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192 papers
Growth from KiDS: Stellar mass assembly of galaxies since z=2 in the light of Kilo-Degree Survey
Qingshan Wang, Antonios Katsianis, Nicola R. Napolitano +10
We measure the galaxy stellar mass function at using 28M galaxies from the KiDS DR4 which spans an effective survey area of 676.9 deg. Combining nine-band photometry…
LenNet: Direct Detection and Localization of Strong Gravitational Lenses in Wide-Field Sky Survey Images
Pufan Liu, Hui Li, Ziqi Li +9
Strong gravitational lenses are invaluable tools for addressing fundamental questions in astrophysics, from the nature of dark matter to the expansion of the universe. While curren…
CASCO: Cosmological and AStrophysical parameters from Cosmological simulations and Observations IV. Testing warm dark matter cosmologies with galaxy scaling relations: A joint simulation-observation study using DREAMS simulations
M. Silvestrini, C. Tortora, V. Busillo +9
Small-scale discrepancies in the standard Lambda cold dark matter paradigm have motivated the exploration of alternative dark matter (DM) models, such as warm dark matter (WDM). We…
Euclid Quick Data Release (Q1). LEMON -- Lens Modelling with Neural networks. Automated and fast modelling of Euclid gravitational lenses with a singular isothermal ellipsoid mass profile
Euclid Collaboration, V. Busillo, C. Tortora +312
The Euclid mission aims to survey around 14000 deg^{2} of extragalactic sky, providing around 10^{5} gravitational lens images. Modelling of gravitational lenses is fundamental to…
CASCO: Cosmological and AStrophysical parameters from Cosmological simulations and Observations III. The physics behind the emergence of the golden mass scale
C. Tortora, V. Busillo, N. R. Napolitano +5
We investigate the origin and evolution of the "golden mass" (halo mass , stellar mass ), linked to peak star f…
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…