Biased molecular dynamics: Difference between revisions

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*Fermi function (see curve (b) on the plot above)
*Fermi function (see curve (b) on the plot above)
:<math>
:<math>
\tilde{V}(\xi_1,\dots,\xi_{M}) = \sum_{\mu=1}^{M}\frac{A}{1+\text{exp}\left [-D\frac{\xi(q)}{\xi_0} -1 \right ]} \;
\tilde{V}(\xi_1,\dots,\xi_{M}) = \sum_{\mu=1}^{M}\frac{A_{\mu}}{1+\text{exp}\left [-D_{\mu}\frac{\xi(q)}{\xi_{0,\mu}} -1 \right ]} \;
</math>
</math>
where the sum runs all (<math>M</math>) coordinates the potential acts upon, which are defined in the {{FILE|ICONST}}-file by setting the status to 4.
{{TAG|FBIAS_A}} {{TAG|FBIAS_D}} {{TAG|FBIAS_R0}} 


*Gauss function (see curve (b) on the plot above)
*Gauss function (see curve (b) on the plot above)

Revision as of 11:57, 6 April 2023

The probability density for a geometric parameter ξ of the system driven by a Hamiltonian:

with T(p), and V(q) being kinetic, and potential energies, respectively, can be written as:

The term stands for a thermal average of quantity X evaluated for the system driven by the Hamiltonian H.

If the system is modified by adding a bias potential acting on one or multiple selected internal coordinates of the system ξ=ξ(q), the Hamiltonian takes a form:

and the probability density of ξ in the biased ensemble is:

It can be shown that the biased and unbiased averages are related via a simple formula:

More generally, an observable :

can be expressed in terms of thermal averages within the biased ensemble:

Simulation methods such as umbrella sampling[1] use a bias potential to enhance sampling of ξ in regions with low Pi) such as transition regions of chemical reactions. The correct distributions are recovered afterwards using the equation for above.

A more detailed description of the method can be found in Ref.[2]. Biased molecular dynamics can be used also to introduce soft geometric constraints in which the controlled geometric parameter is not strictly constant, instead it oscillates in a narrow interval of values. The bias potentials are supported both the NVT and NpT MD simulations regardless of the particular thermostat and/or barostat setting. Different types of potentials can be freely combined.

Graphical representation of (a) harmonic, (b) Fermi function-shaped, and (c) and Gauss function-shaped bias potentials.

Supported types of bias potentials

Presently, the following types of bias potential are supported:


  • Harmonic potential (see curve (a) on the plot above)

where the sum runs all () coordinates the potential acts upon, which are defined in the ICONST-file by setting the status to 8. The parameters of the potential, (force constant) and (minimum of potential), are defined, respectively, via the keywords SPRING_K and SPRING_R0 in INCAR. Optionally, it is also possible to change the value of every MD step at a constant rate defined via parameter SPRING_V. Note that the number of items defined via SPRING_K, SPRING_R0, and SPRING_V must be equal to , otherwise the calculation terminates with an error message. This form of bias potential is employed in several simulation protocols, such as the umbrella sampling[1], umbrella integration, or steered MD, and is useful also in cases where the values need restrained.

  • Fermi function (see curve (b) on the plot above)

where the sum runs all () coordinates the potential acts upon, which are defined in the ICONST-file by setting the status to 4.

FBIAS_A FBIAS_D FBIAS_R0  


  • Gauss function (see curve (b) on the plot above)



Andersen thermostat

  • For a biased molecular dynamics run with Andersen thermostat, one has to:
  1. Set the standard MD-related tags: IBRION=0, TEBEG, POTIM, and NSW
  2. Set MDALGO=1 (MDALGO=11 in VASP 5.x), and choose an appropriate setting for ANDERSEN_PROB
  3. In order to avoid updating of the bias potential, set HILLS_BIN=NSW
  4. Define collective variables in the ICONST-file, and set the STATUS parameter for the collective variables to 5
  5. Define the bias potential in the PENALTYPOT-file

Nose-Hoover thermostat

  • For a biased molecular dynamics run with Nose-Hoover thermostat, one has to:
  1. Set the standard MD-related tags: IBRION=0, TEBEG, POTIM, and NSW
  2. Set MDALGO=2 (MDALGO=21 in VASP 5.x), and choose an appropriate setting for SMASS
  3. In order to avoid updating of the bias potential, set HILLS_BIN=NSW
  4. Define collective variables in the ICONST-file, and set the STATUS parameter for the collective variables to 5
  5. Define the bias potential in the PENALTYPOT-file

The values of all collective variables for each MD step are listed in the REPORT-file, check the lines after the string Metadynamics.

References

  1. a b G. M. Torrie and J. P. Valleau, J. Comp. Phys. 23, 187 (1977).
  2. D. Frenkel and B. Smit, Understanding molecular simulations: from algorithms to applications, Academic Press: San Diego, 2002.