| Autor: |
Krippendorf, Sven, Perez, Nicolas Baron, Bulbul, Esra, Kara, Melih, Seppi, Riccardo, Comparat, Johan, Artis, Emmanuel, Bahar, Emre, Garrel, Christian, Ghiardini, Vittorio, Kluge, Matthias, Liu, Ang, Ramos-Ceja, Miriam E., Sanders, Jeremy, Zhang, Xiaoyuan, Brüggen, Marcus, Grandis, Sebastian, Weller, Jochen |
| Rok vydání: |
2023 |
| Předmět: |
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| Druh dokumentu: |
Working Paper |
| Popis: |
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 using supervised learning on simulations of eROSITA observations, focusing in this paper on the Final Equatorial Depth Survey (eFEDS). We use convolutional neural networks which are modified to include additional information of the cluster, in particular its redshift. In contrast to existing work, we utilize simulations including background and point sources to develop a tool which is usable directly on observational eROSITA data for an extended mass range from group size halos to massive clusters with masses in between $10^{13}M_\odotComment: 10 pages, 8 figures |
| Databáze: |
arXiv |
| Externí odkaz: |
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