Related papers: CMU DeepLens: Deep Learning For Automatic Image-ba…
Strong gravitational lenses are a rare and instructive type of astronomical object. Identification has long relied on serendipity, but different strategies -- such as mixed spectroscopy of multiple galaxies along the line of sight, machine…
We present the results of a new search for galaxy-scale strong lensing systems in CFHTLS Wide. Our lens-finding technique involves a preselection of potential lens galaxies, applying simple cuts in size and magnitude. We then perform a…
[Abridged] We exploit the clustering of massive galaxies to perform a high efficiency imaging search for gravitational lenses. Our dataset comprises 44 fields imaged by the Hubble Space Telescope (HST) Advanced Camera for Surveys (ACS),…
We have carried out a systematic search for galaxy-scale strong lenses in multiband imaging from the Hyper Suprime-Cam (HSC) survey. Our automated pipeline, based on realistic strong-lens simulations, deep neural network classification, and…
The goal of this paper is to develop a machine learning model to analyze the main gravitational lens and detect dark substructure (subhalos) within simulated images of strongly lensed galaxies. Using the technique of image segmentation, we…
With the advent of new spectroscopic surveys from ground and space, observing up to hundreds of millions of galaxies, spectra classification will become overwhelming for standard analysis techniques. To prepare for this challenge, we…
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…
The study of strong-lensing systems conventionally involves constructing a mass distribution that can reproduce the observed multiply-imaging properties. Such mass reconstructions are generically non-unique. Here, we present an alternative…
Strong lensing has developed into an important astrophysical tool for probing both cosmology and galaxies (their structure, formation, and evolution). Using the gravitational lensing theory and cluster mass distribution model, we try to…
We study the correlation between the locations of galaxy-galaxy strong lensing candidates and tracers of large-scale structure from both weak lensing or X-ray emission. The COSMOS survey is a unique data set, combining deep, high resolution…
Forthcoming imaging surveys will potentially increase the number of known galaxy-scale strong lenses by several orders of magnitude. For this to happen, images of tens of millions of galaxies will have to be inspected to identify potential…
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 Volume Exploration Survey (DELVE), which contains $\sim 520$…
Quantifying image distortions caused by strong gravitational lensing and estimating the corresponding matter distribution in lensing galaxies has been primarily performed by maximum likelihood modeling of observations. This is typically a…
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…
This article reviews recent advances in the application of machine learning to weak-lensing cosmology. Weak gravitational lensing provides a unique and powerful probe of the total matter distribution in the Universe, independent of its…
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 (CFHTLS) imaging for the identification of potential strong…
Whereas considerable effort has been afforded in understanding the properties of galaxies, a full physical picture, connecting their baryonic and dark-matter content, super-massive black holes, and (metric) theories of gravity, is still…
We use AStroLens, a newly developed gravitational lens-modeling code that relies only on geometric and photometric information of cluster galaxies as input, to map the strong-lensing regions and estimate the lensing strength of 96 galaxy…
Gravitational lensing has become one of the most powerful tools available for investigating the 'dark side' of the universe. Cosmological strong gravitational lensing, in particular, probes the properties of the dense cores of dark matter…
Studies of strong gravitational lensing in current and upcoming wide and deep photometric surveys, and of stellar kinematics from (integral-field) spectroscopy at increasing redshifts, promise to provide valuable constraints on galaxy…