Searching cosmic strings network in the CMB

Abstract

The CMB stochastic field provides us with a unique opportunity to search for the predicted imprints of various cosmological theories. In this work, we explore the detectability of the cosmic string (CS) network traces in the pixel-space through its gravitational impact on the CMB anisotropies, i.e. the Gott–Kaiser–Stebbins effect. First, in a classical approach, we use a series of multi-scale edge-detection algorithms followed by certain critical and excursion sets measures on the CMB simulated data (with different levels of contributions from the CSs). With this pipeline the minimum value of detectable CS’s tension for noiseless maps with a resolution of [Formula: see text] is found to be [Formula: see text]. Calling for the help the power of the machine learning algorithms with our proposed feature vectors, decreases the above lower bound to [Formula: see text]. The methods developed and used in this work are quite general and applicable to a wide variety of pattern search problems in the various stochastic fields ranging from cosmological random fields to other natural and artificial complex systems.