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

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.