Model-independent cosmology with joint observations of gravitational waves and $\gamma$-ray bursts

Multi-messenger (MM) observations of binary neutron star (BNS) mergers provide a promising approach to trace the distance-redshift relation, crucial for understanding the expansion history of the Universe and, consequently, testing the nature of Dark Energy (DE). While the gravitational wave (GW) signal offers a direct measure of the distance to the source, high-energy observatories can detect the electromagnetic counterpart and drive the optical follow-up providing the redshift of the host galaxy. In this work, we exploit up-to-date catalogs of $\gamma$-ray bursts (GRBs) supposedly coming from BNS mergers observed by the Fermi $\gamma$-ray Space Telescope and the Neil Gehrels Swift Observatory, to construct a large set of mock MM data. We explore how combinations of current and future generations of GW observatories operating under various underlying cosmological models would be able to detect GW signals from these GRBs. We achieve the reconstruction of the GW parameters by means of a novel prior-informed Fisher matrix approach. We then use these mock data to perform an agnostic reconstruction of the DE phenomenology, thanks to a machine learning method based on forward modeling and Gaussian Processes (GP). Our study highlights the paramount importance of observatories capable of detecting GRBs and identifying their redshift. In the best-case scenario, the GP constraints are 1.5 times more precise than those produced by classical parametrizations of the DE evolution. We show that, in combination with forthcoming cosmological surveys, fewer than 40 GW-GRB detections will enable unprecedented precision on $H_\mathrm{0}$ and $\Omega_\mathrm{m}$, and accurately reconstruct the DE density evolution.