The WMAP cold spot

TL;DR

This paper investigates the WMAP cold spot, identifying it as likely caused by a collapsing cosmic texture, based on wavelet analysis, statistical significance, and Bayesian modeling.

Contribution

It provides a detailed analysis of the cold spot and supports the cosmic texture hypothesis as the most probable explanation.

Findings

The cold spot is statistically significant with a p-value around 1%.

A collapsing cosmic texture best explains the cold spot.

Wavelet analysis effectively detects anomalies in CMB data.

Abstract

The WMAP cold spot was found by applying spherical wavelets to the first year WMAP data. An excess of kurtosis of the wavelet coefficient was observed at angular scales of around 5 degrees. This excess was shown to be inconsistent with Gaussian simulations with a p-value of around 1%. A cold spot centered at (b = -57, l = 209) was shown to be the main cause of this deviation. Several hypotheses were raised to explain the origin of the cold spot. After performing a Bayesian template fit a collapsing cosmic texture was found to be the most probable hypothesis explaining the spot. Here we review the properties of the cold spot and the possible explanations.