Cosmic microwave background anomalies viewed via Gumbel Statistics

TL;DR

This paper applies Gumbel statistics to WMAP data to analyze extreme temperature events in the CMB, offering a model-independent method that can detect certain non-Gaussian features and alignments.

Contribution

It introduces the use of Gumbel statistics for CMB analysis, demonstrating its effectiveness in modeling extrema and identifying anomalies without relying on specific Gaussian assumptions.

Findings

Gumbel statistics effectively model CMB temperature extrema.

Weak discrimination for non-Gaussianity with $f_{NL}<1000$.

Hemispheric analysis shows alignments with known CMB anomalies.

Abstract

We describe and discuss the application of Gumbel statistics, which model extreme events, to WMAP 5-year measurements of the cosmic microwave background. We find that temperature extrema of the CMB are well modelled by the Gumbel formalism and describe tests for Gaussianity that the approach can provide. Comparison to simulations reveals Gumbel statistics to have only weak discriminatory power for the conventional statistic: $f_{NL}<1000$, though it may probe other regimes of non-Gaussianity. Tests based on hemispheric cuts reveal interesting alignment with other reported CMB anomalies. The approach has the advantage of model independence and may find further utility with smaller scale data.