Related papers: Automated Lensing Learner: Automated Strong Lensin…
We investigate the merits of a massive forward modeling of ground-based optical imaging as a diagnostic for the strong lensing nature of Early-Type Galaxies, in the light of which blurred and faint Einstein rings can hide. We simulate…
Large scale imaging surveys will increase the number of galaxy-scale strong lensing candidates by maybe three orders of magnitudes beyond the number known today. Finding these rare objects will require picking them out of at least tens of…
Convolution Neural Networks trained for the task of lens finding with similar architecture and training data as is commonly found in the literature are biased classifiers. An understanding of the selection function of lens finding neural…
The distribution of dark and luminous matter can be mapped around galaxies that gravitationally lens background objects into arcs or Einstein rings. New surveys will soon observe hundreds of thousands of galaxy lenses, and current,…
This work presents AutoLens, the first entirely automated modeling suite for the analysis of galaxy-scale strong gravitational lenses. AutoLens simultaneously models the lens galaxy's light and mass whilst reconstructing the extended source…
With a primary goal of conducting precision weak lensing measurements from space, the COSMOS survey has imaged the largest contiguous area observed by the Hubble Space Telescope (HST) to date using the Advanced Camera for Surveys (ACS).…
Cosmic shear is a primary cosmological probe for several present and upcoming surveys investigating dark matter and dark energy, such as Euclid or WFIRST. The probe requires an extremely accurate measurement of the shapes of millions of…
Challenges inherent to high-resolution and high signal-to-noise data as well as model degeneracies can cause systematic biases in analyses of strong lens systems. In the past decade, the number of lens modeling methods has significantly…
We explore the effectiveness of deep learning convolutional neural networks (CNNs) for estimating strong gravitational lens mass model parameters. We have investigated a number of practicalities faced when modelling real image data, such as…
We have carried out HST snapshot observations at 1.1 $\mu$m of 281 candidate strongly lensed galaxies identified in the wide-area extragalactic surveys conducted with the Herschel space observatory. Our candidates comprise systems with flux…
We consider a machine learning algorithm to detect and identify strong gravitational lenses on sky images. First, we simulate different artificial but very close to reality images of galaxies, stars and strong lenses, using six different…
Cluster-scale strong lensing is a powerful tool for exploring the properties of dark matter and constraining cosmological models. However, due to the complex parameter space, pixelized strong lens modeling in galaxy clusters is…
We present the weak lensing and optical analysis of the SL2S-ARCS (SARCS) sample of strong lens candidates. The sample is based on the Strong Lensing Legacy Survey (SL2S), a systematic search of strong lensing systems in the photometric…
Galaxy-galaxy strong lensing provides a powerful probe of galaxy formation, evolution, and the properties of dark matter and dark energy. However, conventional lens-modeling approaches are computationally expensive and require fine-tuning…
Strong gravitational lensing by galaxies is a powerful tool for studying cosmology and galaxy structure. The China Space Station Telescope (CSST) will revolutionize this field by discovering up to $\sim$100,000 galaxy-scale strong lenses, a…
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…
Vast amounts of astronomical photometric data are generated from various projects, requiring significant effort to identify variable stars and other object classes. In light of this, a general, widely applicable classification framework…
As new large-scale astronomical surveys greatly increase the number of objects targeted and discoveries made, the requirement for efficient follow-up observations is crucial. Adaptive optics imaging, which compensates for the image-blurring…
Efficient algorithms are being developed to search for strong gravitational lens systems owing to increasing large imaging surveys. Neural networks have been successfully used to discover galaxy-scale lens systems in imaging surveys such as…
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 lenses. However, supervised machine-learning approaches…