Flavour-tagging is a critical component of the ATLAS experiment physics programme. Existing flavour tagging algorithms rely on several low-level taggers, which are a combination of physically informed algorithms and machine learning models. A novel approach presented here instead uses a single machine learning model based on reconstructed tracks, avoiding the need for low-level taggers based...
This contribution presents the final iteration of the CaloClouds series. Simulation of photon showers in the granularities expected in a future Higgs factory is computationally challenging. A viable simulation must capture the find details exposed by such a detector, while also being fast enough to keep pace with the expected rate of observations. The Caloclouds model utilises point cloud...
The Helmholtz Model Zoo (HMZ) is a cloud-based platform that gives Helmholtz researchers seamless access to deep learning models via a web interface and REST API. It enables easy integration of AI into scientific workflows without moving data outside the Helmholtz Association.
Scientists across all 18 Helmholtz centers can contribute models through a streamlined GitLab submission process....
