Related papers: An extended catalog of galaxy-galaxy strong gravit…
Using stellar population models, we predicted that the Dark Energy Survey (DES) - due to its special combination of area (5000 deg. sq.) and depth ($i = 24.3$) - would be in the position to detect massive ($\gtrsim 10^{11}$ M$_{\odot}$)…
We present a search for galaxy-scale strong gravitational lenses in the initial 2 500 square degrees of the Canada-France Imaging Survey (CFIS). We designed a convolutional neural network (CNN) committee that we applied to a selection of 2…
Convolutional Neural Networks (ConvNets) are one of the most promising methods for identifying strong gravitational lens candidates in survey data. We present two ConvNet lens-finders which we have trained with a dataset composed of real…
We present the Dark Energy Spectroscopic Instrument (DESI) Strong Lens Foundry. We discovered $\sim 3500$ new strong gravitational lens candidates in the DESI Legacy Imaging Surveys using residual neural networks (ResNet). We observed a…
Machine learning models can greatly improve the search for strong gravitational lenses in imaging surveys by reducing the amount of human inspection required. In this work, we test the performance of supervised, semi-supervised, and…
Ongoing and future imaging surveys represent significant improvements in depth, area and seeing compared to current data-sets. These improvements offer the opportunity to discover up to three orders of magnitude more galaxy-galaxy strong…
The volume of data that will be produced by new-generation surveys requires automatic classification methods to select and analyze sources. Indeed, this is the case for the search for strong gravitational lenses, where the population of the…
We present a systematic search for wide-separation (Einstein radius >1.5"), galaxy-scale strong lenses in the 30 000 sq.deg of the Pan-STARRS 3pi survey on the Northern sky. With long time delays of a few days to weeks, such systems are…
We employ self-supervised representation learning to distill information from 76 million galaxy images from the Dark Energy Spectroscopic Instrument Legacy Imaging Surveys' Data Release 9. Targeting the identification of new strong…
We present galaxy-galaxy lensing measurements from 1321 sq. deg. of the Dark Energy Survey (DES) Year 1 (Y1) data. The lens sample consists of a selection of 660,000 red galaxies with high-precision photometric redshifts, known as redMaGiC,…
We present integral field spectroscopic observations of 75 strong gravitational lens candidates identified with a residual neural network in the DESI Legacy Imaging Surveys, obtained with the Multi Unit Spectroscopic Explorer (MUSE) on the…
We conduct a search for galaxy-scale strong gravitational lens systems in Data Release 4 of the Hyper Suprime-Cam Subaru Strategic Program (HSC SSP), consisting of data taken up to the S21A semester. We select 103191 luminous red galaxies…
We present the Dark Energy Spectroscopic Instrument (DESI) Strong Lensing Secondary Target Program. This is a spectroscopic follow-up program for strong gravitational lens candidates found in the DESI Legacy Imaging Surveys footprint.…
Here, we present a catalog of blended spectra in Data Release 1 of the Deep Extragalactic VIsible Legacy Survey (DEVILS) on the Anglo-Australian Telescope (AAT). Of the 23197 spectra, 181 showed signs of a blend of redshifts and spectral…
We present the first catalog of 67 strong galaxy-galaxy lens candidates discovered in the 1.64 square degree Hubble Space Telescope COSMOS survey. Twenty of these systems display multiple images or strongly curved large arcs. Our initial…
Convolutional Neutral Networks have been successfully applied in searching for strong lensing systems, leading to discoveries of new candidates from large surveys. On the other hand, systematic investigations about their robustness are…
We apply a novel model based on convolutional neural networks (CNNs) to identify gravitationally-lensed galaxies in multi-band imaging of the Hyper Suprime Cam Subaru Strategic Program (HSC-SSP) Survey. The trained model is applied to a…
Lensed quasars are powerful probes of cosmology, the co-evolution of supermassive black holes and their host galaxies, and the distribution of dark matter. We cross-match 1,724 previously identified candidates from KiDS, HSC, and the DESI…
Bright galaxy-galaxy strong lenses are much more powerful than lensed quasars for measuring the mass profiles of galaxies, but until this year only a handful have been known. Here we present five new examples, identified via the optimal…
We present in this paper one of the largest galaxy morphological classification catalogues to date, including over 20 million of galaxies, using the Dark Energy Survey (DES) Year 3 data based on Convolutional Neural Networks (CNN).…