Neural-Parareal dataset JOREK blob runs with RMHD model

Please refer to journal paper from S.J.P.Pamela, titled "Neural-Parareal: Self-improving acceleration of fusion MHD simulations using time-parallelisation and neural operators" Available on ArXiV and on Comp.Phys.Comm.: https://doi.org/10.1016/j.cpc.2024.109391 Data produced by the JOREK code, https://jorek.eu All runs created using the RMHD model, model-ID "model600", with option with_vpar = .false. Data downsampled by saving every 10th timestep, on a regular 2D grid of 100x100. To reproduce full runs, use corresponding input files. Note: variables names are the same as in the JOREK code: u = electric potential omega = toroidal vorticity rho = density T = temperature psi = poloidal magnetic flux zj = toroidal current The create_gif.py can be used to convert data into movies.请参阅S.J.P.Pamela发表的期刊论文，标题为《Neural-Parareal：利用时间并行化（time-parallelisation）与神经算子（neural operators）实现聚变磁流体动力学（Magnetohydrodynamics, MHD）模拟的自改进加速》。该论文可在ArXiv及Comp.Phys.Comm.获取，链接为：https://doi.org/10.1016/j.cpc.2024.109391。 本数据集由JOREK代码生成，其官方网址为https://jorek.eu。所有模拟运行均采用相对论磁流体动力学（RMHD）模型，模型标识符为"model600"，且设置with_vpar参数为逻辑假值。 数据已进行下采样处理：每10个时间步保存一次数据，最终得到的数据集为100×100的规则二维网格。如需复现完整的原始模拟运行，请使用对应的输入文件。 注：变量名称与JOREK代码中的定义完全一致： u = 电势 omega = 环向涡量 rho = 密度 T = 温度 psi = 极向磁通量 zj = 环向电流 可使用create_gif.py脚本将数据集转换为视频文件。