News on ILC/Higgs factories (if any)

AI-based event reconstruction and detector design for Higgs factories

• Taikan Suehara (ICEPP, The University of Tokyo)

Detector designs for Higgs factories are highly optimized to maximize performance of multi-particle final states, especially including multiple hadron jets. This requires highly-granular detector elements, especially in calorimeters to separate particles. Event reconstruction with such detectors is highly non-trivial, requiring intelligent pattern recognition, thus suitable to use modern machine-learning techniques. In this talk I will introduce several state-of-the-art technologies such as transformer-based flavor tagging, GNN (graph neural network) based particle flow and so on. These algorithms are also crucial for detector design, since performance of the detectors is highly correlated to the reconstruction algorithms and ML-based algorithm has advantages on utilizing additional or improved information of improved detector designs seemlessly to compare with existing designs. Discussions on such direction will also be presented.