Wang-Landau method: Difference between revisions

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during the simulation in order get a prefixed distribution of energies (usually
during the simulation in order get a prefixed distribution of energies (usually
a uniform distribution); this is done by modifying the values of <math> f(E) </math>
a uniform distribution); this is done by modifying the values of <math> f(E) </math>
to reduce the probability of the energies that have been already ''visited''.
to reduce the probability of the energies that have been already ''visited'', i.e.
Such a simple scheme is continued until the shape of the energy distribution
If the current configuration has energy <math> E_i </math>, <math> f(E_i) </math>
approaches the prefixed one.
is uptdated as:
 
<math> f^{new}(E_i) = f(E_i) - \Delta f </math> ;


where it has been considered that the system has discrete values of the energy (as it
happens in [[Potts model|Potts Models]]), and <math> \Delta f > 0  </math>




Such a simple scheme is continued until the shape of the energy distribution
approaches the prefixed one. Notice that this simulation scheme does not produces
an
equilibrium procedure, since it does not fulfills detailed balance. To overcome
this problem the Wang-Landau procedure consists in the repetition of the scheme
sketched above along several stages. In each subsequent stage the '''perturbation'''
parameter <math> \Delta f </math> is reduced. So, at the last stages the function <math> f(E) </math> hardly changes and the simulation results of these last stages
can be considered as a good description of the actual equilibrium system.


==References==
==References==

Revision as of 12:32, 8 July 2008

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The Wang-Landau method was proposed by F. Wang and D. P. Landau (Ref. 1) to compute the density of states, , of Potts models; where is the number of microstates of the system having energy .

The Wang-Landau method in its original version is a simulation technique designed to reach an uniform sampling of the energies of the system in a given range. In a standard Metropolis Monte Carlo in the canonical ensemble the probability of a given microstate, is given by:

;

whereas for the Wang-Landau procedure we can write:

 ;

where is a function of the energy. changes during the simulation in order get a prefixed distribution of energies (usually a uniform distribution); this is done by modifying the values of to reduce the probability of the energies that have been already visited, i.e. If the current configuration has energy , is uptdated as:

 ;

where it has been considered that the system has discrete values of the energy (as it happens in Potts Models), and


Such a simple scheme is continued until the shape of the energy distribution approaches the prefixed one. Notice that this simulation scheme does not produces an equilibrium procedure, since it does not fulfills detailed balance. To overcome this problem the Wang-Landau procedure consists in the repetition of the scheme sketched above along several stages. In each subsequent stage the perturbation parameter is reduced. So, at the last stages the function hardly changes and the simulation results of these last stages can be considered as a good description of the actual equilibrium system.

References

  1. Fugao Wang and D. P. Landau "Determining the density of states for classical statistical models: A random walk algorithm to produce a flat histogram", Physical Review E 64 056101 (2001)
  2. D. P. Landau, Shan-Ho Tsai, and M. Exler "A new approach to Monte Carlo simulations in statistical physics: Wang-Landau sampling", American Journal of Physics 72 pp. 1294-1302 (2004)
  3. Georg Ganzenmüller and Philip J. Camp "Applications of Wang-Landau sampling to determine phase equilibria in complex fluids", Journal of Chemical Physics 127 154504 (2007)
  4. R. E. Belardinelli and V. D. Pereyra "Wang-Landau algorithm: A theoretical analysis of the saturation of the error", Journal of Chemical Physics 127 184105 (2007)
  5. R. E. Belardinelli and V. D. Pereyra "Fast algorithm to calculate density of states", Physical Review E 75 046701 (2007)