Laser Pulse

Laser pulse research focuses on optimizing pulse characteristics—including temporal shape, intensity, and wavelength—to enhance various applications. Current efforts utilize machine learning, particularly deep reinforcement learning and multi-fidelity ensemble models, to efficiently explore the complex parameter space and optimize laser performance for tasks like material processing (e.g., 3D printing, micromachining) and particle acceleration. These advancements improve precision, efficiency, and control in diverse fields, ranging from manufacturing and energy harvesting to fundamental physics research. The development of robust predictive models, often leveraging large datasets and federated learning, further contributes to improved process control and lifetime prediction of laser systems.