Flat histogram¶
Flat histogram Monte Carlo methods bias the system along a macrostate, or order parameter, to observe uniform sampling and recover the free energy as a function of this order parameter.
FlatHistogram contains a Macrostate and a Bias.
The Macrostate could be the number of particles or some other quantity such as the energy or a parameter of a model.
The method of Bias includes Wang-Landau and Transition-Matrix.
Importantly, the Bias computes the probability distribution of the macrostate on the fly, which is related to the free energy.
Tutorial¶
- Ideal gas equation of state using grand canonical ensemble transition-matrix Monte Carlo
- Grand canonical ensemble transition-matrix Monte Carlo
- Analysis of a one-phase (supercritical) simulation
- Analysis of a two-phase (phase separated) simulation
- Grand Canonical Flat Histogram Simulation of Lennard-Jones
- Grand Canonical Flat Histogram Simulation of SPC/E
- Grand Canonical Flat Histogram Simulation of RPM
- Grand Canonical Flat Histogram Simulation of Hard Spheres.
- Grand Canonical Flat Histogram Simulation of Patchy Trimers
- Grand Canonical Flat Histogram Simulation of Kern-Frenkel Patches
- Grand Canonical Flat Histogram Simulation at low temperature
Tools¶
For restarting multicore simulations, see /path/to/feasst/plugin/flat_histogram/tools/restart.cpp