9 citations · 73 across the 53 of their papers we have counts for
43 papers · 1 filter
Euclid Quick Data Release (Q1). From simulations to sky: Advancing machine-learning lens detection with real Euclid data
Euclid Collaboration, N. E. P. Lines, T. E. Collett +301
In the era of large-scale surveys like Euclid, machine learning has become an essential tool for identifying rare yet scientifically valuable objects, such as strong gravitational…
Euclid preparation: LXXXI. The impact of nonparametric star formation histories on spatially resolved galaxy property estimation using synthetic Euclid images
Euclid Collaboration, A. Nersesian, Abdurro'uf +283
We analyzed the spatially resolved and global star formation histories (SFHs) for a sample of 25 TNG50-SKIRT Atlas galaxies to assess the feasibility of reconstructing accurate SFH…
Euclid Quick Data Release (Q1): Hunting for luminous z > 6 galaxies in the Euclid Deep Fields -- forecasts and first bright detections
Euclid Collaboration, N. Allen, P. A. Oesch +309
The evolution of the rest-frame ultraviolet luminosity function (UV LF) is a powerful probe of early star formation and stellar mass build-up. At z > 6, its bright end (MUV < -21)…
Euclid Quick Data Release (Q1). Spectroscopic unveiling of highly ionised lines at z = 2.48-3.88
Euclid Collaboration, D. Vergani, S. Quai +316
This study explores a rare population of sources in a currently uncharted region of spectroscopic redshift space in the Euclid Quick Data Release (Q1), and is intended potentially…
Euclid Quick Data Release (Q1). Searching for giant gravitational arcs in galaxy clusters with mask region-based convolutional neural networks
Euclid Collaboration, L. Bazzanini, G. Angora +306
Strong gravitational lensing (SL) by galaxy clusters is a powerful probe of their inner mass distribution and a key test bed for cosmological models. However, the detection of SL e…
Euclid Quick Data Release (Q1). The average far-infrared properties of Euclid-selected star-forming galaxies
Euclid Collaboration, R. Hill, A. Abghari +302
The first Euclid Quick Data Release contains millions of galaxies with excellent optical and near-infrared (IR) coverage. To complement this dataset, we investigate the average far…
Euclid Quick Data Release (Q1). Quenching precedes bulge formation in dense environments but follows it in the field
Euclid Collaboration, F. Gentile, E. Daddi +321
(Abridged) The bimodality between star-forming discs and quiescent spheroids requires the existence of two main processes: the galaxy quenching and the morphological transformation…
Euclid preparation: The flat-sky approximation for the clustering of Euclid's photometric galaxies
Euclid Collaboration, W. L. Matthewson, R. Durrer +277
We compare the performance of the flat-sky approximation and Limber approximation for the clustering analysis of the photometric galaxy catalogue of Euclid. We study a 6 bin config…
Euclid preparation XCVII. Cosmology Likelihood for Observables in Euclid (CLOE). 4: Validation and performance
Euclid Collaboration, M. Martinelli, A. Pezzotta +334
The Euclid satellite will provide data on the clustering of galaxies and on the distortion of their measured shapes, which can be used to constrain and test the cosmological model.…
Euclid preparation. XCVI. Cosmology Likelihood for Observables in Euclid (CLOE). 3. Inference and Forecasts
Euclid Collaboration, G. Cañas-Herrera, L. W. K. Goh +337
The Euclid mission aims to measure the positions, shapes, and redshifts of over a billion galaxies to provide unprecedented constraints on the nature of dark matter and dark energy…
Euclid preparation. LXXXV. Toward a DR1 application of higher-order weak lensing statistics
Euclid Collaboration, S. Vinciguerra, F. Bouchè +284
This is the second paper in the HOWLS (higher-order weak lensing statistics) series exploring the usage of non-Gaussian statistics for cosmology inference within Euclid. With respe…
Euclid preparation. Predicting star-forming galaxy scaling relations with the spectral stacking code SpectraPyle
Euclid Collaboration, S. Quai, L. Pozzetti +309
We introduce SpectraPyle, a versatile spectral stacking pipeline developed for the Euclid mission's NISP spectroscopic surveys, aimed at extracting faint emission lines and spectra…
Euclid preparation. XCI. Validation method for the detections in the Euclid Catalogue of Galaxy Clusters using external data
Euclid Collaboration, J. -B. Melin, S. A. Stanford +315
We present our methodology for identifying known clusters as counterparts to objects in the Euclid Catalogue of Galaxy Clusters (ECGC). Euclid is expected to detect a large number…
Euclid preparation. Establishing the quality of the 2D reconstruction of the filaments of the cosmic web with DisPerSE using Euclid photometric redshifts
Euclid Collaboration, N. Malavasi, F. Sarron +313
Cosmic filaments are prominent structures of the matter distribution of the Universe. Modern detection algorithms are an efficient way to identify filaments in large-scale observat…
Euclid preparation: Expected constraints on initial conditions
Euclid Collaboration, F. Finelli, Y. Akrami +307
The Euclid mission of the European Space Agency will deliver galaxy and cosmic shear surveys, which will be used to constrain initial conditions and statistics of primordial fluctu…
Euclid VI. NISP-P optical ghosts
Euclid Collaboration, K. Paterson, M. Schirmer +309
The Near-Infrared Spectrometer and Photometer (NISP) onboard Euclid includes several optical elements in its path, which introduce artefacts into the data from non-nominal light pa…
Euclid preparation. Simulating thousands of Euclid spectroscopic skies
Euclid Collaboration, P. Monaco, G. Parimbelli +303
We present two extensive sets of 3500+1000 simulations of dark matter haloes on the past light cone, and two corresponding sets of simulated (`mock') galaxy catalogues that represe…
Euclid preparation. Constraining parameterised models of modifications of gravity with the spectroscopic and photometric primary probes
Euclid Collaboration, I. S. Albuquerque, N. Frusciante +285
The Euclid mission has the potential to understand the fundamental physical nature of late-time cosmic acceleration and, as such, of deviations from the standard cosmological model…
Euclid preparation: The NISP spectroscopy channel, on ground performance and calibration
Euclid Collaboration, W. Gillard, T. Maciaszek +356
ESA's Euclid cosmology mission relies on the very sensitive and accurately calibrated spectroscopy channel of the Near-Infrared Spectrometer and Photometer (NISP). With three opera…
Euclid preparation. The impact of redshift interlopers on the two-point correlation function analysis
Euclid Collaboration, I. Risso, A. Veropalumbo +317
The Euclid survey aims to measure the spectroscopic redshift of emission-line galaxies by identifying the H line in their slitless spectra. This method is sensitive to the sig…
Euclid preparation: TBD. Cosmic Dawn Survey: evolution of the galaxy stellar mass function across 0.2<z<6.5 measured over 10 square degrees
Euclid Collaboration, L. Zalesky, J. R. Weaver +304
The Cosmic Dawn Survey Pre-launch (PL) catalogues cover an effective 10.13 deg area with uniform deep Spitzer/IRAC data ( mag, 5), the largest area covered to the…
Euclid preparation LXX. Forecasting detection limits for intracluster light in the Euclid Wide Survey
Euclid Collaboration, C. Bellhouse, J. B. Golden-Marx +292
The intracluster light (ICL) permeating galaxy clusters is a tracer of the cluster's assembly history, and potentially a tracer of their dark matter structure. In this work we expl…
Euclid Quick Data Release (Q1): The Strong Lensing Discovery Engine A -- System overview and lens catalogue
Euclid Collaboration, M. Walmsley, P. Holloway +372
We present a catalogue of 497 galaxy-galaxy strong lenses in the Euclid Quick Release 1 data (63 deg). In the initial 0.45\% of Euclid's surveys, we double the total number of…
Euclid Quick Data Release (Q1). An investigation of optically faint, red objects in the Euclid Deep Fields
Euclid Collaboration, G. Girardi, G. Rodighiero +326
Our understanding of cosmic star-formation at used to largely rely on rest-frame UV observations. However, these observations overlook dusty and massive sources, resulting in…