collaborators

19 papers

astro-ph.GA2026

Euclid Quick Data Release (Q1): The geometry of dark matter halos from extragalactic streams

Euclid Collaboration, N. Starkman, J. Nibauer +295

Wide-field surveys like Euclid mark a new era of extragalactic stellar stream studies. With a large number of streams, it is now possible to constrain the dark matter halos of gala…

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

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…

astro-ph.GA2026

Euclid preparation. Probing galaxy evolution within cosmic voids in Euclid-like simulations

Euclid Collaboration, G. Papini, O. Cucciati +294

The evolution of galaxies is profoundly influenced by the environment in which they reside. Cosmic voids serve as pristine laboratories for studying galaxy evolution in the relativ…

astro-ph.CO2026

Euclid preparation: Testing multi-field inflation with galaxy power spectrum and bispectrum

Euclid Collaboration, D. Linde, A. Moradinezhad Dizgah +281

Primordial non-Gaussianity (PNG) is a powerful probe of the origin of cosmic structure. Stage-IV surveys like \Euclid will measure galaxy - and -point clustering at high sign…

astro-ph.CO2026

Efficient estimators for power spectrum and bispectrum multipole measurements

Yunchen Xie, Ruiyang Zhao, Gan Gu +6

Large galaxy surveys demand fast and scalable estimators for anisotropic clustering statistics beyond the monopole. We present a suite of efficient FFT-based estimators for power-s…