1k citations · 6.8k across the 78 of their papers we have counts for
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Euclid: Searches for strong gravitational lenses using convolutional neural nets in Early Release Observations of the Perseus field
R. Pearce-Casey, B. C. Nagam, J. Wilde +204
The Euclid Wide Survey (EWS) is predicted to find approximately 170 000 galaxy-galaxy strong lenses from its lifetime observation of 14 000 deg^2 of the sky. Detecting this many le…
Deep Drilling in the Time Domain with DECam: Survey Characterization
Melissa L. Graham, Robert A. Knop, Thomas Kennedy +41
This paper presents a new optical imaging survey of four deep drilling fields (DDFs), two Galactic and two extragalactic, with the Dark Energy Camera (DECam) on the 4 meter Blanco…
LensingETC: a tool to optimize multi-filter imaging campaigns of galaxy-scale strong lensing systems
Anowar J. Shajib, Karl Glazebrook, Tania Barone +7
Imaging data is the principal observable required to use galaxy-scale strong lensing in a multitude of applications in extragalactic astrophysics and cosmology. In this paper, we d…
Rubin-Euclid Derived Data Products: Initial Recommendations
Leanne P. Guy, Jean-Charles Cuillandre, Etienne Bachelet +117
This report is the result of a joint discussion between the Rubin and Euclid scientific communities. The work presented in this report was focused on designing and recommending an…
Strong Lensing Science Collaboration input to the on-sky commissioning of the Vera Rubin Observatory
Graham P. Smith, Timo Anguita, Simon Birrer +10
We present the Strong Lensing Science Collaboration's (SLSC) recommended observing targets for the science verification and science validation phases of commissioning. Our recommen…
4MOST: Project overview and information for the First Call for Proposals
R. S. de Jong, O. Agertz, A. Agudo Berbel +335
We introduce the 4-metre Multi-Object Spectroscopic Telescope (4MOST), a new high-multiplex, wide-field spectroscopic survey facility under development for the four-metre-class Vis…
Optimizing the LSST Observing Strategy for Dark Energy Science: DESC Recommendations for the Wide-Fast-Deep Survey
Michelle Lochner, Daniel M. Scolnic, Humna Awan +33
Cosmology is one of the four science pillars of LSST, which promises to be transformative for our understanding of dark energy and dark matter. The LSST Dark Energy Science Collabo…
Finding strong lenses in CFHTLS using convolutional neural networks
Colin Jacobs, Karl Glazebrook, Thomas Collett +2
We train and apply convolutional neural networks, a machine learning technique developed to learn from and classify image data, to Canada-France-Hawaii Telescope Legacy Survey (CFH…
Automated Lensing Learner: Automated Strong Lensing Identification with a Computer Vision Technique
Camille Avestruz, Nan Li, Hanjue Zhu +3
Forthcoming surveys such as the Large Synoptic Survey Telescope (LSST) and Euclid necessitate automatic and efficient identification methods of strong lensing systems. We present a…
CMU DeepLens: Deep Learning For Automatic Image-based Galaxy-Galaxy Strong Lens Finding
Francois Lanusse, Quanbin Ma, Nan Li +5
Galaxy-scale strong gravitational lensing is not only a valuable probe of the dark matter distribution of massive galaxies, but can also provide valuable cosmological constraints,…
Space Warps: I. Crowd-sourcing the Discovery of Gravitational Lenses
Philip J. Marshall, Aprajita Verma, Anupreeta More +20
We describe Space Warps, a novel gravitational lens discovery service that yields samples of high purity and completeness through crowd-sourced visual inspection. Carefully produce…