PBMETAD
This is part of the bias module

Used to performed Parallel Bias MetaDynamics.

This action activate Parallel Bias MetaDynamics (PBMetaD) [36], a version of MetaDynamics [31] in which multiple low-dimensional bias potentials are applied in parallel. In the current implementation, these have the form of mono-dimensional MetaDynamics bias potentials:

\[ {V(s_1,t), ..., V(s_N,t)} \]

where:

\[ V(s_i,t) = \sum_{ k \tau < t} W_i(k \tau) \exp\left( - \frac{(s_i-s_i^{(0)}(k \tau))^2}{2\sigma_i^2} \right). \]

To ensure the convergence of each mono-dimensional bias potential to the corresponding free energy, at each deposition step the Gaussian heights are multiplied by the so-called conditional term:

\[ W_i(k \tau)=W_0 \frac{\exp\left( - \frac{V(s_i,k \tau)}{k_B T} \right)}{\sum_{i=1}^N \exp\left( - \frac{V(s_i,k \tau)}{k_B T} \right)} \]

where \(W_0\) is the initial Gaussian height.

The PBMetaD bias potential is defined by:

\[ V_{PB}(\vec{s},t) = -k_B T \log{\sum_{i=1}^N \exp\left( - \frac{V(s_i,t)}{k_B T} \right)}. \]

Information on the Gaussian functions that build each bias potential are printed to multiple HILLS files, which are used both to restart the calculation and to reconstruct the mono-dimensional free energies as a function of the corresponding CVs. These can be reconstructed using the sum_hills utility because the final bias is given by:

\[ V(s_i) = -F(s_i) \]

Currently, only a subset of the METAD options are available in PBMetaD.

The bias potentials can be stored on a grid to increase performances of long PBMetaD simulations. You should provide either the number of bins for every collective variable (GRID_BIN) or the desired grid spacing (GRID_SPACING). In case you provide both PLUMED will use the most conservative choice (highest number of bins) for each dimension. In case you do not provide any information about bin size (neither GRID_BIN nor GRID_SPACING) and if Gaussian width is fixed PLUMED will use 1/5 of the Gaussian width as grid spacing. This default choice should be reasonable for most applications.

Another option that is available is well-tempered metadynamics [4]. In this variant of PBMetaD the heights of the Gaussian hills are rescaled at each step by the additional well-tempered metadynamics term. This ensures that each bias converges more smoothly. It should be noted that, in the case of well-tempered metadynamics, in the output printed the Gaussian height is re-scaled using the bias factor. Also notice that with well-tempered metadynamics the HILLS files do not contain the bias, but the negative of the free-energy estimate. This choice has the advantage that one can restart a simulation using a different value for the \(\Delta T\). The applied bias will be scaled accordingly.

With the keyword INTERVAL one changes the metadynamics algorithm setting the bias force equal to zero outside boundary [3]. If, for example, metadynamics is performed on a CV s and one is interested only to the free energy for s > sw, the history dependent potential is still updated according to the above equations but the metadynamics force is set to zero for s < sw. Notice that Gaussians are added also if s < sw, as the tails of these Gaussians influence VG in the relevant region s > sw. In this way, the force on the system in the region s > sw comes from both metadynamics and the force field, in the region s < sw only from the latter. This approach allows obtaining a history-dependent bias potential VG that fluctuates around a stable estimator, equal to the negative of the free energy far enough from the boundaries. Note that:

  • It works only for one-dimensional biases;
  • It works both with and without GRID;
  • The interval limit sw in a region where the free energy derivative is not large;
  • If in the region outside the limit sw the system has a free energy minimum, the INTERVAL keyword should be used together with a UPPER_WALLS or LOWER_WALLS at sw.

Multiple walkers [40] can also be used, in the MPI implementation only. See below the examples.

Description of components

By default this Action calculates the following quantities. These quanties can be referenced elsewhere in the input by using this Action's label followed by a dot and the name of the quantity required from the list below.

Quantity Description
bias the instantaneous value of the bias potential
Compulsory keywords
ARG the input for this action is the scalar output from one or more other actions. The particular scalars that you will use are referenced using the label of the action. If the label appears on its own then it is assumed that the Action calculates a single scalar value. The value of this scalar is thus used as the input to this new action. If * or *.* appears the scalars calculated by all the proceding actions in the input file are taken. Some actions have multi-component outputs and each component of the output has a specific label. For example a DISTANCE action labelled dist may have three componets x, y and z. To take just the x component you should use dist.x, if you wish to take all three components then use dist.*.More information on the referencing of Actions can be found in the section of the manual on the PLUMED Getting started. Scalar values can also be referenced using POSIX regular expressions as detailed in the section on Regular Expressions. To use this feature you you must compile PLUMED with the appropriate flag.
SIGMA the widths of the Gaussian hills
PACE the frequency for hill addition, one for all biases
FILE files in which the lists of added hills are stored
Options
NUMERICAL_DERIVATIVES ( default=off ) calculate the derivatives for these quantities numerically
GRID_SPARSE ( default=off ) use a sparse grid to store hills
GRID_NOSPLINE ( default=off ) don't use spline interpolation with grids
MULTIPLE_WALKERS

( default=off ) Switch on MPI version of multiple walkers

HEIGHT the height of the Gaussian hills, one for all biases. Compulsory unless TAU, TEMP and BIASFACTOR are given
FMT specify format for HILLS files (useful for decrease the number of digits in regtests)
BIASFACTOR use well tempered metadynamics with this biasfactor, one for all biases. Please note you must also specify temp
TEMP the system temperature - this is only needed if you are doing well-tempered metadynamics
TAU in well tempered metadynamics, sets height to (kb*DeltaT*pace*timestep)/tau
GRID_MIN the lower bounds for the grid
GRID_MAX the upper bounds for the grid
GRID_BIN the number of bins for the grid
GRID_SPACING the approximate grid spacing (to be used as an alternative or together with GRID_BIN)
INTERVAL_MIN monodimensional lower limits, outside the limits the system will not feel the biasing force.
INTERVAL_MAX

monodimensional upper limits, outside the limits the system will not feel the biasing force.

Examples
The following input is for PBMetaD calculation using as collective variables the distance between atoms 3 and 5 and the distance between atoms 2 and 4. The value of the CVs and the PBMetaD bias potential are written to the COLVAR file every 100 steps.
DISTANCE ATOMS=3,5 LABEL=d1
DISTANCE ATOMS=2,4 LABEL=d2
PBMETAD ARG=d1,d2 SIGMA=0.2,0.2 HEIGHT=0.3 PACE=500 LABEL=pb FILE=HILLS_d1,HILLS_d2
PRINT ARG=d1,d2,pb.bias STRIDE=100 FILE=COLVAR
(See also DISTANCE and PRINT).
If you use well-tempered metadynamics, you should specify a single biasfactor and initial Gaussian height.
DISTANCE ATOMS=3,5 LABEL=d1
DISTANCE ATOMS=2,4 LABEL=d2
PBMETAD ...
ARG=d1,d2 SIGMA=0.2,0.2 HEIGHT=0.3 
PACE=500 BIASFACTOR=8 LABEL=pb 
FILE=HILLS_d1,HILLS_d2
... PBMETAD
PRINT ARG=d1,d2,pb.bias STRIDE=100 FILE=COLVAR
Only the MPI version of multiple-walkers is currently implemented.
DISTANCE ATOMS=3,5 LABEL=d1
DISTANCE ATOMS=2,4 LABEL=d2
PBMETAD ...
ARG=d1,d2 SIGMA=0.2,0.2 HEIGHT=0.3 
PACE=500 BIASFACTOR=8 LABEL=pb 
FILE=HILLS_d1,HILLS_d2
MULTIPLE_WALKERS
... PBMETAD
PRINT ARG=d1,d2,pb.bias STRIDE=100 FILE=COLVAR