TM4FF: Physics-Constrained Transformer-Mamba Framework for Flow Field PredictionNew

This paper presents TM4FF (Transformer-Mamba for Flow Field), a physics-constrained operator learning framework for computational fluid dynamics. The framework introduces three key innovations: a Residual Wavelet Mamba (RWM) layer for feature denoising, a Transformer-based attention mechanism for enhanced feature extraction, and physics constraints to ensure consistency with governing equations. The approach addresses limitations of existing methods like PINNs and Fourier Neural Operators in terms of generalization, noise robustness, and physical consistency.