2D particle movement system on an asymmetric potential energy surface

该数据集包含了10条轨迹，每条轨迹具有10万时间步，用于评估PESLA在能量估算和演化预测方面的准确性。数据集涉及在能量驱动漂移和噪声引起的扩散下，粒子在景观上的移动情况，旨在不依赖真实能量值的情况下推断能量景观。规模上，每条轨迹包含10万时间步，任务聚焦于能量估算和演化预测。

This dataset contains 10 trajectories, each with 100,000 time steps, to evaluate the accuracy of PESLA in energy estimation and evolutionary prediction. The dataset captures the motion of particles on an energy landscape under energy-driven drift and noise-induced diffusion, with the goal of inferring the energy landscape without relying on ground-truth energy values. In terms of scale, each trajectory includes 100,000 time steps, and the core tasks focus on energy estimation and evolutionary prediction.