ERGO-ML I: inferring the assembly histories of IllustrisTNG galaxies from integral observable properties via invertible neural networks
A fundamental prediction of the ΛCDM cosmology is the hierarchical build-up of structure and therefore the successive merging of galaxies into more massive ones. As one can only observe galaxies at one specific time in the cosmic history, this merger history remains, in principle, unobservable. By u...
Gespeichert in:
| Hauptverfasser: | , , , , , |
|---|---|
| Dokumenttyp: | Article (Journal) |
| Sprache: | Englisch |
| Veröffentlicht: |
2023
|
| In: |
Monthly notices of the Royal Astronomical Society
Year: 2023, Jahrgang: 519, Heft: 2, Pages: 2199-2223 |
| ISSN: | 1365-2966 |
| DOI: | 10.1093/mnras/stac3295 |
| Online-Zugang: | Verlag, kostenfrei, Volltext: https://doi.org/10.1093/mnras/stac3295
|
| Verfasserangaben: | Lukas Eisert, Annalisa Pillepich, Dylan Nelson, Ralf S. Klessen, Marc Huertas-Company and Vicente Rodriguez-Gomez |
Search Result 1
ERGO-ML I: inferring the assembly histories of IllustrisTNG galaxies from integral observable properties via invertible neural networks
Article (Journal)
Kapitel/Artikel
Online Resource