Detector Design

Detector design is undergoing a transformation driven by the increasing use of artificial intelligence (AI) to optimize complex systems for diverse applications, from particle physics experiments to medical imaging. Current research focuses on employing AI algorithms, including generative adversarial networks (GANs), graph neural networks, and transformer-based architectures like Swin Transformers, to improve detector performance, speed up simulations, and automate design processes. This AI-driven approach promises to significantly enhance the efficiency and capabilities of detectors across various scientific fields, leading to improved data analysis and potentially new discoveries.