Pretrained Event Classification Model for High Energy Physics Analysis

Researchers have developed a foundation model based on Graph Neural Network architecture to classify events in high-energy physics. Trained on 120 million simulated proton-proton collision events, the model provides a new tool for identifying distinct physical processes within complex particle data.