57 citations · 196 across the 11 of their papers we have counts for
8 papers · 1 filter
ERGO-ML: The assembly histories of HSC galaxy images via invertible neural networks, contrastive learning, and cosmological simulations
Lukas Eisert, Connor Bottrell, Annalisa Pillepich +4
In this paper of ERGO-ML (Extracting Reality from Galaxy Observables with Machine Learning), we develop a model that infers the merger/assembly histories of galaxies directly from…
ERGO-ML: A continuous organization of the X-ray galaxy cluster population in TNG-Cluster with contrastive learning
Urmila Chadayammuri, Lukas Eisert, Annalisa Pillepich +3
The physical properties of the intracluster medium (ICM) reflect signatures of the underlying gravitational potential, mergers and strong interactions with other halos and satellit…
Constraints on the in-situ and ex-situ stellar masses in nearby galaxies with Artificial Intelligence
Eirini Angeloudi, Jesús Falcón-Barroso, Marc Huertas-Company +4
The hierarchical model of galaxy evolution suggests that the impact of mergers is substantial on the intricate processes that drive stellar assembly within a galaxy. However, accur…
ERGO-ML: Comparing IllustrisTNG and HSC galaxy images via contrastive learning
Lukas Eisert, Connor Bottrell, Annalisa Pillepich +5
Modern cosmological hydrodynamical galaxy simulations provide tens of thousands of reasonably realistic synthetic galaxies across cosmic time. However, quantitatively assessing the…
IllustrisTNG in the HSC-SSP: image data release and the major role of mini mergers as drivers of asymmetry and star formation
Connor Bottrell, Hassen M. Yesuf, Gergö Popping +13
At fixed galaxy stellar mass, there is a clear observational connection between structural asymmetry and offset from the star forming main sequence, SFMS. Herein, we use the TNG…
ERGO-ML: Towards a robust machine learning model for inferring the fraction of accreted stars in galaxies from integral-field spectroscopic maps
Eirini Angeloudi, Jesús Falcón-Barroso, Marc Huertas-Company +4
Quantifying the contribution of mergers to the stellar mass of galaxies is key for constraining the mechanisms of galaxy assembly across cosmic time. However, the mapping between o…
The merger and assembly histories of Milky Way- and M31-like galaxies with TNG50: disk survival through mergers
Diego Sotillo-Ramos, Annalisa Pillepich, Martina Donnari +6
We analyze the merger and assembly histories of Milky Way (MW) and Andromeda (M31)-like galaxies to quantify how, and how often, disk galaxies of this mass can survive recent major…
ERGO-ML I: Inferring the assembly histories of IllustrisTNG galaxies from integral observable properties via invertible neural networks
Lukas Eisert, Annalisa Pillepich, Dylan Nelson +3
A fundamental prediction of the LambdaCDM cosmology is the hierarchical build-up of structure and therefore the successive merging of galaxies into more massive ones. As one can on…