Related papers: Substructure Detection in Realistic Strong Lensing…
The abundance of dark matter (DM) subhalos orbiting a host galaxy is a generic prediction of the cosmological framework, and is a promising way to constrain the nature of DM. In this paper, we investigate the use of machine learning-based…
A defining prediction of the cold dark matter (CDM) cosmological model is the existence of a very large population of low-mass haloes. This population is absent in models in which the dark matter particle is warm (WDM). These alternatives…
We demonstrate that the perturbations of strongly lensed images by low-mass dark matter subhalos are significantly impacted by the concentration of the perturbing subhalo. For subhalo concentrations expected in $\Lambda$CDM, significant…
We analyse the properties of substructures within dark matter halos (subhalos) using a set of high-resolution numerical simulations of the formation of structure in a Lambda-CDM Universe. Our simulation set includes 11 high-resolution…
Weak gravitational lensing of distant galaxies by foreground structures has proven to be a powerful tool to study the mass distribution in the universe. The advent of panoramic cameras on 4m class telescope has led to a first generation of…
Recently, ``CDM crisis'' is under discussion. The main point of this crisis is that number of substructures presented by cosmological N-body simulations based on CDM scenario for structure formation is much larger than observed…
We describe the first results from two observational projects aimed at measuring the amount and spatial distribution of dark matter in distant early-type galaxies (E/S0s) and clusters of galaxies. At the galaxy scale, the Lenses Structure…
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…
We address the question of how well the density profile of galaxy clusters can be determined by combining strong lensing and velocity dispersion data. We use cosmological dark matter simulations of clusters to test the reliability of the…
Conventional galaxy mass estimation methods suffer from model assumptions and degeneracies. Machine learning, which reduces the reliance on such assumptions, can be used to determine how well present-day observations can yield predictions…
We demonstrate a machine learning approach designed to extract hidden chemistry/physics to facilitate new materials discovery. In particular, we propose a novel method for learning latent knowledge from material structure data in which…
Two-dimensional materials are a class of atomically thin materials with assorted electronic and quantum properties. Accurate identification of layer thickness, especially for a single monolayer, is crucial for their characterization. This…
A galaxy cluster acts as a cosmic telescope over background galaxies but also as a cosmic microscope of the lens imperfections. The diverging magnification of lensing caustics enhances the microlensing effect of substructure present within…
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…
Strong gravitational lensing is a powerful probe for studying the fundamental properties of dark matter on sub-galactic scales. Detailed analyses of galaxy-scale lenses have revealed localized gravitational perturbations beyond the smooth…
Machine learning, and eventually true artificial intelligence techniques, are extremely important advancements in astrophysics and astronomy. We explore the application of deep learning using neural networks in order to automate the…
Different models of dark matter can alter the distribution of mass in galaxy clusters in a variety of ways. However, so can uncertain astrophysical feedback mechanisms. Here we present a Machine Learning method that ''learns'' how the…
Time delay cosmography uses the arrival time delays between images in strong gravitational lenses to measure cosmological parameters, in particular the Hubble constant $H_0$. The lens models used in time delay cosmography omit dark matter…
Weak gravitational lensing is rapidly becoming one of the principal probes of dark matter and dark energy in the universe. In this brief review we outline how weak lensing helps determine the structure of dark matter halos, measure the…
We propose a novel method to select satellite galaxies in outer regions of galaxy groups or clusters using weak gravitational lensing. The method is based on the theoretical expectation that the tangential shear pattern around satellite…