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Euclid preparation. XXVII. Covariance model validation for the 2-point correlation function of galaxy clusters
Euclid Collaboration, A. Fumagalli, A. Saro +191
Aims. We validate a semi-analytical model for the covariance of real-space 2-point correlation function of galaxy clusters. Methods. Using 1000 PINOCCHIO light cones mimicking the…
Euclid preparation. XXV. The Euclid Morphology Challenge -- Towards model-fitting photometry for billions of galaxies
Euclid Collaboration, E. Merlin, M. Castellano +218
The ESA Euclid mission will provide high-quality imaging for about 1.5 billion galaxies. A software pipeline to automatically process and analyse such a huge amount of data in real…
BeyondPlanck X. Planck LFI frequency maps with sample-based error propagation
A. Basyrov, A. -S. Suur-Uski, L. P. L. Colombo +37
We present Planck LFI frequency sky maps derived within the BeyondPlanck framework. This framework draws samples from a global posterior distribution that includes instrumental, as…
BeyondPlanck XI. Bayesian CMB analysis with sample-based end-to-end error propagation
L. P. L. Colombo, J. R. Eskilt, S. Paradiso +36
We present posterior sample-based cosmic microwave background (CMB) constraints from Planck LFI and WMAP observations derived through global end-to-end Bayesian processing. We use…
Euclid preparation. XXIV. Calibration of the halo mass function in CDM cosmologies
Euclid Collaboration, T. Castro, A. Fumagalli +179
Euclid's photometric galaxy cluster survey has the potential to be a very competitive cosmological probe. The main cosmological probe with observations of clusters is their number…
Euclid preparation: XXIII. Derivation of galaxy physical properties with deep machine learning using mock fluxes and H-band images
Euclid Collaboration, L. Bisigello, C. J. Conselice +196
Next generation telescopes, like Euclid, Rubin/LSST, and Roman, will open new windows on the Universe, allowing us to infer physical properties for tens of millions of galaxies. Ma…