Speaker
Adam Malyali
(MPE)
Description
Due to eROSITA’s cadence and its 30-fold increased sensitivity in the soft X-ray band relative to ROSAT, eROSITA promises to detect 1000s of tidal disruption event (TDE) candidates during its all sky survey phase. I will present our machine-learning assisted approach for identifying TDE candidates amongst the millions of X-ray sources in eROSITA's source catalogues, and selected early results from the first months of the all-sky survey.
| Presenter status | eROSITA consortium member |
|---|
Primary authors
Adam Malyali
(MPE)
Dr
Arne Rau
(MPE Garching)
Prof.
Kirpal Nandra
(MPE Garching)
Andrea Merloni
Axel Schwope
(AIP)
