当前位置: X-MOL 学术J. Mol. Graph. Model. › 论文详情
Our official English website, www.x-mol.net, welcomes your feedback! (Note: you will need to create a separate account there.)
Predictive compression of molecular dynamics trajectories.
Journal of Molecular Graphics and Modelling ( IF 2.7 ) Pub Date : 2020-01-13 , DOI: 10.1016/j.jmgm.2020.107531
Jan Dvořák 1 , Martin Maňák 2 , Libor Váša 1
Affiliation  

Molecular dynamics simulations help to understand the complex behavior of molecules. The output of such a simulation describes the trajectories of individual atoms as snapshots of atom positions in time. Many compression schemes were developed to reduce the amount of data needed for storing long trajectories. This is achieved by limiting the precision of coordinates, encoding differences instead of absolute values, dimensionality reduction by principal component analysis, or by using polynomials approximating vertex trajectories. However, compression schemes using actual bonds between atoms have not been utilized to their full potential. Therefore, we developed a lossy compression method that captures the local, mostly rotational movement of atoms with respect to their bonded neighbors and predicts their positions in each frame. This allows full control over the data distortion. In our experiments, the method achieves data rates which are substantially better than the rates achieved by competing methods at the same error level.



中文翻译:

分子动力学轨迹的预测压缩。

分子动力学模拟有助于理解分子的复杂行为。这种模拟的输出将单个原子的轨迹描述为时间上原子位置的快照。开发了许多压缩方案来减少存储长轨迹所需的数据量。这是通过限制坐标的精度,编码差异而不是绝对值,通过主成分分析或通过使用近似顶点轨迹的多项式来减少维数来实现的。但是,利用原子间实际键的压缩方案尚未充分发挥其潜力。因此,我们开发了一种有损压缩方法,该方法可以捕获原子相对于其键合邻居的局部(主要是旋转)运动,并预测它们在每帧中的位置。这样可以完全控制数据失真。在我们的实验中,该方法获得的数据速率大大优于在相同误差水平下通过竞争方法获得的数据速率。

更新日期:2020-01-13
down
wechat
bug