Related papers: Euclid preparation. Modelling spectroscopic cluste…
We present HST2EUCLID, a novel Python code to generate Euclid realistic mock images in the $H_{\rm E}$, $J_{\rm E}$, $Y_{\rm E}$, and $I_{\rm E}$ photometric bands based on panchromatic Hubble Space Telescope observations. The software was…
Cosmic shear, galaxy clustering, and the abundance of massive halos each probe the large-scale structure of the Universe in complementary ways. We present cosmological constraints from the joint analysis of the three probes, building on the…
We explore the use of strong lensing by galaxy clusters to constrain the dark energy equation of state and its possible time variation. The cores of massive clusters often contain several multiply imaged systems of background galaxies at…
We present results from a set of mock lightcones for the DESI One-Percent Survey, created from the Uchuu simulation. This This 8 (Gpc/h)^3 N-body simulation comprises 2.1 trillion particles and provides high-resolution dark matter…
We investigate the spatial properties of the large scale structure (LSS) of the Universe in the framework of coupled dark energy (cDE) cosmologies. Using the public halo catalogues from the CoDECS simulations -- the largest set of N-body…
The unexpectedly high abundance of bright, blue, super-early galaxies ($z\gtrsim10$) has challenged most pre-JWST models of early galaxy formation and motivated a wide range of proposed explanations. We systematically investigate whether…
In the era of large surveys, yielding thousands of galaxy clusters, efficient mass proxies at all scales are necessary in order to fully utilize clusters as cosmological probes. At the cores of strong lensing clusters, the Einstein radius…
We study the constraint on $f(R)$ gravity that can be obtained by photometric primary probes of the Euclid mission. Our focus is the dependence of the constraint on the theoretical modelling of the nonlinear matter power spectrum. In the…
Cluster-scale strong lensing is a powerful tool for exploring the properties of dark matter and constraining cosmological models. However, due to the complex parameter space, pixelized strong lens modeling in galaxy clusters is…
We present initial results on the use of Mixture Models for density estimation in large astronomical databases. We provide herein both the theoretical and experimental background for using a mixture model of Gaussians based on the…
Understanding the impact of baryonic processes such as star formation and active galactic nuclei (AGN) feedback on matter clustering is crucial to ensure precise and unbiased cosmological inference. Most theoretical models of baryonic…
The next generation of data-intensive surveys are bound to produce a vast amount of data, which can be dealt with using machine-learning methods to explore possible correlations within the multi-dimensional parameter space. We explore the…
Accurate weak lensing mass estimates of clusters are needed in order to calibrate mass proxies for the cosmological exploitation of galaxy cluster surveys. Such measurements require accurate knowledge of the redshift distribution of the…
We use giga-particle N-body simulations to study galaxy cluster populations in Hubble Volumes of LCDM (Omega_m=0.3, Omega_Lambda=0.7) and tCDM (Omega_m=1) world models. Mapping past light-cones of locations in the computational space, we…
We investigate how much the constraints on the neutrino properties can be improved by combining the CMB, the photometric and spectroscopic galaxy redshift surveys which include the CMB lensing, galaxy lensing tomography, galaxy clustering…
We perform a study of the nonlinear clustering of matter in the late-forming dark matter (LFDM) scenario in which dark matter results from the transition of a nonminimally coupled scalar field from radiation to collisionless matter. A…
With data from Pantheon, we have at our disposal a sample of more than a thousand supernovae Ia covering a wide range of redshifts with good precision. Here we make fits to the corresponding Hubble--Lema\^itre diagram with various…
Euclid will collect an enormous amount of data during the mission's lifetime, observing billions of galaxies in the extragalactic sky. Along with traditional template-fitting methods, numerous machine learning algorithms have been presented…
We present a new method that simultaneously solves for cosmology and galaxy bias on non-linear scales. The method uses the halo model to analytically describe the (non-linear) matter distribution, and the conditional luminosity function…
We present a simulation-based method to explore the optimum tomographic redshift binning strategy for 3x2pt analyses with Euclid, focusing on the expected configuration of its first major data release (DR1). To do this, we 1) simulate a…