Wavelet-Bayesian inference of cosmic strings embedded in the cosmic microwave background

TL;DR

This paper introduces a Bayesian wavelet-based framework for detecting cosmic strings in the CMB, capable of estimating string tension and distinguishing string signals from inflationary background.

Contribution

The authors develop a novel wavelet-Bayesian approach for cosmic string inference, enabling posterior estimation of string tension and model comparison using CMB data.

Findings

Method sensitive to Gμ ~ 5×10^{-7} in simulations

Framework effectively distinguishes string signals from inflationary background

Performance compares favorably with existing techniques

Abstract

Cosmic strings are a well-motivated extension to the standard cosmological model and could induce a subdominant component in the anisotropies of the cosmic microwave background (CMB), in addition to the standard inflationary component. The detection of strings, while observationally challenging, would provide a direct probe of physics at very high energy scales. We develop a new framework for cosmic string inference, constructing a Bayesian analysis in wavelet space where the string-induced CMB component has distinct statistical properties to the standard inflationary component. Our wavelet-Bayesian framework provides a principled approach to compute the posterior distribution of the string tension $G\mu$ and the Bayesian evidence ratio comparing the string model to the standard inflationary model. Furthermore, we present a technique to recover an estimate of any string-induced CMB map embedded in observational data. Using Planck-like simulations we demonstrate the application of our framework and evaluate its performance. The method is sensitive to $G\mu \sim 5 \times 10^{-7}$ for Nambu-Goto string simulations that include an integrated Sachs-Wolfe (ISW) contribution only and do not include any recombination effects, before any parameters of the analysis are optimised. The sensitivity of the method compares favourably with other techniques applied to the same simulations.