Real space tests of the statistical isotropy and Gaussianity of the WMAP CMB data
Bartosz Lew

TL;DR
This paper introduces a novel real-space method to test the statistical isotropy and Gaussianity of WMAP CMB data, applying it to identify anomalies and constrain foreground residuals with high confidence.
Contribution
It presents a new real-space analysis technique that enhances exploration of CMB data and provides robust tests for isotropy and Gaussianity, including detection of anomalies.
Findings
WMAP maps are consistent with Gaussian isotropic models at 68% CL.
Detected a significant dipole excess in the V band data.
Identified large-scale hemispherical power asymmetry with low statistical significance.
Abstract
ABRIDGED: We introduce and analyze a method for testing statistical isotropy and Gaussianity and apply it to the WMAP CMB foreground reduced, temperature maps, and cross-channel difference maps. We divide the sky into regions of varying size and shape and measure the first four moments of the one-point distribution within these regions, and using their simulated spatial distributions we test the statistical isotropy and Gaussianity hypotheses. By randomly varying orientations of these regions, we sample the underlying CMB field in a new manner, that offers a richer exploration of the data content, and avoids possible biasing due to a single choice of sky division. The statistical significance is assessed via comparison with realistic Monte-Carlo simulations. We find the three-year WMAP maps to agree well with the isotropic, Gaussian random field simulations as probed by regions…
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