A Multiscale pipeline for the search of stringinduced CMB anisotropies
Abstract
We propose a multiscale edgedetection algorithm to search for the GottKaiserStebbins imprints of a cosmic string (CS) network on the cosmic microwave background (CMB) anisotropies. Curvelet decomposition and extended Canny algorithm are used to enhance the string detectability. Various statistical tools are then applied to quantify the deviation of CMB maps having a CS contribution with respect to pure Gaussian anisotropies of inflationary origin. These statistical measures include the onepoint probability density function, the weighted twopoint correlation function (TPCF) of the anisotropies, the unweighted TPCF of the peaks and of the upcrossing map, as well as their crosscorrelation. We use this algorithm on a hundred of simulated NambuGoto CMB flat sky maps, covering approximately 10 per cent of the sky, and for different string tensions Gμ. On noiseless sky maps with an angular resolution of 0.9 arcmin, we show that our pipeline detects CSs with Gμ as low as Gμ ≳ 4.3 × 10^{10}. At the same resolution, but with a noise level typical to a CMBS4 phase II experiment, the detection threshold would be to Gμ ≳ 1.2 × 10^{7}.
 Publication:

Monthly Notices of the Royal Astronomical Society
 Pub Date:
 March 2018
 DOI:
 10.1093/mnras/stx3126
 arXiv:
 arXiv:1710.00173
 Bibcode:
 2018MNRAS.475.1010V
 Keywords:

 methods: data analysis;
 methods: statistical;
 techniques: image processing;
 cosmic background radiation;
 early Universe;
 Astrophysics  Cosmology and Nongalactic Astrophysics;
 Astrophysics  Instrumentation and Methods for Astrophysics;
 Physics  Data Analysis;
 Statistics and Probability;
 Statistics  Applications
 EPrint:
 13 pages, 5 figures, 1 table, Comments are welcome