Speaker
Description
The rapid development of detector technology, including these sensitive to gravitational waves and neutrinos, has brought us to the gate of an era where we will be able to observe transient events as they unfold throughout a large fraction of the Universe. The availability of these data floods requires new systems for data processing and the consistent application of modern statistical methods ("machine learning").
I will here describe AMPEL, an open source development platform for real-time data analysis. Users develop and tune complex workflows in a local development environment which can be uploaded to a computer center for large-scale live processing or shared for reproducibility, effectively introducing the "code-to-data" paradigm in astronomy. AMPEL was developed during the ZTF survey and has been a critical component in the multi-messenger programs, including in the discovery of Tidal Disruption Events associated with extragalactic neutrinos.
AMPEL will be one of the brokers for the LSST real-time alert stream, and results from the ELAsTiCC simulations show that the technology and photometric classification methods are now mature for these data rates. My final question will instead be whether "we" are ready - the largest challenge might be in how to combine individual scientific creativity with computational requirements.
