Constraints on interacting holographic dark energy models: Implications from background and perturbations data

In this study, we employ a two-step method to analyze models of holographic dark energy (HDE) and interacting holographic dark energy (IHDE), incorporating three distinct dark energy (DE)-dark matter (DM) interaction terms. First, using the latest background dataset, we conduct a Markov chain Monte Carlo analysis to constrain the free parameters of the models. Then, we assess the models against each other using the key background parameters and compare them to the $\mathrm{\ensuremath{\Lambda}}$ cold dark matter ($\mathrm{\ensuremath{\Lambda}}\mathrm{CDM}$) standard model. Our results show that at high redshifts, the equation of state parameter related to the models for both homogeneous and clustered DE cases falls within the quintessence region. However, as we approach the present time, all models except HDE transition into the phantom region, and two models cross the phantom line earlier than others. In the next step, we focus on the evolution of perturbations in DE and DM. Using background and growth rate data, we constrain parameters including ${\ensuremath{\sigma}}_{8}$. We then investigate the evolution of the growth rate of matter perturbations, $f{\ensuremath{\sigma}}_{8}(z)$, and its deviation, $\mathrm{\ensuremath{\Delta}}f{\ensuremath{\sigma}}_{8}$, from the $\mathrm{\ensuremath{\Lambda}}\mathrm{CDM}$ model. The HDE model shows the best agreement with observational data, while other models predict varying growth rates compared to $\mathrm{\ensuremath{\Lambda}}\mathrm{CDM}$. Finally, we demonstrate through Akaike and Bayesian information criteria analysis that the compatibility of models with observational data depends on the type of data used, the DE-DM interaction term, and the assumptions regarding DE homogeneity and clustering. Our results suggest that homogeneous DE models yield more agreement with observational data than clustered DE models.