Heidelberg 2022 – wissenschaftliches Programm
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T: Fachverband Teilchenphysik
T 26: Data Analysis, Information Technology and Artificial Intelligence
T 26.8: Vortrag
Montag, 21. März 2022, 18:00–18:15, T-H39
Studies of machine learning inspired clustering algorithms for jets — Amrita Bhattacherjee1, Debarghya Ghoshdastidar1, •Siddha Hill2, and Stefan Kluth2 — 1TUM Informatik — 2MPI für Physik
We study several machine learning inspired hierarchical clustering algorithms algorithms to cluster the particles of hadronic final states in high energy e+e- collisions into jets. We compare their performance against well known algorithms such as JADE or Durham. Performance indicators are physically motivated such as angular distance or energy difference of matching jets at parton, hadron or detector level. We also study new performance indicators derived from computer science clustering theory.