Modeling dark energy through an Ising fluid with network interactions

TL;DR

This paper models dark energy using an Ising fluid with network interactions, reproducing the cosmological constant behavior without vacuum energy, and shows it fits observational data better than some existing models.

Contribution

It introduces a novel Ising fluid model for dark energy that naturally produces negative pressure and aligns with observational constraints, avoiding fine-tuning issues.

Findings

The model reproduces the cosmological constant behavior at low redshift.

It fits supernovae, BAO, and CMB data effectively.

Statistically favored over CPL parametrization.

Abstract

We show that the dark energy effects can be modeled by using an \emph{Ising perfect fluid} with network interactions, whose low redshift equation of state, i.e. $\omega_0$, becomes $\omega_0=-1$ as in the $\Lambda$CDM model. In our picture, dark energy is characterized by a barotropic fluid on a lattice in the equilibrium configuration. Thus, mimicking the spin interaction by replacing the spin variable with an occupational number, the pressure naturally becomes negative. We find that the corresponding equation of state mimics the effects of a variable dark energy term, whose limiting case reduces to the cosmological constant $\Lambda$. This permits us to avoid the introduction of a vacuum energy as dark energy source by hand, alleviating the coincidence and fine tuning problems. We find fairly good cosmological constraints, by performing three tests with supernovae Ia, baryonic acoustic oscillation and cosmic microwave background measurements. Finally, we perform the AIC and BIC selection criteria, showing that our model is statistically favored with respect to the CPL parametrization.