tgEDMD: Approximation of the Kolmogorov Operator in Tensor Train Format
<p>Data sets required to re-produce numerical examples in</p> <p>Lücke, M. and Nüske, F. <em>tgEDMD: Approximation of the Kolmogorov Operator in Tensor Train Format</em>, arxiv 2111.09606 (2021)</p> <p><strong>Lemon Slice Example:</strong></p> <p>- Simulation_LS_Full.npy: Complete set of ten independent simulations, at time spacing 10^{-3}, each comprising 300,000 steps.</p> <p>- Simulation_LS_delta_100.npy: Downsampled set of ten independent simulations, at time spacing 10^{-1}, each comprising 3,000 steps.</p> <p><strong>Deca Alanine Example:</strong></p> <p>- Dih_Traj_*.npy: Trajectories of sixteen backbone dihedral angles for 50,000 steps each, at 10ps time spacing.</p> <p>- Dih_Jac_Traj_*.npy: Trajectories of Jacobian matrices for sixteen backbone dihedral angles. Derivatives are taken with respect to the Euclidean coordinates of 26 atoms required for the computation of the dihedrals, and evaluated for 50,000 steps each, at 10ps time spacing.</p> <p>- Timescales_MSM.npy: Implied timescales computed by MSM analysis of the same data set. Contains the first 499 timescales computed using seven different MSM lag times.</p>
ShareScore
36/100
Overall dataset sharing score
Score breakdown
These five areas show where the dataset supports — or may limit — practical reuse.
- Stewardship
- 4
- Harmonization
- 4
- Access
- 20
- Reuse readiness
- 8
- Engagement
- 0