SIMBAD references

2022A&A...662A..44C - Astronomy and Astrophysics, volume 662A, 44-44 (2022/6-1)

Tomography-based observational measurements of the halo mass function via the submillimeter magnification bias.

CUELI M.M., BONAVERA L., GONZALEZ-NUEVO J., CRESPO D., CASAS J.M. and LAPI A.

Abstract (from CDS):


Aims. The main goal of this paper is to derive observational constraints on the halo mass fuction (HMF) by performing a tomographic analysis of the magnification bias signal on a sample of background submillimeter galaxies. The results can then be compared with those from a non-tomographic study.
Methods. We measure the cross-correlation function between a sample of foreground GAMA galaxies with spectroscopic redshifts in the range 0.1 < z < 0.8 (and divided up into four bins) and a sample of background submillimeter galaxies from H-ATLAS with photometric redshifts in the range 1.2 < z < 4.0. We model the weak lensing signal within the halo model formalism and carry out a Markov chain Monte Carlo algorithm to obtain the posterior distribution of all HMF parameters, which we assume to follow the Sheth and Tormen (ST) three-parameter and two-parameter fits.
Results. While the observational constraints on the HMF from the non-tomographic analysis are not stringent, there is a remarkable improvement in terms of uncertainty reduction when tomography is adopted. Moreover, with respect to the traditional ST triple of values from numerical simulations, the results from the three-parameter fit predict a higher number density of halos at masses below ∼1012 M h–1 at 95% credibility. The two-parameter fit yields even more restricting results, with a larger number density of halos below ∼1013 M h–1 and a lower one above ∼1014 M h–1, this time at more than 3σ credibility. Our results are therefore in disagreement with the standard N-body values for the ST fit at 2σ and 3σ, respectively.

Abstract Copyright: © ESO 2022

Journal keyword(s): galaxies: halos - submillimeter: galaxies - gravitational lensing: weak

Simbad objects: 1

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