A new analysis of the distribution of matter in the Universe continues to find a discrepancy in the clumpiness of dark matter in the late and early Universe, suggesting a fundamental error in the standard cosmological model.
Cosmological constraints can be improved by applying machine learning to a combination of data from two leading probes of the large-scale structure of the Universe.
A large galaxy survey releases its three-year observations, providing key cosmological-parameter measurements that have double the precision of those previously released.