activity
19952025
most citedKiDS-450: Cosmological parameter constraints from tomographic weak gravitational lensing

1k citations · 5.9k across the 100 of their papers we have counts for

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Showing astro-ph.GAShow all

24 papers · 1 filter

astro-ph.GA2024★ 17 cited

Euclid preparation. XLIII. Measuring detailed galaxy morphologies for Euclid with machine learning

Euclid Collaboration, B. Aussel, S. Kruk +255

The Euclid mission is expected to image millions of galaxies with high resolution, providing an extensive dataset to study galaxy evolution. We investigate the application of deep…

astro-ph.GA2023

DenseLens -- Using DenseNet ensembles and information criteria for finding and rank-ordering strong gravitational lenses,

Bharath Chowdhary Nagam, Léon V. E. Koopmans, Edwin A. Valentijn +5

Convolutional neural networks (CNNs) are the state-of-the-art technique for identifying strong gravitational lenses. Although they are highly successful in recovering genuine lens…

astro-ph.GA2023

Euclid preparation. Spectroscopy of active galactic nuclei with NISP

Euclid Collaboration, E. Lusso, S. Fotopoulou +246

The statistical distribution and evolution of key properties (e.g. accretion rate, mass, or spin) of active galactic nuclei (AGN), remain an open debate in astrophysics. The ESA Eu…

astro-ph.GA2023★ 14 cited

Euclid preparation. XXX. Performance assessment of the NISP Red-Grism through spectroscopic simulations for the Wide and Deep surveys

Euclid Collaboration, L. Gabarra, C. Mancini +232

This work focuses on the pilot run of a simulation campaign aimed at investigating the spectroscopic capabilities of the Euclid Near-Infrared Spectrometer and Photometer (NISP), in…

astro-ph.GA2022★ 19 cited

The SAMI -- Fornax Dwarfs Survey II: The Stellar Mass Fundamental Plane and the Dark Matter fraction of Dwarf Galaxies

F. Sara Eftekhari, Reynier F. Peletier, Nicholas Scott +14

We explore the kinematic scaling relations of 38 dwarf galaxies in the Fornax Cluster using observations from the SAMI integral field spectrograph. We focus on the Fundamental Plan…

astro-ph.GA2022

Euclid preparation: XXIII. Derivation of galaxy physical properties with deep machine learning using mock fluxes and H-band images

Euclid Collaboration, L. Bisigello, C. J. Conselice +196

Next generation telescopes, like Euclid, Rubin/LSST, and Roman, will open new windows on the Universe, allowing us to infer physical properties for tens of millions of galaxies. Ma…