activity
20242026
most citedClassifying merger stages with adaptive deep learning and cosmological hydrodynamical simulations

2 citations · 2 across the 5 of their papers we have counts for

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5 papers · 1 filter

astro-ph.GA2025

Super-resolving Herschel - a deep learning based deconvolution and denoising technique

Dennis Koopmans, Lingyu Wang, Berta Margalef-Bentabol +9

Dusty star-forming galaxies (DSFGs) dominate the far-infrared and sub-millimetre number counts, but single-dish surveys suffer from poor angular resolution, complicating mult-wavel…

astro-ph.GA20252 cited

Classifying merger stages with adaptive deep learning and cosmological hydrodynamical simulations

Rosa de Graaff, Berta Margalef-Bentabol, Lingyu Wang +4

Hierarchical merging of galaxies plays an important role in galaxy formation and evolution. Mergers could trigger key evolutionary phases such as starburst activities and active ac…

astro-ph.GA20249 cited

Probabilistic and progressive deblended far-infrared and sub-millimetre point source catalogues I. Methodology and first application in the COSMOS field

Lingyu Wang, Antonio La Marca, Fangyou Gao +12

Single-dish far-infrared (far-IR) and sub-millimetre (sub-mm) point source catalogues and their connections with catalogues at other wavelengths are of paramount importance. Howeve…

astro-ph.GA2024

The TNG50-SKIRT Atlas: wavelength dependence of the effective radius

Maarten Baes, Aleksandr Mosenkov, Raymond Kelly +17

Galaxy sizes correlate with many other important properties of galaxies, and the cosmic evolution of galaxy sizes is an important observational diagnostic for constraining galaxy e…

astro-ph.GA2024

The TNG50-SKIRT Atlas: post-processing methodology and first data release

Maarten Baes, Andrea Gebek, Ana Trcka +17

Galaxy morphology is a powerful diagnostic to assess the realism of cosmological hydrodynamical simulations. Determining the morphology of simulated galaxies requires the generatio…