DESI results: Hint towards coupled dark matter and dark energy
Amlan Chakraborty, Prolay K. Chanda, Subinoy Das, Koushik Dutta
TL;DR
The paper addresses DESI's hints of evolving dark energy and phantom-crossing by proposing an interacting dark sector model in which a quintessence field is Yukawa-coupled to dark matter. It demonstrates that the observable equation of state $w_{\rm eff}$ can cross the phantom barrier while the intrinsic field equation of state $w_{\phi}$ remains above $-1$, achieving compatibility with DESI (and Planck/Union3) within 2$\sigma$ for certain parameter choices. The authors solve the coupled Klein-Gordon and Friedmann equations for two self-interaction potentials, showing late-time crossing around $z\sim0.5-1$ under thawing dynamics, and highlight the need for forthcoming MCMC analyses and perturbation studies. This framework offers a viable path to interpret DESI data without phantom fields, motivating further cosmological and particle-physics investigations.
Abstract
We investigate a scenario where a dark energy quintessence field $φ$ with positive kinetic energy is coupled with dark matter. With two different self-interaction potentials for the field and a particular choice of the coupling function, we show explicitly how the observable effective equation of state parameter $w_{\rm eff}$ for the dark energy field crosses the phantom barrier ($w_{\rm eff} = -1$) while keeping the equation of state of the quintessence field $w_φ> -1$. With appropriate choices of parameters, $w_{\rm eff}$ crosses the phantom divide around redshift $z\sim 0.5$, transitioning from $w_{\rm eff} <-1$ in the past to $w_{\rm eff}>-1$ today. This explains DESI observations well. Our analysis reveals that the model remains consistent within the $2σ$ confidence intervals provided by DESI for several combinations of the scalar field parameters, highlighting its potential in explaining the dynamics of dark energy arising from a simple Yukawa-type long-range interaction in the dark sector. While the current findings offer a promising framework for interpreting DESI observations, future work, including a comprehensive Markov Chain Monte Carlo (MCMC) analysis, is necessary to constrain the parameter space further and strengthen the statistical significance of the results.
