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Talk22 min

Investigation of Anomaly Detection algorithms for filtering events with microseconds latency in the ATLAS hardware-level trigger

Tara Tahseen · CERN

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About

This project aims to evaluate the robustness of a candidate data-driven autoencoder-based anomaly detection algorithm for use at the ATLAS hardware trigger, which performs real-time event selection to save only the events deemed most interesting. This work tests the sensitivity of the algorithm across a variety of physics processes and explores new methods for increasing sensitivity to anomalous events occurring at low energy or low multiplicity, which are more easily obscured by background.

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The talk

  1. Investigation of Anomaly Detection algorithms for filtering events with microseconds latency in the ATLAS hardware-level trigger 2026-03-04 · 22 min · CERN's player

Credits and licence

Institution
CERN
Speaker
Tara Tahseen
Year
2026
Language
English
Subjects
Computer science
Source
CERN
Licence
CERN, as CERN states it. CERN's terms
Attribution
© CERN. CERN provides its audiovisual media free of charge for educational and informational use, credited to CERN; this lecture is shown in CERN's own player.
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