2012
DOI: 10.1093/mnras/sts056
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Scale-dependent non-Gaussianities in the CMB data identified with Minkowski functionals and scaling indices

Abstract: We present further investigations of the Wilkinson Microwave Anisotropy Probe (WMAP) data by means of the Minkowski functionals and the scaling index method. In order to test for non-Gaussianities (NGs) with respect to scale-dependencies we use so-called surrogate maps, in which possible phase correlations of the Fourier phases of the original WMAP data and the simulations, respectively, are destroyed by applying a shuffling scheme to the maps. A statistical comparison of the original maps with the surrogate m… Show more

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Cited by 18 publications
(27 citation statements)
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“…The dashed (dotted) line indicates the 1 (3) σ significance level. the Planck data, consistent with those obtained previously with WMAP data (for comparison see Modest et al 2013). Figure 25 presents results that allow us to attempt to elucidate the origin of the detected asymmetry and its relationship to other anomalies.…”
Section: Phase Correlationssupporting
confidence: 86%
See 1 more Smart Citation
“…The dashed (dotted) line indicates the 1 (3) σ significance level. the Planck data, consistent with those obtained previously with WMAP data (for comparison see Modest et al 2013). Figure 25 presents results that allow us to attempt to elucidate the origin of the detected asymmetry and its relationship to other anomalies.…”
Section: Phase Correlationssupporting
confidence: 86%
“…Previous studies using these methods, based on the WMAP three-, five-and seven-year data (Räth et al 2009(Räth et al , 2011Rossmanith et al 2012;Modest et al 2013), showed significant evidence for intrinsic phase correlations at low values in the CMB. The signal was demonstrated to be robust with respect to the WMAP data release, to the component separation methods and to the selected test statistics.…”
Section: Phase Correlationsmentioning
confidence: 98%
“…MFs (Mecke et al 1994;Schmalzing & Buchert 1997;Schmalzing & Gorski 1998;Winitzki & Kosowsky 1998) are a measure of fields' local morphology used to constrain their stationarity, isotropy and Gaussianity. Mostly probing general NG in a frequentist fashion in two-dimensions on CMB maps (Eriksen et al 2004;Komatsu et al 2005;Modest et al 2013;Natoli et al 2010;Curto et al 2008) or three-dimensions on LSS data (Park et al 2005;Wiegand et al 2014), they have also been used to measure specific NG targets with Bayesian methods, such as f local NL (Hikage et al 2006(Hikage et al , 2008Ducout et al 2013;Planck Collaboration XXIV 2014), other bispectrum and trispectrum shapes (Hikage & Matsubara 2012) and topological defects (Planck Collaboration XXV 2014). New developments have been made recently, using needlets (Fantaye et al 2015), neural networks (Novaes et al 2015) or allowing scaledependent measurements (Munshi et al 2013).…”
Section: Minkowski Functionals Resultsmentioning
confidence: 99%
“…MFs describe the morphological properties of the CMB field and can be used as generic estimators of NG Eriksen et al 2004;De Troia et al 2007;Hikage et al 2008;Curto et al 2008;Natoli et al 2010;Hikage & Matsubara 2012;Modest et al 2013). As they are sensitive to every order of NG, they can be used to constrain different bispectrum and trispectrum shapes (Hikage et al 2006(Hikage et al , 2008Hikage & Matsubara 2012).…”
Section: Constraints On Local Non-gaussianity With Minkowski Functionalsmentioning
confidence: 99%