924 citations · 4.8k across the 176 of their papers we have counts for
183 papers
Euclid Quick Data Release (Q1). Exploring the complexity of quenching processes across time, environment, and mass through recently quenched galaxies
Euclid Collaboration, Z. Mao, L. Pozzetti +308
Recently quenched galaxies (RQGs) provide insights into galaxy quenching. We present a photometric and spectroscopic analysis of RQGs using the first Euclid Quick Data Release (Q1)…
Euclid: Galaxy cluster detection through the weak lensing effect - algorithm assessment and selection
A. Manjón-García, G. Leroy, S. Pires +164
Weak gravitational lensing offers a powerful way to detect galaxy clusters by directly tracing their total matter content. Its effectiveness increases with the density of backgroun…
Euclid: Quick Data Release (Q1) -- Exploring the detailed visual morphology of galaxies in clusters
P. Mas-Buitrago, S. Kruk, D. O'Ryan +167
Galaxy clusters provide unique laboratories for studying environmental effects on galaxy evolution. The morphology--density (--) and morphology--cluster-centric radius (--…
Euclid preparation. The shape of halo profiles in CDM and non-standard cosmologies
Euclid Collaboration, L. Pizzuti, G. Y. Ferron +304
We study the shape of three-dimensional and projected dark-matter halo profiles extracted from cosmological -body simulations in CDM and non-standard cosmologies, using the \…
Euclid: Measuring the intrinsic alignment of galaxies around cosmic voids in the \Euclid Flagship simulation\
P. Vielzeuf, M. -C. Cousinou, A. Pisani +149
We present a methodology to measure the intrinsic alignment (IA) signal of galaxies in the vicinity of cosmic voids using the \Euclid-like Flagship cosmological simulation from the…
Galaxy clusters in the VIDEO fields: detection and characterisation in the context of MOONRISE
Pierre Galois, Christophe Benoist, Gianluca Castignani +21
We analyse the cluster content of the XMM-LSS and CDFS VIDEO fields which are expected to be partially covered by the upcoming MOONRISE survey. Using AMI…