Predicted Constraints on Cosmic String Tension from Planck and Future CMB Polarization Measurements

TL;DR

This study forecasts the precision of cosmic string tension measurements from Planck and future CMB polarization data, accounting for variable string network parameters and introducing an efficient computational tool.

Contribution

It introduces StringFast, a fast code for string-induced CMB spectra, and assesses how free string parameters affect constraints on Gmu from upcoming observations.

Findings

Planck can detect Gmu if it is at current maximum levels.

Constraints weaken by a factor of 2-7 when including free string parameters.

Detection is unlikely if Gmu is two orders of magnitude smaller.

Abstract

We perform a Fisher matrix calculation of the predicted uncertainties on estimates of the cosmic string tension Gmu from upcoming observational data (namely, cosmic microwave background power spectra from the Planck satellite and an idealized future polarization experiment). We employ simulations that are more general than others commonly used in the literature, leaving the mean velocity of strings, correlation length of the string network, and "wiggliness" (which parametrizes smaller-scale structure along the strings) as free parameters that can be observationally measured. In a new code, StringFast, we implement a method for efficient computation of the C_l spectra induced by a network of strings, which is fast enough to be used in Markov Chain Monte Carlo analyses of future data. Performing a calculation with the string parameters left free results in projected constraints on Gmu that are larger than those obtained by fixing their values a priori, typically by a factor of ~2-7. We also find that if Gmu is equal to the current observational maximum, Planck will be able to make a confident detection of strings. However, if Gmu is two orders of magnitude smaller, even a perfect, lensing-free measurement of polarization power spectra will not be able to detect a nonzero string tension at better than 2 sigma confidence.