Yifu An | Searcharxiv

arXiv2026

Sun-to-Earth Coronal Mass Ejection Simulations From a Vector Magnetogram

We implement a novel approach to performing Sun-to-Earth coronal mass ejection (CME) simulations and test it on three geo-effective space weather events. Using a vector magnetogram observed prior to the CME as the boundary condition, we reconstruct non-linear force free field (NLFFF) solutions in solar active regions with an established magneto-frictional method. We find a pre-eruption solar corona containing the NLFFF in the AWSoM model, which then spontaneously erupts. We apply STITCH, a photospheric driving method, when needed, to increase the strength of the CME shock. The eruptions successfully produce magnetic flux ropes (MFRs) that propagate to 1 au in the full MHD simulation. The synthetic white light images of the simulated CMEs share a striking resemblance in shape to observations. The interplanetary MFRs (IMFRs) arrive at 1 au with a 1.5- to 9-hour error. A comparison of simulated solar wind plasma with in-situ measurements shows that IMFR crossing can reproduce a southward $B_z$ and often its magnitudes, which determine the geo-effectiveness of the event.

astro-ph.SR↗

arXiv2025

BATSRUS GPU: Faster-than-Real-Time Magnetospheric Simulations with a Block-Adaptive Grid Code

BATSRUS, our state-of-the-art extended magnetohydrodynamic code, is the most used and one of the most resource-consuming models in the Space Weather Modeling Framework. It has always been our objective to improve its efficiency and speed with emerging techniques, such as GPU acceleration. To utilize the GPU nodes on modern supercomputers, we port BATSRUS to GPUs with the OpenACC API. Porting the code to a single GPU requires rewriting and optimizing the most used functionalities of the original code into a new solver, which accounts for around 1% of the entire program in length. To port it to multiple GPUs, we implement a new message passing algorithm to support its unique block-adaptive grid feature. We conduct weak scaling tests on as many as 256 GPUs and find good performance. The program has 50-60% parallel efficiency on up to 256 GPUs, and up to 95% efficiency within a single node (4 GPUs). Running large problems on more than one node has reduced efficiency due to hardware bottlenecks. We also demonstrate our ability to run representative magnetospheric simulations on GPUs. The performance for a single A100 GPU is about the same as 270 AMD "Rome" CPU cores, and it runs 3.6 times faster than real time. The simulation can run 6.9 times faster than real time on four A100 GPUs.

astro-ph.IM↗