20 citations · 56 across the 23 of their papers we have counts for
26 papers
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…
Euclid Quick Data Release (Q1): The impact of AGN emission on SED-derived physical properties
Euclid Collaboration, B. Laloux, A. Bongiorno +309
The Euclid Quick Data Release (Q1) is a powerful dataset to study active galactic nuclei (AGN) and their host galaxies. Deriving their physical properties through multi-component s…
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…
Euclid preparation. Refining input galaxy shape distributions for shear calibration simulations
Euclid Collaboration, H. Jansen, N. Martinet +282
The Euclid Wide Survey (EWS) will cover the majority of the extragalactic sky with a resolution similar to the Hubble Space Telescope. This unprecedented data set will introduce a…
Euclid Quick Data Release (Q1). AstroVink: A vision transformer approach to find strong gravitational lens systems
Euclid Collaboration, S. H. Vincken, K. Rojas +302
We present AstroVink, a vision transformer classifier designed for automated identification of strong lens candidates in Euclid imaging. We build upon the DINOv2 encoder, fine tune…
Euclid Quick Data Release (Q1). AgileLens: A scalable CNN-based pipeline for strong gravitational lens identification
Euclid Collaboration, X. Xu, R. Chen +308
We present an end-to-end, iterative pipeline for efficient identification of strong galaxy--galaxy lensing systems, applied to the Euclid Q1 imaging data. Starting from VIS catalog…
Euclid preparation. Testing template-fitting models for the multipoles of the two-point clustering of galaxy clusters
Euclid Collaboration, E. Tsaprazi, A. Fumagalli +274
The Euclid satellite will deliver a catalogue of optically selected galaxy clusters spanning from around 2000 deg in Data Release (DR) 1 to around deg in DR3. In…
Euclid preparation. Impact of redshift distribution uncertainties on the joint analysis of photometric galaxy clustering and weak gravitational lensing
Euclid Collaboration, K. A. Bertmann, A. Porredon +290
One of the mission's key projects is the so-called 32pt analysis, that is, the combination of cosmic shear, photometric galaxy clustering, and galaxy-gala…
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…
Euclid preparation. Galaxy 2-point correlation function modelling in redshift space
Euclid Collaboration, M. Kärcher, M. -A. Breton +309
The Euclid satellite will measure spectroscopic redshifts for tens of millions of emission-line galaxies. In the context of Stage-IV surveys, the 3-dimensional clustering of galaxi…
Euclid preparation. Decomposing components of the extragalactic background light using multi-band intensity mapping cross-correlations
Euclid Collaboration, Y. Cao, A. R. Cooray +269
The extragalactic background light (EBL) fluctuations in the optical/near-IR encode the cumulative integrated galaxy light (IGL), diffuse intra-halo light (IHL), and high- sourc…
Euclid preparation. Galaxy power spectrum modelling in redshift space
Euclid Collaboration, B. Camacho Quevedo, M. Crocce +292
Accurate modelling of redshift-space distortions (RSD) is essential for maximizing the cosmological information extracted from large galaxy redshift surveys. In preparation for the…
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…
Does Machine Learning Work? A Comparative Analysis of Strong Gravitational Lens Searches in the Dark Energy Survey
J. Gonzalez, T. Collett, K. Rojas +9
We present a systematic comparison of three independent machine learning (ML)-based searches for strong gravitational lenses applied to the Dark Energy Survey (Jacobs et al. 2019a,…
Euclid: A machine-learning search for dual and lensed AGN at sub-arcsec separations
L. Ulivi, F. Mannucci, M. Scialpi +189
Cosmological models of hierarchical structure formation predict the existence of a widespread population of dual accreting supermassive black holes (SMBHs) on kpc-scale separations…
The revolution in strong lensing discoveries from Euclid
Natalie E. P. Lines, Tian Li, Thomas E. Collett +5
Strong gravitational lensing offers a powerful and direct probe of dark matter, galaxy evolution and cosmology, yet strong lenses are rare: only 1 in roughly 10,000 massive galaxie…
Euclid Quick Data Release (Q1). The first catalogue of strong-lensing galaxy clusters
Euclid Collaboration, P. Bergamini, M. Meneghetti +375
We present the first catalogue of strong lensing galaxy clusters identified in the Euclid Quick Release 1 observations (covering ). This catalogue is the resu…
Euclid Quick Data Release (Q1). The Strong Lensing Discovery Engine E -- Ensemble classification of strong gravitational lenses: lessons for Data Release 1
Euclid Collaboration, P. Holloway, A. Verma +343
The Euclid Wide Survey (EWS) is expected to identify of order galaxy-galaxy strong lenses across deg. The Euclid Quick Data Release (Q1) of deg Eu…
Euclid Quick Data Release (Q1). The Strong Lensing Discovery Engine D -- Double-source-plane lens candidates
Euclid Collaboration, T. Li, T. E. Collett +335
Strong gravitational lensing systems with multiple source planes are powerful tools for probing the density profiles and dark matter substructure of the galaxies. The ratio of Eins…
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). The Strong Lensing Discovery Engine C: Finding lenses with machine learning
Euclid Collaboration, N. E. P. Lines, T. E. Collett +350
Strong gravitational lensing has the potential to provide a powerful probe of astrophysics and cosmology, but fewer than 1000 strong lenses have been confirmed so far. With a 0.16'…
Searching for strong lensing by late-type galaxies in UNIONS
J. A. Acevedo Barroso, B. Clément, F. Courbin +8
Recent wide-field galaxy surveys have led to an explosion in the number of galaxy-scale strong gravitational lens candidates. However, the vast majority of them feature massive lum…
Euclid: Finding strong gravitational lenses in the Early Release Observations using convolutional neural networks
B. C. Nagam, J. A. Acevedo Barroso, J. Wilde +192
The Early Release Observations (ERO) from Euclid have detected several new galaxy-galaxy strong gravitational lenses, with the all-sky survey expected to find 170,000 new systems,…
Discovering Strong Gravitational Lenses in the Dark Energy Survey with Interactive Machine Learning and Crowd-sourced Inspection with Space Warps
J. Gonzalez, P. Holloway, T. Collett +70
We conduct a search for strong gravitational lenses in the Dark Energy Survey (DES) Year 6 imaging data. We implement a pre-trained Vision Transformer (ViT) for our machine learnin…