Beecroft Institute for Particle Astrophysics and Cosmology

Abstract:

We present the first cosmological constraints from a joint analysis of galaxy clustering and galaxy–galaxy lensing using extended SubHalo Abundance Matching (SHAMe). We analyse stellar mass-selected Galaxy And Mass Assembly galaxy clustering and Kilo-Degree Survey (KiDS-1000) galaxy–galaxy lensing and find constraints on , in agreement with Planck at 1.7, with the mass density fluctuation amplitude in 8 sphere at present and the density parameter in total matter. These results are in agreement with the cosmic microwave background results from Planck. We are able to constrain all five SHAMe parameters, which describe the galaxy–subhalo connection. We validate our methodology by first applying it to simulated catalogues, generated from the TNG300 simulation, which mimic the stellar mass selection of our real data. We show that we are able to recover the input cosmology for both our fiducial and all-scale analyses. Our all-scale analysis extends to scales of galaxy–galaxy lensing below , which we exclude in our fiducial analysis to avoid baryonic effects. When including all scales, we find a value of , which is 1.26 higher than our fiducial result (against naive expectations where baryonic feedback should lead to small-scale power suppression), and in agreement with Planck at 0.9. We also find a 21 per cent tighter constraint on and a 29 per cent tighter constraint on compared to our fiducial analysis. This work shows the power and potential of joint small-scale galaxy clustering and galaxy–galaxy lensing analyses using SHAMe.

Abstract:

We present two extensive sets of 3500+1000 simulations of dark matter haloes on the past light cone and two corresponding sets of simulated (mock) galaxy catalogues that represent the spectroscopic sample of Euclid . The simulations were produced with the latest version of the code Pinocchio and provide the largest public set of simulated skies. The mock galaxy catalogues were obtained by populating haloes with galaxies using an halo occupation distribution (HOD) model extracted from the Flagship galaxy catalogue provided by Euclid Collaboration. The Geppetto set of 3500 simulated skies was obtained by tiling a 1.2 h −1 Gpc box to cover a light cone whose sky footprint is a circle with a radius of 30° for an area of 2763 deg 2 and a minimum halo mass of 1.5 × 10 11 h −1 M ⊙ . The relatively small size of the box means that this set is unsuitable for measuring very large scales. The EuclidLargeBox set consists of 1000 simulations of 3.38 h −1 Gpc and has the same mass resolution and a footprint that covers half of the sky. It excludes the Milky Way zone of avoidance. From this, we produced a set of 1000 EuclidLargeMocks on the 30° radius footprint, whose comoving volume is fully contained in the simulation box. We validated the two sets of catalogues by analysing number densities, power spectra, and two-point correlation functions to show that the Flagship spectroscopic catalogue is consistent with being one of the realisations of the simulated sets. We noted small deviations, however, that are limited to the quadrupole at k > 0.2 h Mpc −1 . We infer the cosmological parameters from these catalogues and demonstrate that using one realisation of EuclidLargeMocks in place of the Flagship mock produces the same posteriors to within the expected shift given by the sample variance. These simulated skies will be used for the galaxy clustering analysis of the Euclid Data Release 1 (DR1), and an even larger set of simulations is planned for the next releases.

Abstract:

Abstract The cross-correlation of galaxies at different redshifts with other tracers of the large-scale structure can be used to reconstruct the cosmic mean of key physical quantities, and their evolution over billions of years, at high precision. However, a correct interpretation of these measurements must ensure that they are independent of the clustering properties of the galaxy sample used. In this paper we explore different prescriptions to extract tomographic reconstruction measurements and use the FLAMINGO hydrodynamic simulations to show that a robust estimator, independent of the small-scale galaxy bias, can be constructed. We focus on the tomographic reconstruction of the halo bias-weighted electron pressure 〈bPe〉 and star-formation density 〈bρSFR〉, which can be reconstructed from tomographic analysis of Sunyaev-Zel’dovich and cosmic infrared background maps, respectively. We show that these quantities can be reconstructed with an accuracy of 1-3% over a wide range of redshifts, using different galaxy samples. We also show that these measurements can be accurately interpreted using the halo model, assuming a sufficiently reliable model can be constructed for the halo mass function, large-scale halo bias, and for the dependence of the physical quantities being reconstructed on halo mass.

Abstract:

The cross-correlation of galaxies at different redshifts with other tracers of the large-scale structure can be used to reconstruct the cosmic mean of key physical quantities, and their evolution over billions of years, at high precision. However, a correct interpretation of these measurements must ensure that they are independent of the clustering properties of the galaxy sample used. In this paper, we explore different prescriptions to extract tomographic reconstruction measurements and use the flamingo hydrodynamic simulations to show that a robust estimator, independent of the small-scale galaxy bias, can be constructed. We focus on the tomographic reconstruction of the halo bias-weighted electron pressure and star formation density , which can be reconstructed from tomographic analysis of Sunyaev–Zel’dovich and cosmic infrared background maps, respectively. We show that these quantities can be reconstructed with an accuracy of 1–3 per cent over a wide range of redshifts, using different galaxy samples. We also show that these measurements can be accurately interpreted using the halo model, assuming that a sufficiently reliable model can be constructed for the halo mass function, large-scale halo bias, and for the dependence of the physical quantities being reconstructed on halo mass.