activity
20202026
most citedGalaxyNet: Connecting galaxies and dark matter haloes with deep neural networks and reinforcement learning in large volumes

62 citations · 165 across the 6 of their papers we have counts for

collaborators

6 papers

astro-ph.GA2026

Blue Monsters and Dusty Descendants: Reconciling UV and IR Emission from Galaxies from z=7, up to z= 14

Laura Sommovigo, Lachlan Lancaster, Shyam H. Menon +3

Recent JWST observations reveal massive, UV-bright galaxies at with little apparent dust attenuation, whereas ALMA detections at show similarly massive system…

astro-ph.GA2023★ 8 cited

Predictions on the stellar-to-halo mass relation in the dwarf regime using the empirical model for galaxy formation EMERGE

Joseph A. O'Leary, Ulrich P. Steinwandel, Benjamin P. Moster +2

One of the primary goals when studying galaxy formation is to understand how the luminous component of the Universe, galaxies, relates to the growth of structure which is dominated…

astro-ph.GA2020★ 29 cited

Globular cluster numbers in dark matter haloes in a dual formation scenario: an empirical model within EMERGE

Lucas M. Valenzuela, Benjamin P. Moster, Rhea-Silvia Remus +2

We present an empirical model for the number of globular clusters (GCs) in galaxies based on recent data showing a tight relationship between dark matter halo virial masses and GC…

astro-ph.GA2020★ 7 cited

EMERGE: Constraining merging probabilities and timescales of close galaxy pairs

Joseph A. O'Leary, Benjamin P. Moster, Eva Krämer

Theoretical models are vital for exploring the galaxy merger process, which plays a crucial role in the evolution of galaxies. Recent advances in modelling have placed tight constr…

astro-ph.GA2020★ 62 cited

GalaxyNet: Connecting galaxies and dark matter haloes with deep neural networks and reinforcement learning in large volumes

Benjamin P. Moster, Thorsten Naab, Magnus Lindström +1

We present the novel wide & deep neural network GalaxyNet, which connects the properties of galaxies and dark matter haloes, and is directly trained on observed galaxy statistics u…

astro-ph.GA2020★ 59 cited

EMERGE: Empirical predictions of galaxy merger rates since

Joseph A. O'Leary, Benjamin P. Moster, Thorsten Naab +1

We explore the galaxy-galaxy merger rate with the empirical model for galaxy formation, Emerge. On average, we find that between per cent and per cent of massive galaxies…