Cosmic microwave background anisotropy from wiggly strings
Levon Pogosian, Tanmay Vachaspati
TL;DR
This work addresses how wiggly cosmic strings influence CMBR anisotropy and the matter power spectrum, exploring whether small-scale wiggles can reconcile predictions with observations. It combines a wiggly-string stress-energy model with the one-scale string-network evolution and uses line-of-sight integration via $\text{CMBFAST}$ to predict observables. Key findings show that wiggliness raises the CMB power peak at $l \approx 400$ and can boost small-scale matter power, but a cosmological-constant–dominated model still requires a scale-dependent bias of order $b \approx 1.6$ to $2.4$, with COBE-normalized $G\mu_0$ near $10^{-6}$ to a few $\times10^{-6}$. The work demonstrates that incorporating small-scale structure in strings can improve data compatibility, while also highlighting limitations due to neglect of loops, compensation, and backreaction, pointing to directions for refined string-network modeling.
Abstract
We investigate the effect of wiggly cosmic strings on the cosmic microwave background radiation anisotropy and matter power spectrum by modifying the string network model used by Albrecht et al.. We employ the wiggly equation of state for strings and the one-scale model for the cosmological evolution of certain network characteristics. For the same choice of simulation parameters we compare the results with and without including wiggliness in the model and find that wiggliness together with the accompanying low string velocities lead to a significant peak in the microwave background anisotropy and to an enhancement in the matter power spectrum. For the cosmologies we have investigated (standard CDM, and, CDM plus cosmological constant), and within the limitations of our modeling of the string network, the anisotropy is in reasonable agreement with current observations but the COBE normalized amplitude of density perturbations is lower than what the data suggests. In the case of a cosmological constant and CDM model, a bias factor of about 2 is required.
