I'm kind of the person who introduced the MC barostat into Amber, via the
mdgx code. Jason Swails and Scott Legrand ported it into pmemd. The
reference is a good one; there are also discussions about it in
Computational Simulation of Liquids by Allen and Tildesley if I recall
correctly.
In order to better understand the MC barostat, it's useful to consider the
case of an ideal gas, and how the barostat does indeed correctly reproduce
the intended pressure / volume relationship despite the naïve perception
that a volume move on an ideal gas would not produce a change in the
potential energy of the particles (which is purely kinetic). It's all
about the effect of the work term PdV and the probability of making the
move (see Barostats.c, line 832), which includes the number of particles N
and the log of the volume change, on the metropolis acceptance criterion.
That's the detailed balance relationship and the means by which PV = ((( N
))) RT.
Dave
On Tue, Nov 14, 2017 at 1:17 PM, Niel Henriksen <shireham.gmail.com> wrote:
> Hi Filip,
>
> I did not implement the MC barostat in AMBER, but this paper should provide
> useful background:
> https://doi.org/10.1016/j.cplett.2003.12.039
>
> The relevant AMBER code is
> here: $AMBERHOME/AmberTools/src/sander/barostats.F90
>
> --Niel
>
> On Tue, Nov 14, 2017 at 3:09 AM, filip <filip.persson.bpc.lu.se> wrote:
>
> > Dear AMBER developers,
> >
> > I would like to see a reference for the Monte Carlo barostat implemented
> > in AMBER 16 in order to understand exactly how it works. The manual is
> > lacking in detail here and is not of very much help unfortunately.
> >
> > Best regards,
> > Filip Persson
> >
> > PhD student
> > Department of Biophysical Chemistry
> > Lund University
> > Sweden
> >
> >
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> > AMBER.ambermd.org
> > http://lists.ambermd.org/mailman/listinfo/amber
> >
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Received on Tue Nov 14 2017 - 11:30:02 PST
