25th IEEE Real Time Conference - La Biodola, Elba, Italy

Commissioning and Low Latency Operation of the Graph Neural Network Electromagnetic Calorimeter Trigger at the Belle II Experiment

28 May 2026, 09:50

20m

Maria Luisa Room (Hotel Hermitage)

Oral presentation Data Acquisition and Trigger Architectures Data Acquisition and Trigger Architectures

Speaker

Marc Neu

Description

We present the commissioning and operation of the Graph Neural Network Electromagnetic Calorimeter Trigger Module (GNN-ETM) of the Belle II experiment at the SuperKEKB collider. The GNN-ETM processes calorimeter trigger cells as graph nodes to perform clustering and feature extraction. We fully integrate the system with the successive stages of the first-level trigger, develop slow-control drivers, and add online monitoring capabilities. We optimize the existing FPGA-based architecture through hardware–algorithm co-design to reduce the overall system latency from 3.141 us to 1.050 us. Our hardware implementation is validated through register-transfer-level simulations, achieving bit-accurate agreement with the offline reference model. Online monitoring enables the measurement of instantaneous trigger rates, providing a quantitative basis for trigger-level performance studies. In summary, we report on the GNN-ETM as a fully operational, low-latency trigger module with online control and monitoring capabilities.