Reconstruction of the swampland conjectures with DESI DR1 BAO data

The swampland conjectures (SCs) propose constraints on effective field theories that can arise from a consistent theory of quantum gravity. Two prominent SCs suggest that the scalar field excursion and the gradient of the potential should be at most $\mathcal{O}(1)$ in Planck units. Using the first data release from the Dark Energy Spectroscopic Instrument (DESI) survey and model-independent reconstructions of the SC-related quantities at late times, via a machine learning approach known as genetic algorithms, we evaluate the consistency of these reconstructions with the SC expectations. Our results indicate that the reconstructed second SC is several $\ensuremath{\sigma}$'s away from zero, suggesting a steep potential, in contrast to recent model-specific analyses assuming exponential potentials. The novelty of our approach lies in using solely model-independent reconstructions of cosmological observables from DESI, such as the angular diameter distance and the Hubble expansion history. This makes our method readily applicable to forthcoming data from stage IV surveys, providing a framework for further assessing consistency with SCs.