Observational constraints of diffusive dark-fluid cosmology

TL;DR

This paper explores a diffusive dark-fluid cosmological model where dark matter and dark energy interact through diffusion, showing it can explain late-time acceleration and influence structure formation, with strong statistical support from recent data.

Contribution

It introduces a novel diffusive interaction mechanism between dark matter and dark energy, deriving background and perturbation equations, and constrains the model using current cosmological observations.

Findings

The diffusive model can drive late-time cosmic acceleration.

State-finder diagnostics show Chaplygin gas behavior.

DM dominates structure formation, with deviations from ΛCDM at higher redshifts.

Abstract

In this manuscript, we investigate late-time cosmology and the evolution of cosmic structures using an interacting dark fluid model in which dark matter (DM) and dark energy (DE) interact through a diffusive mechanism. To provide a comprehensive understanding, we derive the background evolution and perturbation equations within this model and obtain cosmological parameters through MCMC simulations. We use recent measurements for statistical analysis and constrain the parameters $H_0$ in km/s/Mpc, $\Omega_m$, $r_d$, $M$, $\sigma_8$, $S_8$, and the interaction term $Q_{dm}$. From the constrained values of $Q_{dm}$, we show that the diffusive model is a promising alternative DE model, capable of driving late-time cosmic acceleration due to energy exchange from DM to DE. State-finder diagnostics indicate that the model behaves like a Chaplygin gas when energy transfers from DM to DE during the Universe's expansion. We also investigate the growth of density contrast, finding $\delta_m(z)\gg\delta_{de}(z)$, which highlights the dominant role of DM in structure formation. Redshift space distortion and growth rate analysis show that minor deviations from $\Lambda$CDM at low redshifts, with larger differences at higher redshifts, indicate the impact of energy diffusion on early structure growth. Finally, we perform a detailed statistical analysis, including ${\mathcal{L}(\hat{\Theta}|data)}$, $\chi^2$, $\rm{AIC}$, and $\rm{BIC}$, which strongly supports the proposed diffusive dark-fluid model.