17 citations · 48 across the 5 of their papers we have counts for
5 papers
The SRG/eROSITA All-Sky Survey. The Weak-Lensing Mass Calibration and the Stellar Mass-to-Halo Mass Relation from the Hyper Suprime-Cam Subaru Strategic Program
I-Non Chiu, Vittorio Ghirardini, Sebastian Grandis +23
We present the weak-lensing mass calibration and constrain the BCG (brightest cluster galaxy) stellar-mass-to-halo-mass-and-redshift () relation for a s…
The SRG/eROSITA All-Sky Survey : Subaru/HSC-SSP weak-lensing mass measurements for the eRASS1 Galaxy Clusters
Nobuhiro Okabe, Thomas H. Reiprich, Sebastian Grandis +20
We performed individual weak-lensing (WL) mass measurements for 78 eROSITA's first All-Sky Survey (eRASS1) clusters in the footprint of Hyper Suprime-Cam Subaru Strategic Program (…
The hot gas mass fraction in halos. From Milky Way-like groups to massive clusters
P. Popesso, A. Biviano, I. Marini +21
By using eROSITA data in the eFEDS area, we provide a measure of the hot gas fraction vs. halo mass relation over the largest halo mass range, from Milky Way-sized halos to massive…
The SRG/eROSITA All-Sky Survey: Weak-Lensing of eRASS1 Galaxy Clusters in KiDS-1000 and Consistency Checks with DES Y3 & HSC-Y3
Florian Kleinebreil, Sebastian Grandis, Tim Schrabback +21
We aim to participate in the calibration of the X-ray photon count rate to halo mass scaling relation of galaxy clusters selected in the first eROSITA All-Sky Survey on the Western…
The eROSITA Final Equatorial-Depth Survey (eFEDS): A Machine Learning Approach to Infer Galaxy Cluster Masses from eROSITA X-ray Images
Sven Krippendorf, Nicolas Baron Perez, Esra Bulbul +15
We develop a neural network based pipeline to estimate masses of galaxy clusters with a known redshift directly from photon information in X-rays. Our neural networks are trained u…