57 citations · 196 across the 11 of their papers we have counts for
11 papers
An overview of stray light findings and interpretation during on-sky commissioning of LSSTCam
Gabriele Rodeghiero, Alex Drlica-Wagner, Alessio Taranto +78
Wide-field telescopes are intrinsically difficult to shield from unwanted stray and scattered light, while the search to identify sources of contaminating light is frequently a cha…
Modeling of the diffuse background produced by the Vera C. Rubin Observatory M2 baffle scattered light
Alessio Taranto, Gabriele Rodeghiero, Luca Rosignoli +58
The Vera C. Rubin Observatory, with its unprecedented field of view and fast focal ratio, will survey the entire sky every 3.5 nights. This unique capacity requires dealing with of…
The Vera C. Rubin Observatory Data Preview 1
Vera C Rubin Observatory Team, Tatiana Acero Cuellar, Emily Acosta +325
We present Rubin Data Preview 1 DP1, the first data from the NSF DOE Vera C Rubin Observatory, comprising raw and calibrated single epoch images, coadds, difference images, detecti…
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…