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tgEDMD: Approximation of the Kolmogorov Operator in Tensor Train Format

<p>Data sets required to re-produce numerical examples in</p> <p>L&uuml;cke, M.&nbsp;and N&uuml;ske, F.&nbsp;<em>tgEDMD: Approximation of the Kolmogorov Operator in Tensor Train Format</em>, arxiv&nbsp;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>-&nbsp;Simulation_LS_delta_100.npy: Downsampled set of ten independent simulations, at time spacing 10^{-1}, each comprising 3,000&nbsp;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:&nbsp;Trajectories of Jacobian matrices&nbsp;for sixteen backbone dihedral angles. Derivatives are taken&nbsp;with respect to the Euclidean coordinates of 26 atoms required for the computation of the dihedrals, and evaluated for&nbsp;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