20 citations · 56 across the 23 of their papers we have counts for
12 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…
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…