Related papers: Image segmentation for analyzing galaxy-galaxy str…
Classification of galactic morphologies is a crucial task in galactic astronomy, and identifying fine structures of galaxies (e.g., spiral arms, bars, and clumps) is an essential ingredient in such a classification task. However, seeing…
Measuring dark matter substructure within galaxy cluster haloes is a fundamental probe of the Lambda-CDM model of structure formation. Gravitational lensing is a technique for measuring the total mass distribution which is independent of…
Strong gravitational lensing at the galaxy scale is a valuable tool for various applications in astrophysics and cosmology. The primary uses of galaxy-scale lensing are to study elliptical galaxies' mass structure and evolution, constrain…
The statistics of Einstein radii for a sample of strong lenses can provide valuable constraints on the underlying mass distribution. The correct interpretation, however, relies critically on the modelling of the selection of the sample,…
Stringent observational constraints on the sub-galactic matter power spectrum would allow one to distinguish between the concordance $\Lambda$CDM and the various alternative dark-matter models that predict significantly different properties…
Weak gravitational lensing is the slight distortion of galaxy shapes caused primarily by the gravitational effects of dark matter in the universe. In our work, we seek to invert the weak lensing signal from 2D telescope images to…
Galaxy-galaxy strong gravitational lenses have become a popular probe of dark matter (DM) by providing a window into structure formation on the smallest scales. In particular, the convergence power spectrum of subhalos within lensing…
Context. Strong lenses are a biased subset of the general population of galaxies. Aims. The goal of this work is to quantify how lens galaxies and lensed sources differ from their parent distribution, namely the strong lensing bias.…
Small distortions in the images of Einstein rings or giant arcs offer the exciting prospect of detecting dark matter haloes or subhaloes of mass below $10^9$M$_{\odot}$, most of which are too small to have made a visible galaxy. A very…
With the advent of future big-data surveys, automated tools for unsupervised discovery are becoming ever more necessary. In this work, we explore the ability of deep generative networks for detecting outliers in astronomical imaging…
A generic prediction of particle dark matter theories is that a large population of dark matter substructures should reside inside the host haloes of galaxies. In gravitational imaging, strong gravitational lens observations are used to…
We investigate the gravitational lensing properties of dark matter halos with Burkert profiles. We derive an analytic expression for the lens equation and use it to compute the magnification, impact parameter and image separations for…
If the dark matter halos of galaxies contain large numbers of subhalos as predicted by the $\Lambda$CDM model, these subhalos are expected to appear in strong galaxy--galaxy lens systems as small--scale perturbations in individual images.…
As a computer vision task, automatic object segmentation remains challenging in specialized image domains without massive labeled data, such as synthetic aperture sonar images, remote sensing, biomedical imaging, etc. In any domain,…
Dark matter is an important ingredient of galaxies, as was recognised early on by Ken Freeman himself! Evidence for dark matter halos is still indirect, based on analysing motions of tracers such as gas and stars. In a sense the visible…
In this paper, we propose a new method to use the strong lensing data sets to constrain a cosmological model. By taking the ratio…
Cosmological cluster-scale strong gravitational lensing probes the mass distribution of the dense cores of massive dark matter halos and the structures along the line of sight from background sources to the observer. It is frequently…
Image segmentation is an important component of many image understanding systems. It aims to group pixels in a spatially and perceptually coherent manner. Typically, these algorithms have a collection of parameters that control the degree…
We propose an end-to-end learning framework for segmenting generic objects in both images and videos. Given a novel image or video, our approach produces a pixel-level mask for all "object-like" regions---even for object categories never…
We explore the use of strong lensing by galaxy clusters to constrain the dark energy equation of state and its possible time variation. The cores of massive clusters often contain several multiply imaged systems of background galaxies at…