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IOP Joint APP and HEPP Annual Conference 2026

8–10 Apr 2026
John McIntyre Conference Centre
Europe/London timezone

Session

Parallel - machine learning/reconstruction

10 Apr 2026, 11:00
John McIntyre Conference Centre

John McIntyre Conference Centre

Pollock Halls, 18 Holyrood Park Rd, Edinburgh EH16 5AY

Conveners

Parallel - machine learning/reconstruction: Friday Salisbury

  • Lucien Heurtier (King's College London)

Presentation materials

There are no materials yet.

  1. 7. Particle-Based Representation Learning for Anomaly Detection in the CMS High-Level Trigger
    Mehrnoosh Moallemi (Science and Technology Facilities Council STFC (GB))
    10/04/2026, 11:00
    Collider physics
    Parallel talk

    Anomaly detection at the LHC aims to identify events that deviate from dominant Standard Model (SM) processes while minimizing assumptions inherent to predefined trigger selections, enabling model-agnostic searches for new physics. The CMS experiment employs a two-stage trigger system that reduces the LHC bunch-crossing rate of up to 40 MHz to an output rate of approximately 9 kHz for offline...

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  2. 91. Boosted Top Jet Tagging Based on LundNet
    Yuanda Zhu (UCL)
    10/04/2026, 11:15
    Machine learning and reconstruction
    Parallel talk

    This study investigates the enhancement of boosted top quark tagging at the ATLAS detector by integrating jet substructure features, captured through the Lund Jet Plane (LJP) and the LundNet Graph Neural Network, with b-tagging information from the GN3X transformer model. The study demonstrates that combining these orthogonal data sources improves background rejection compared to using...

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  3. 25. Quantum Computing for Particle Physics: Simulation and Machine Learning
    Callum Duffy (University College London)
    10/04/2026, 11:30
    Machine learning and reconstruction
    Parallel talk

    Quantum computing is a rapidly emerging technology with potential applications in particle physics. From the direct simulation of quantum field theories on quantum hardware to the acceleration of computationally demanding components of data analysis, the interface between quantum information science and high-energy physics has become an active and expanding area of research. Potential...

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  4. 74. A Hadronic Tau Preselection in the ATLAS detectors High Level Trigger
    Joel Davidson (University of Warwick (GB))
    10/04/2026, 11:45
    Machine learning and reconstruction
    Parallel talk

    At the Large Hadron Collider, the ATLAS detector experiences a collision rate of about 1 billion proton-proton collisions per second. This rate of collisions is far too large for us to store all observed events, so only interesting events are stored. The ATLAS trigger system reduces this input rate to a manageable 3 kHz via the use of the hardware-based Level 1 trigger and the software-based...

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