PIK-ICoNe-landscape/Stability_Landscapes

Kuramoto-Stability-Landscape (KSL) 数据集包含使用随机增长算法生成的合成振荡器网络拓扑。这些网络通过应用二阶 Kuramoto 模型进行动态模拟，该模型在分析诸如电力网格和神经元网络等复杂系统的同步动力学方面被广泛认可。数据集包括两个集合，每个集合包含 10,000 个独特的网络拓扑，分别是包含 20 个节点的 dataset20 和包含 100 个节点的 dataset100。每个拓扑都与单个节点稳定性池图（SNBS）相关联，提供每个节点的详细空间稳定性信息。

The Kuramoto-Stability-Landscape (KSL) dataset consists of synthetic oscillator network topologies generated using a random growth algorithm. Dynamical simulations are conducted by applying the second-order Kuramoto model to the nodes, which is widely recognized for its effectiveness in analyzing synchronization dynamics in complex systems such as power grids and neuronal networks. The dataset includes two ensembles, each containing 10,000 unique network topologies: dataset20 with 20 nodes each, and dataset100 with 100 nodes each. Each topology is associated with single-node basin stability (SNBS) heatmaps, providing detailed spatial stability information per node.