Related papers: Deep Learning the Morphology of Dark Matter Substr…
Strong gravitational lensing is a powerful tool for probing the matter distribution in the cores of massive dark matter haloes. Recent and ongoing analyses of galaxy cluster surveys (MACS, CFHTLS, SDSS, SGAS, CLASH, LoCuSS) have adressed…
In the field of pattern recognition research, the method of using deep neural networks based on improved computing hardware recently attracted attention because of their superior accuracy compared to conventional methods. Deep neural…
Dark matter plays a crucial role in our comprehension of the universe, but its mysterious nature poses challenges for direct detection. A primary obstacle in detecting dark matter is distinguishing genuine signals from the prevailing…
Strong gravitational lensing is a powerful probe of the distribution of matter on sub-kpc scales. It can be used to test the existence of completely dark subhalos surrounding galaxies, as predicted by the standard cold dark matter model, or…
Dark matter caustics have specific density profiles and, therefore, precisely calculable gravitational lensing properties. We present a formalism which simplifies the relevant calculations, and apply it to four specific cases. In the first…
The Dark Matter present in the Large-Scale Structure of the Universe is invisible, but its presence can be inferred through the small gravitational lensing effect it has on the images of far away galaxies. By measuring this lensing effect…
To set useful limits on the abundance of small-scale dark matter halos (subhalos) in a galaxy scale, we have carried out mid-infrared imaging and integral-field spectroscopy for a sample of quadruple lens systems showing anomalous flux…
It is difficult to quantify structure-property relationships and to identify structural features of complex materials. The characterization of amorphous materials is especially challenging because their lack of long-range order makes it…
Strong gravitational lensing provides a powerful tool to directly infer the dark matter (DM) subhalo mass function (SHMF) in lens galaxies. However, comparing observationally inferred SHMFs to theoretical predictions remains challenging, as…
The advent of new deep+wide photometric lensing surveys will open up the possibility of direct measurements of the dark matter halos of dwarf galaxies. The HSC wide survey will be the first with the statistical capability of measuring the…
Large cosmological datasets have been probing the properties of our universe and constraining the parameters of dark matter and dark energy with increasing precision. Deep learning techniques have shown potential to be smarter, and to…
The arrival times, positions, and fluxes of multiple images in strong lens systems can be used to infer the presence of dark subhalos in the deflector, and thus test predictions of cold dark matter models. However, gravitational lensing…
Deep learning architectures based on convolutional neural networks tend to rely on continuous, smooth features. While this characteristics provides significant robustness and proves useful in many real-world tasks, it is strikingly…
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…
We demonstrate the potential of Deep Learning methods for measurements of cosmological parameters from density fields, focusing on the extraction of non-Gaussian information. We consider weak lensing mass maps as our dataset. We aim for our…
Deep-learning algorithms enable precise image recognition based on high-dimensional hierarchical image features. Here, we report the development and implementation of a deep-learning-based image segmentation algorithm in an autonomous…
The GRavitational lEnsing Accuracy Testing 2008 (GREAT08) Challenge focuses on a problem that is of crucial importance for future observations in cosmology. The shapes of distant galaxies can be used to determine the properties of dark…
Strong lensing in galaxy clusters probes properties of dense cores of dark matter halos in mass, studies the distant universe at flux levels and spatial resolutions otherwise unavailable, and constrains cosmological models independently.…
Gravitational lensing by galaxy clusters has emerged as a powerful tool to probe the standard Cold Dark Matter (CDM) paradigm of structure formation in the Universe. Despite the remarkable explanatory power of CDM on large scales, tensions…
The cold dark matter (DM) model predicts that every galaxy contains thousands of DM subhalos; almost all other DM models include a physical process that smooths away the subhalos. The subhalos are invisible, but could be detected via strong…