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Modeling the mass distribution of galaxy-scale strong gravitational lenses is a task of increasing difficulty. The high-resolution and depth of imaging data now available render simple analytical forms ineffective at capturing lens…

Instrumentation and Methods for Astrophysics · Physics 2022-12-21 Aymeric Galan , Georgios Vernardos , Austin Peel , Frédéric Courbin , Jean-Luc Starck

With the dramatic rise in high-quality galaxy data expected from Euclid and Vera C. Rubin Observatory, there will be increasing demand for fast high-precision methods for measuring galaxy fluxes. These will be essential for inferring the…

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…

Cosmology and Nongalactic Astrophysics · Physics 2017-07-19 Jorit Schmelzle , Aurelien Lucchi , Tomasz Kacprzak , Adam Amara , Raphael Sgier , Alexandre Réfrégier , Thomas Hofmann

As one of the probes of universe, strong gravitational lensing systems allow us to compare different cosmological models and constrain vital cosmological parameters. This purpose can be reached from the dynamic and geometry properties of…

Cosmology and Nongalactic Astrophysics · Physics 2015-08-06 C. C. Yuan , F. Y. Wang

Cluster strong lensing cosmography is a promising probe of the background geometry of the Universe and several studies have emerged, thanks to the increased quality of observations using space and ground-based telescopes. For the first…

Cosmology and Nongalactic Astrophysics · Physics 2022-01-19 G. B. Caminha , S. H. Suyu , C. Grillo , P. Rosati

We present a method for automatic detection and classification of galaxies which includes a novel data-augmentation procedure to make trained models more robust against the data taken from different instruments and contrast-stretching…

Instrumentation and Methods for Astrophysics · Physics 2018-09-07 Roberto E. González , Roberto P. Muñoz , Cristian A. Hernández

In the coming years, a new generation of sky surveys, in particular, Euclid Space Telescope (2022), and the Rubin Observatory's Legacy Survey of Space and Time (LSST, 2023) will discover more than 200,000 new strong gravitational lenses,…

Cosmology and Nongalactic Astrophysics · Physics 2022-06-15 Ronan Legin , Yashar Hezaveh , Laurence Perreault Levasseur , Benjamin Wandelt

Strong gravitational lensing provides unique opportunities to investigate the mass distribution at the cores of galaxy clusters and to study high redshift galaxies. Using $94$ strong lensing models of $74$ cluster fields from the…

Cosmology and Nongalactic Astrophysics · Physics 2022-04-06 Carter Fox , Guillaume Mahler , Keren Sharon , Juan D. Remolina González

Convolutional Neural Networks (ConvNets) are one of the most promising methods for identifying strong gravitational lens candidates in survey data. We present two ConvNet lens-finders which we have trained with a dataset composed of real…

Like light, gravitational waves can be gravitationally lensed by massive astrophysical objects. Strong gravitational lensing by galaxies and galaxy clusters is anticipated to become observable in the coming years. This phenomenon will…

General Relativity and Quantum Cosmology · Physics 2025-06-03 Leo C. Y. Ng , Justin Janquart , Hemantakumar Phurailatpam , Harsh Narola , Jason S. C. Poon , Chris Van Den Broeck , Otto A. Hannuksela

Gravitational lensing is a powerful astrophysical and cosmological probe and is particularly valuable at submillimeter wavelengths for the study of the statistical and individual properties of dusty starforming galaxies. However the…

Strong gravitational lensing is a unique observational tool for studying the dark and luminous mass distribution both within and between galaxies. Given the presence of substructures, current strong lensing observations demand more complex…

Instrumentation and Methods for Astrophysics · Physics 2023-07-19 Luca Biggio , Georgios Vernardos , Aymeric Galan , Austin Peel

In a strong gravitational lensing system, the distorted light from a source is analysed to infer the properties of the lens. However, light emitted by the lens itself can contaminate the image of the source, introducing systematic errors in…

We have conducted a search for strong gravitational lensing systems in the Dark Energy Spectroscopic Instrument (DESI) Legacy Imaging Surveys Data Release 10 (DR10). This paper is the fourth in a series of searches (following Huang et al.…

Strong gravitational lensing is a promising probe of the substructure of dark matter halos. Deep learning methods have the potential to accurately identify images containing substructure, and differentiate WIMP dark matter from other well…

Cosmology and Nongalactic Astrophysics · Physics 2020-04-09 Stephon Alexander , Sergei Gleyzer , Evan McDonough , Michael W. Toomey , Emanuele Usai

The light we observe from distant astrophysical objects including supernovae and quasars allows us to determine large distances in terms of a cosmological model. Despite the success of the standard cosmological model in fitting the data,…

Cosmology and Nongalactic Astrophysics · Physics 2024-05-07 Angela L. H. Ng

Strongly lensed quasars provide valuable insights into the rate of cosmic expansion, the distribution of dark matter in foreground deflectors, and the characteristics of quasar hosts. However, detecting them in astronomical images is…

We present a new sample of galaxy-scale strong gravitational-lens candidates, selected from 904 square degrees of Data Release 4 of the Kilo-Degree Survey (KiDS), i.e., the "Lenses in the Kilo-Degree Survey" (LinKS) sample. We apply two…

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.…

Astrophysics of Galaxies · Physics 2023-09-29 Alessandro Sonnenfeld , Shun-Sheng Li , Giulia Despali , Raphael Gavazzi , Anowar J. Shajib , Edward N. Taylor
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