[gmx-users] 1. Re: g_msd (Gaurav Goel)

Ricardo Cuya Guizado rcuyag at hotmail.com
Tue Jul 13 15:32:26 CEST 2010

Thanks so much Gaurav

Your explication was so clear, and answer all my questions.

Ricardo Cuya

> Message: 1
> Date: Mon, 12 Jul 2010 18:56:02 -0400
> From: Gaurav Goel <gauravgoeluta at gmail.com>
> Subject: Re: [gmx-users] g_msd
> To: Discussion list for GROMACS users <gmx-users at gromacs.org>
> Message-ID:
> 	<AANLkTin8BKOORXkdylk1iwlvnnGq0VK8-LXsx_81Wsb2 at mail.gmail.com>
> Content-Type: text/plain; charset=ISO-8859-1
> On Mon, Jul 12, 2010 at 5:22 PM, Ricardo Cuya Guizado
> <rcuyag at hotmail.com> wrote:
> > Dear gromacs users
> > I make a MD of 20 ns of a solute in water
> > With the g_msd program the msd vs the time was obtained
> > In the plot, I observed a linear behaviour of the MSD from 0 to 15 ns and a
> > plateau with no linear tendence at the last 5 ns arpoximately.
> > In order to know if the observed plateau was due to the data or is due to
> > the way as the algorithm process the data, I divided the MD in two
> > trajectories and obtained the msd for each one.
> > From 0-10ns, the plot observed shows a linear tendence en the begining and a
> > plateau with no linear tendence from 9 to 10 ns.
> > From 10-20 ns the plot observed was linear from 10 to 18 ns and not linear
> > at the last, the same plateau was observed.
> > Comparing the plots there are not equivalent,.
> > Why g_msd produces a non linear plot at the last of the calculation and the
> > plateau is ever produces.
> > Somebody will explain the way as the g_msd algorithm work? and why the plot
> > are no equivalent or why there must be equivalent?
> I will explain how the g_msd algorithm works and hopefully that will
> answer all your questions above. What you see in the output file is
> average-MSD versus time. This average is done over all the particles
> in the group you selected and over multiple time origins (this last
> option can be selected with the -trestart parameter). Also, time in
> column 1 is time difference from the start of your trajectory to
> current time.
> E.g., let's say you collected a trajectory over 5 time units and
> choose -trestart=1 time unit and -dt=1 time unit.
> dt=1 means you'll have 6 configurations for your analysis (including
> the configuration at t=0).
> trestart=1 means you'll have 5 distinct trajectories for your analysis:
> Trajectory 1: 0-5
> T2: 1-5
> T3: 2-5
> T4: 3-5
> T5: 4-5
> Now you can notice that all 5 trajectories contribute to the average
> MSD after 1 time unit (T1-T5), 4 trajectories contribute to the
> average MSD after 2 time units (T1-T4),  3 trajectories to the average
> MSD after 3 time units (T1-T3), ...., and only one trajectory to the
> MSD after 5 time units (T1). Of course, this assumes that trestart is
> large enough that all all these trajectories are uncorrelated.
> So, it's clear that longer the time interval at which you want to
> evaluate the MSD lesser the number of trajectories used to evaluate
> it...and hence, higher error in MSD values at longer times. That might
> explain deviation from linear behaviour at long times.
> However, you must be careful in interpreting the MSD data and I
> recommend reading some literature on the subject. A plateau in MSD
> versus time data might also signify what is called cage motion, in
> which a particle or atom is trapped by the surrounding particles and
> is not able to move out of that hole on the simulation time scale. If
> you want you can send me your MSD versus time data along with some
> information on your system (such as potentials, density, temperature
> etc.) and I can let you know my comments.
> Few words of caution:
> Make sure that the center of mass of your particle (or atom or
> molecule) is diffusing several particle diameters. Also, make sure
> that you're calculating the self-diffusion coefficient  by fitting a
> straight line to the linear region of MSD versus time data. You can
> either modify the -beginfit and -endfit options... or calculate the
> slope of the MSD versus time data using some other software (e.g.,
> gnuplot, excel, etc.). If you're doing the latter you'll need to take
> a look at the code in gmx_msd.c to know how the diffusion coefficent
> is calculated from the slope of MSD versus time data (tog et correct
> units, use proper scaling factors, etc.).
> I hope that helped.
> -Gaurav
> >
> >
> >
> >
> > Regards
> > Ricardo Cuya
> >

Regardez-moi dans les yeux : vidéobavardage GRATUIT
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