To obtain an accurate cosmological inference from upcoming weak lensing surveys such as the one conducted by Euclid, the shear measurement requires calibration using galaxy image simulations. As it typically requires millions of simulated galaxy images and consequently a substantial computational effort, seeking methods to speed the calibration up

Aims: We validate a semi-analytical model for the covariance of the real-space two-point correlation function of galaxy clusters. Methods: Using 1000 PINOCCHIO light cones mimicking the expected Euclid sample of galaxy clusters, we calibrated a simple model to accurately describe the clustering covariance. Then, we used this model to quantify the

Context. The cosmological surveys that are planned for the current decade will provide us with unparalleled observations of the distribution of galaxies on cosmic scales, by means of which we can probe the underlying large-scale structure (LSS) of the Universe. This will allow us to test the concordance cosmological model and its extensions

Modern cosmological hydrodynamical galaxy simulations provide tens of thousands of reasonably realistic synthetic galaxies across cosmic time. However, quantitatively assessing the level of realism of simulated universes in comparison to the real one is difficult. In this paper of the Extracting Reality from Galaxy Observables with Machine Learning

In a very recent work, [1] claim that the scenario of temperature inhomogeneities proposed by [2] ($t2$ > 0) is not able to explain the O$^{2+}$/H$^{+}$ abundance discrepancy observed between the calculations based on the optical [OIII] collisional excited lines (CELs) and the OII recombination lines (RLs) in the star forming galaxy Mrk71. In this

Context. Known Mars trojans could be primordial small bodies that have remained in their present-day orbits for the age of the Solar System. Their orbital distribution is strongly asymmetric; there are over a dozen objects at the L 5 point and just one at L 4, (121514) 1999 UJ 7. Most L 5 trojans appear to form a collision-induced asteroid cluster