collaborators

49 papers

astro-ph.CO2026

Dark Energy Survey Year 6 Results: Redshift Calibration of the Weak Lensing Source Galaxies

B. Yin, A. Amon, A. Campos +95

Determining the distribution of redshifts for galaxies in wide-field photometric surveys is essential for robust cosmological studies of weak gravitational lensing. We present the…

astro-ph.CO2026

The PAU Survey and Euclid: Analysing photometric redshifts from realistically simulated narrow-band photometry with Flagship 2

A. Wittje, H. Hildebrandt, D. Navarro-Gironés +154

The study of the large-scale structure of the Universe and the distribution of galaxies has been greatly advanced by the application of various types of photometric redshift estima…

astro-ph.CO2026

Euclid. Populating a dark universe with galaxies using SciPIC

Euclid Collaboration, E. J. Gonzalez, J. Carretero +305

High-fidelity galaxy mocks are crucial for validating analysis pipelines and for cosmological inference. In this context, the Science Pipeline at PIC (SciPIC) is a pipeline specifi…

astro-ph.CO2026

Dark Energy Survey Year 3 results: optimized CDM simulation-based inference with weak lensing map-level hybrid statistics

J. Williamson, T. L. Makinen, N. Porqueres +85

We present cosmological constraints from the Dark Energy Survey Year 3 (DES Y3) weak lensing data using hierarchical hybrid statistics within a Bayesian simulation-based inference…

astro-ph.CO2026

Euclid preparation. CIV. Impact of galaxy intrinsic alignment modelling choices on Euclid 3x2pt cosmology

Euclid Collaboration, D. Navarro-Gironés, I. Tutusaus +274

The Euclid galaxy survey will provide unprecedented constraints on cosmology, but achieving unbiased results will require an optimal characterisation and mitigation of systematic e…

astro-ph.CO2026

Euclid preparation. CII. Non-Gaussianity of 2-pt statistics likelihood: Parameter inference with a non-Gaussian likelihood in Fourier and configuration space

Euclid Collaboration, S. Gouyou Beauchamps, J. Bel +277

In this work we account for this skewness in parameter inference by modelling the likelihood through an Edgeworth expansion which involves the complete skewness tensor, composed of…