually were damping the deviations on average. Our analyses per band and per year suggest, however, that it is very unlikely that the detected anomalies are due to foreground effects.

A model-independent test for scale-dependent non-Gaussianities in the CMB

We present a model-independent method to test for scale-dependent non-Gaussianities in combination with scaling indices as test statistics. Therefore, surrogate data sets are generated, in which the power spectrum of the original data is preserved, while the higher order correlations are partly randomised by applying a scale-dependent shuffling procedure to the Fourier phases. We apply this method to the WMAP data of the cosmic microwave background (CMB) and find signatures for non-Gaussianities on large scales. Further tests are required to elucidate the origin of the detected anomalies.