activity
20222025
most citedThe impact of human expert visual inspection on the discovery of strong gravitational lenses

20 citations · 40 across the 5 of their papers we have counts for

collaborators

6 papers

astro-ph.GA2025

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…

astro-ph.CO2023★ 1 cited

Dark Energy Survey Year 3 Results: Mis-centering calibration and X-ray-richness scaling relations in redMaPPer clusters

P. Kelly, J. Jobel, O. Eiger +76

We use Dark Energy Survey Year 3 (DES Y3) clusters with archival X-ray data from XMM-Newton and Chandra to assess the centering performance of the redMaPPer cluster finder and to m…

astro-ph.CO2023

Building an Efficient Cluster Cosmology Software Package for Modeling Cluster Counts and Lensing

M. Aguena, O. Alves, J. Annis +60

We introduce a software suite developed for galaxy cluster cosmological analysis with the Dark Energy Survey Data. Cosmological analyses based on galaxy cluster number counts and w…

astro-ph.CO2023

Cool Cores in Clusters of Galaxies in the Dark Energy Survey

K. Graham, J. O'Donnell, M. M. Silverstein +54

We search for the presence of cool cores in optically-selected galaxy clusters from the Dark Energy Survey (DES) and investigate their prevalence as a function of redshift and clus…

astro-ph.GA2023★ 20 cited

The impact of human expert visual inspection on the discovery of strong gravitational lenses

Karina Rojas, Thomas E. Collett, Daniel Ballard +53

We investigate the ability of human 'expert' classifiers to identify strong gravitational lens candidates in Dark Energy Survey like imaging. We recruited a total of 55 people that…

astro-ph.GA2022★ 19 cited

Identification of Galaxy-Galaxy Strong Lens Candidates in the DECam Local Volume Exploration Survey Using Machine Learning

E. A. Zaborowski, A. Drlica-Wagner, F. Ashmead +88

We perform a search for galaxy-galaxy strong lens systems using a convolutional neural network (CNN) applied to imaging data from the first public data release of the DECam Local V…