Simulating the complex behavior of light inside powerful laser systems requires enormous computing resources, making it difficult for researchers to predict and adjust laser performance quickly. Now, scientists at Stanford University, the University of California, Los Angeles (UCLA), and SLAC National Accelerator Laboratory have developed an artificial intelligence model that dramatically accelerates these calculations. Using deep learning, the new approach reproduces the results of conventional simulations in a fraction of the time while maintaining high accuracy across a wide variety of laser pulse shapes.
The advance focuses on a branch of physics called second-order nonlinear optics, also known as χ2 processes. These interactions occur when light waves exchange energy while traveling through specially designed crystals, allowing scientists to change the frequency of light and precisely control the shape of laser pulses. Such capabilities are particularly important at large scientific facilities that use lasers to generate intense X-rays.
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