Free Electron Laser

Free-electron lasers (FELs) generate intense, ultrafast pulses of X-rays, enabling unprecedented studies of matter at the atomic level. Current research heavily emphasizes improving data analysis using machine learning, particularly deep learning architectures like convolutional neural networks and normalizing flows, to address challenges like phase retrieval from diffraction patterns and real-time data processing for high-repetition-rate experiments. These advancements are crucial for enhancing the efficiency and accuracy of FEL-based experiments across diverse fields, including structural biology and materials science, by automating data analysis and improving the quality of reconstructed images.