In search of an interaction in the dark sector through Gaussian process and ANN approaches

Abstract

ABSTRACT Whether the current observational data indicate any evidence of interaction between the dark sectors is a matter of supreme interest at the present moment. This article searched for an interaction in the dark sector between a pressureless dark matter and a dark energy fluid with constant equation of state, $w_{\rm DE}$. For this purpose, two non-parametric approaches, namely the Gaussian process (GP) and the artificial neural networks (ANNs), have been employed and using the Hubble data from cosmic chronometers, Pantheon+ from Type Ia supernovae, and their combination we have reconstructed the interaction function. We find that for $w_{\rm DE} =-1$, the interaction in the dark sector is not prominent, while for $w_{\rm DE} \ne -1$, evidence of interaction is found depending on the value of $w_{\rm DE}$. In particular, we find that if we start deviating from $w_{\rm DE} = -1$ in either the quintessence ($w_{\rm DE} > -1$) or phantom ($w_{\rm DE} < -1$) direction, an emergence of dark interaction is observed from both GP and ANN reconstructions. We further note that ANN, which is applied for the first time in this context, seems to play a very efficient role compared to GP.