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The PAU Survey: Photometric redshift estimation in deep wide fields
D. Navarro-Gironés, E. Gaztañaga, M. Crocce +23
We present photometric redshifts (photo-) for the deep wide fields of the Physics of the Accelerating Universe Survey (PAUS), covering an area of 50 deg, for 1…
Dark Energy Survey Deep Field photometric redshift performance and training incompleteness assessment
L. Toribio San Cipriano, J. De Vicente, I. Sevilla-Noarbe +55
Context. The determination of accurate photometric redshifts (photo-zs) in large imaging galaxy surveys is key for cosmological studies. One of the most common approaches are machi…
Generating mock galaxy catalogues for flux-limited samples like the DESI Bright Galaxy Survey
A. Smith, C. Grove, S. Cole +28
Accurate mock galaxy catalogues are crucial to validate analysis pipelines used to constrain dark energy models. We present a fast HOD-fitting method which we apply to the AbacusSu…
The PAU Survey: a new constraint on galaxy formation models using the observed colour redshift relation
G. Manzoni, C. M. Baugh, P. Norberg +27
We use the GALFORM semi-analytical galaxy formation model implemented in the Planck Millennium N-body simulation to build a mock galaxy catalogue on an observer's past lightcone. T…
Euclid preparation. LII. Forecast impact of super-sample covariance on 3x2pt analysis with Euclid
Euclid Collaboration, D. Sciotti, S. Gouyou Beauchamps +221
Deviations from Gaussianity in the distribution of the fields probed by large-scale structure surveys generate additional terms in the data covariance matrix, increasing the uncert…
The PAU Survey: Classifying low-z SEDs using Machine Learning clustering
A. L. González-Morán, P. Arrabal Haro, C. Muñóz-Tuñón +15
We present an application of unsupervised Machine Learning Clustering to the PAU Survey of galaxy spectral energy distribution (SED) within the COSMOS field. The clustering algorit…