Wave Simulator

Wave simulators are computational tools used to model wave propagation across diverse fields, from oceanography and seismology to acoustics and electromagnetics. Current research emphasizes improving simulation speed and accuracy, particularly through the integration of machine learning techniques like deep neural networks (including U-Net and Fourier Neural Operators) and physics-informed neural networks (PINNs), often employing compressed convolutional architectures to enhance efficiency. These advancements enable higher-resolution simulations, improved predictions (e.g., of tsunami flooding or wave-induced sound), and faster processing of large datasets, impacting fields requiring real-time analysis and precise predictions.