The aim of this tutorial is to train users to perform metadynamics simulations with PLUMED.
The aim of this tutorial is to train users to perform and analyze metadynamics simulations with PLUMED.
This tutorial has been prepared by Max Bonomi (adapting a lot of material from other tutorials) for
the <a href="http://isddteach.sdv.univ-paris-diderot.fr/fr/accueil.html">Master In Silico Drug Design</a>, held
at Universite' de Paris on November 25th, 2020.
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@@ -275,12 +275,12 @@ The resulting plot should look like the following:
\image html munster-metad-phifest.png "Estimates of the free energy as a function of the dihedral phi calculated every 100 Gaussian kernels deposited."
These two qualitative observations:
- the system is diffusing efficiently in the collective variable space (Figure \ref master-ISDD-2-phi-fig)
- the system is diffusing rapidly in the collective variable space (Figure \ref master-ISDD-2-phi-fig)
- the estimated free energy does not change significantly as a function of time (Figure \ref master-ISDD-2-metad-phifest-fig)
suggest that the simulation might be converged.
suggest that the simulation _might_ be converged.
\warning The two conditions listed above are necessary, but only qualitative, not sufficient for convergence.
\warning The two conditions listed above are necessary, but only not sufficient to declare convergence.
For a quantitative analysis of the convergence of metadynamics simulations, please have a look below at \ref master-ISDD-2-ex-4.
\subsection master-ISDD-2-ex-3 Exercise 3: Reweighting or how to unbias a metadynamics simulation
