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 sector is a matter of supreme interest at the present moment. This article searched for an interaction in the dark sector between a pressure-less dark matter and a dark energy fluid with constant equation of state, $w_{\mathrm{DE}}$. For this purpose, two non-parametric approaches, namely, the Gaussian Process (GP) and the Artificial Neural Networks (ANN) have been employed and using the Hubble data from Cosmic Chronometers (CC), Pantheon+ from Supernovae Type Ia and their combination we have reconstructed the interaction function. We find that for $w_{\mathrm{DE}}=-1$, the interaction in the dark sector is not prominent while for $w_{\mathrm{DE}}\ne -1$, evidence of interaction is found depending on the value of $w_{\mathrm{DE}}$. In particularly, we find that if we start deviating from $w_{\mathrm{DE}}=-1$ either in the quintessence ($w_{\mathrm{DE}}>-1$) or phantom ($w_{\mathrm{DE}}<-1$) 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.

20 pages, 14 figures, 1 table; MNRAS

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