 |  |  |
 | Command |  | Argument |  | Datatype |  | Default |
 | Min |
 | Max |  |  |
 | Format: |
 | MinStep |
| Size = Maximum stepsize during steepest descent minimization in
Å |  | FLOAT |
 | - |
 | - |  | - |  |
 |  | Python: |  | MinStep(size) |  |  |  | Menu: |
 | Simulation
> Temperature control > Parameters |  |  |
 | Related: |
 | Temp
, TempCtrl, AnnealSteps
|  |  |
 | Required: |  |  |  |
 |
If the simulation cell contains a lot of potential energy (e.g. huge atom overlaps),
the standard time step is usually too large to simulate the system reliably, the numerical error accumulates,
the simulation cell overheats and 'explodes'. A steepest descent minimization avoids this problem by automatically choosing very small time steps and keeping the temperature at
0K. It is more secure but much slower than a simulated annealing minimization and should be used for a few hundred steps to remove bumps when importing a new protein structure.
Example:
MinStep 0.05
Automatically choose the time step for each simulation substep so that the fastest atom moves
0.05 Angstroms in every substep.
|