Cosmic Strings as Dynamical Dark Energy: Novel Constraints

TL;DR

This study explores cosmic string models as a form of dynamical dark energy, constraining their properties using current cosmological data and finding no strong evidence to favor these models over standard CDM.

Contribution

It introduces four phenomenological cosmic string models and provides the first comprehensive constraints on their parameters using multiple cosmological datasets.

Findings

Models 1 and 2 are tightly constrained with low string density.

Models 3 and 4 show a mild preference for negative string density values.

Current data do not favor cosmic string models over CDM, according to Bayesian evidence.

Abstract

Cosmic strings, topological defects predicted by high-energy theories, may contribute to the late-time expansion of the Universe, effectively mimicking dynamical dark energy. We investigate four phenomenological extensions of the $\Lambda$CDM model involving a residual string network: (i) a non-relativistic component with positive energy density (Model~1), (ii) a velocity-dependent extension (Model~2), (iii) a non-relativistic string network with energy density allowed to take both positive and negative values (Model~3), and (iv) a general scenario with free energy and velocity parameters (Model~4). These models are constrained using \textit{Planck} CMB data, SDSS or DESI baryon acoustic oscillations, and Type Ia supernovae observations. Models~1 and~2 yield strong upper bounds on the string density, for example, $\Omega_{\mathrm{s}} < 0.00901$ at 95\% CL from the CMB+DESI+DESY5 combination for Model~2, and mildly shift the inferred value of $H_0$ upward, though they are not favored by Bayesian evidence. For the same combination, the bulk velocity is bound as $v_{\mathrm{s}} < 0.569$. Models~3 and~4 exhibit a consistent preference for slightly negative values of $\Omega_{\mathrm{s}}$, with CMB-only data yielding $\Omega_{\mathrm{s}} = -0.038^{+0.029}_{-0.022}$ and $v_{\mathrm{s}}< 0.574$ in Model~4, and a best-fit improvement of $\Delta \chi^2 = -6.07$. However, these improvements are not sufficient to overcome the Occam penalty, and the Bayesian evidence continues to favor $\Lambda$CDM. These findings demonstrate the power of current data to constrain exotic energy components and encourage further exploration of string-inspired extensions to $\Lambda$CDM, particularly those involving negative-tension networks.