Exploring the cosmic microwave background as a composition of signals with Kolmogorov analysis

TL;DR

This paper investigates how Kolmogorov analysis can differentiate between various signals in the cosmic microwave background by examining their statistical properties, aiding in signal separation.

Contribution

It demonstrates the effectiveness of the Kolmogorov stochasticity parameter as a tool for distinguishing cosmological signals from secondary signals in CMB data.

Findings

Kolmogorov parameter effectively characterizes signal statistics.

Method distinguishes between different signal types in CMB.

Provides a new approach for signal separation in cosmology.

Abstract

The problem of separation of different signals in the Cosmic Microwave Background (CMB) radiation using the difference in their statistics is analyzed. Considering samples of sequences which model the CMB as a superposition of signals, we show how the Kolmogorov stochasticity parameter acts as a relevant descriptor, either qualitatively or quantitatively, to distinguish the statistical properties of the cosmological and secondary signals.