The Dark Energy Survey Year 3 high redshift sample: Selection, characterization and analysis of galaxy clustering
C. S\'anchez, A. Alarcon, G. M. Bernstein, J. Sanchez, S. Pandey, M., Raveri, J. Prat, N. Weaverdyck, I. Sevilla-Noarbe, C. Chang, E. Baxter, Y., Omori, B. Jain, O. Alves, A. Amon, K. Bechtol, M. R. Becker, J. Blazek, A., Choi, A. Campos, A. Carnero Rosell, M. Carrasco Kind

TL;DR
This paper presents the selection, characterization, and analysis of high-redshift galaxy samples from DES Year 3 data, extending the redshift range and providing robust cosmological constraints through galaxy clustering measurements.
Contribution
It introduces a novel high-redshift galaxy sample selection using Bayesian redshift estimation and machine learning corrections, significantly extending DES Year 3 analysis capabilities.
Findings
Galaxy clustering yields $ m \Omega_m h$ constraint of 0.195^{+0.023}_{-0.018}
Achieved 2-3% measurements of galaxy clustering amplitude
Sample contains about 9 million galaxies with over twice the density of previous analyses
Abstract
The fiducial cosmological analyses of imaging galaxy surveys like the Dark Energy Survey (DES) typically probe the Universe at redshifts . This is mainly because of the limited depth of these surveys, and also because such analyses rely heavily on galaxy lensing, which is more efficient at low redshifts. In this work we present the selection and characterization of high-redshift galaxy samples using DES Year 3 data, and the analysis of their galaxy clustering measurements. In particular, we use galaxies that are fainter than those used in the previous DES Year 3 analyses and a Bayesian redshift scheme to define three tomographic bins with mean redshifts around , and , which significantly extend the redshift coverage of the fiducial DES Year 3 analysis. These samples contain a total of about 9 million galaxies, and their galaxy density is more than 2 times…
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