Wavefield Solution

Wavefield solution research focuses on accurately and efficiently modeling the propagation of waves through various media, primarily addressing challenges in speed, accuracy, and generalization across diverse scenarios. Current efforts leverage advanced machine learning techniques, such as physics-informed neural networks (PINNs) with specialized architectures like Gabor networks and convolutional long short-term memory (ConvLEM) models, to improve wavefield prediction and interpolation from often sparse or noisy data. These advancements have significant implications for diverse fields, including earthquake early warning, seismic imaging, and acoustic communication, by enabling faster and more accurate simulations and data analysis than traditional numerical methods.