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Outliers in DESI BAO: robustness and cosmological implications
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We apply an Internal Robustness (iR) analysis to the recently released Dark Energy Spectroscopic Instrument (DESI) baryon acoustic oscillations dataset. This approach examines combinations of data subsets through a fully Bayesian model comparison, aiming to identify potential outliers, subsets possibly influenced by systematic errors, or hints of new physics. Using this approach, we identify three data points at $z= 0.295,\,0.51,\,0.71$ as potential outliers. Excluding these points improves the internal robustness of the dataset by minimizing statistical anomalies and enables the recovery of $\Lambda$CDM predictions with a best-fit value of $w_0 = -1.050 \pm 0.128$ and $w_a = 0.208 \pm 0.546$. These results raise the intriguing question of whether the identified outliers signal the presence of systematics or point towards new physics.
Forward citations
Cited by 3 Pith papers
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Present Day Cosmic Acceleration from SDSS and DESI BAO: A Call for Finer Tomography of the DESI Bright Galaxy Survey
DESI BAO+CMB yielding a positive present-day deceleration parameter q0≈0.10 (vs SDSS's q0≈−0.22) is explained by DESI's higher lowest effective redshift (0.295 vs 0.15), not by new physics.
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Mapping the redshift drift at various redshifts through cosmography
Cosmographic Taylor and Padé models fitted to Pantheon+SH0ES+GRB+DESI BAO data yield redshift drift predictions compatible with ΛCDM and ω0ω1CDM at 1-2σ, with mock drift data tightening q0 and j0 bounds.
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Testing Gauss-Bonnet Gravity with DESI BAO Data
Both power-law and exponential f(G) models fit recent cosmological data better than standard ΛCDM according to information criteria, with the exponential model predicting a late-time return to deceleration.
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