The field of numerical methods for hyperbolic PDEs and electromagnetic analysis is experiencing significant developments, with a focus on improving the accuracy and efficiency of simulations. Researchers are exploring new approaches to preserve stationarity and divergence in multi-dimensional problems, such as the use of global flux formulations and weighted essentially non-oscillatory (WENO) schemes. Additionally, there is a growing interest in applying machine learning techniques, like Reservoir Computing, to predict complex dynamics and improve long-term forecasting abilities. The development of hybrid methods, combining different numerical techniques, is also gaining traction, enabling the analysis of complex, multi-material environments and heterogeneous media. Noteworthy papers include:
- A paper on a genuinely multi-dimensional stationarity preserving global flux Finite Volume formulation, which significantly outperforms existing methods.
- A study on model-free forecasting of rogue waves using Reservoir Computing, demonstrating remarkable agreement between predicted and actual dynamics.
- A work on a hybrid DEC-SIE framework for potential-based electromagnetic analysis, offering a unified and efficient approach for solving electromagnetic scattering and radiation problems.