Hi Sikandar,

I'm a little confused, I am already telling Gromacs to use *table.xvg by 
setting vdwtype = user and energygrp_table = PEO PEO PBO PBO PEO PBO. I 
thought that this was the tabulated potential of mean force (in the first 
run). Do you mean I should produce my own tables like this: 
http://www.gromacs.org/Documentation/How-tos/Tabulated_Potentials using 
values for sigma and epsilon read from my current explosion inducing PMF 
tables?

I didn't think that the cut-off would cause the system to blow up either, 
the reason why I'm using such a short one is because my RDFs don't quite 
converge to 1 so it seemed like a better idea to try and fit just the first 
peak, at least initially. 

Thanks a lot,

Dan.


On Wednesday, 28 January 2015 21:50:55 UTC, sikandar wrote:
>
> Hi Dan,
>
> As Christoph suggested, the initial guesses from RDF inversion may be an 
> issue, so try using simple LJ potential (the default LJ from table.xvg). 
> Also, I am not sure why are you cutting choosing the cut-off 0.75 nm based 
> on the first minima in the RDF. Can you try using the the same cut-off as 
> for the LJ interaction in your reference AA system? Anyway, I dont think 
> cut-off could be causing the simulation to blow-up, initial potential 
> guesses could be the main cause.
>
> Best,
> Sikandar
>
> On Wed, Jan 28, 2015 at 12:18 PM, Daniel Allen <[email protected] 
> <javascript:>> wrote:
>
>> It is the nb potential which is problematic. This seems so strange, the 
>> functions seem fine and exactly what you would expect from smooth well 
>> sampled RDFs. What is even more puzzling is that the nb energy breaks in 
>> just one time step. I have printed out energy information every timestep:
>>        
>> Step Time Lambda
>> 4 0.00400 0.00000
>>
>> Energies (kJ/mol)
>> Tab. Bonds Tab. Angles Tab. Dih. LJ (SR) Coulomb (SR)
>> 1.20852e+04 3.70247e+04 9.51537e+03 -7.67663e+05 0.00000e+00
>> Potential Kinetic En. Total Energy Temperature Pressure (bar)
>> -7.09038e+05 2.99711e+04 -6.79067e+05 3.16241e+02 -3.31874e+04
>>
>> Step Time Lambda
>> 5 0.00500 0.00000
>>
>> Energies (kJ/mol)
>> Tab. Bonds Tab. Angles Tab. Dih. LJ (SR) Coulomb (SR)
>> 1.20860e+04 3.70238e+04 9.51379e+03 -nan 0.00000e+00
>>
>> So after integration step 4 the LJ energy is -7.67663e+05 but after the 
>> next it is -nan. In past trials with this system today the LJ energy jumps 
>> to ~10^213 in just one step.
>>
>> If the configuration was bad then surely the energy would be very large 
>> (and positive) from the first step?
>>
>> Any ideas what might cause it to jump like this so suddenly? I would 
>> understand if the LJ energy increased monotonically but it seems stable 
>> (admittedly for an embarrassingly short amount of time) and then breaks.
>>
>>
>> Thanks again,
>>
>> Dan.
>>
>>
>>
>> On Wednesday, 28 January 2015 17:30:20 UTC, Christoph Junghans wrote:
>>>
>>> 2015-01-28 9:11 GMT-07:00 Daniel Allen <[email protected]>: 
>>> > Hi Christoph, 
>>> > 
>>> > thanks for your prompt reply. Sorry I should have been more clear, the 
>>> > system is blowing up on the very first CG run using the initial 
>>> guesses for 
>>> > potentials. I realise that you could say the initial configuration 
>>> must be 
>>> > bad however I don't think it'll be any worse than any other snapshot 
>>> from 
>>> > the reference simulation given that the bilayer is stable during this. 
>>> That usually means one of the initial guesses or the 
>>> Boltzmann-inverted potential (when no initial potentials are given) is 
>>> bad. 
>>> You can look at the energy file to see, which contribution to the 
>>> energy blows up. 
>>> Or replace the potential one by one by a Lennard Jones to find the bad 
>>> one. 
>>>
>>> Christoph 
>>>
>>> > 
>>> > Thanks for your help, 
>>> > 
>>> > Dan. 
>>> > 
>>> > On Wednesday, 28 January 2015 15:49:53 UTC, Christoph Junghans wrote: 
>>> >> 
>>> >> 2015-01-28 7:45 GMT-07:00 Daniel Allen <[email protected]>: 
>>> >> > Hello, 
>>> >> > 
>>> >> > I am trying to perform IBI on a bilayer formed of some polymers. I 
>>> have 
>>> >> > obtained distributions for non-bonded and bonded interactions from 
>>> >> > csg_stat 
>>> >> > and feed these into csg_inverse in *dist.tgt files. I am not 
>>> currently 
>>> >> > iterating bonded interactions, just using csg_inverse to produce 
>>> >> > tabulated 
>>> >> > potentials (bonds, angles, dihedrals). 
>>> >> > 
>>> >> > My RDFs do not quite converge to 1 as my reference system is not 
>>> >> > homogeneous 
>>> >> > so I am cutting off interactions at the first minimum in the RDFs 
>>> (at 
>>> >> > approximately 0.75 nm). 
>>> >> > 
>>> >> > After about 10 integration steps in the first iteration, the 
>>> simulation 
>>> >> > blows up. The initial configuration is the last snapshot of my 
>>> atomistic 
>>> >> > reference simulation mapped onto CG representation. 
>>> >> > 
>>> >> > I have looked at the nb potentials (they seem reasonable) and have 
>>> run a 
>>> >> > script to determine the shortest distance between 2 non-bonded 
>>> beads in 
>>> >> > my 
>>> >> > initial conf.gro that I feed in as the starting state. The shortest 
>>> >> > distance 
>>> >> > is 0.328 nm and sigma for that pairwise interaction is 0.41 nm. 
>>> This 
>>> >> > would 
>>> >> > result in an interaction energy of ~12.8 kJ/mol which doesn't seem 
>>> >> > ridiculously high? 
>>> >> > 
>>> >> > Any ideas how to move past this? I could try using a different 
>>> starting 
>>> >> > state but I fear that any snapshots from the reference system will 
>>> have 
>>> >> > pair 
>>> >> > distances < sigma. 
>>> >> It is really hard to say how to overcome this, but I have more 
>>> general 
>>> >> list of advice: 
>>> >> 1.) Scale the update 
>>> >> 2.) Change the update sequence if you have multiple interactions 
>>> >> 3.) Use last configuration from the previous step ("laststep") as 
>>> >> initial configuration 
>>> >> 4.) Do a pre simulation in each iteration step (pre_simulation) to 
>>> >> minimize the initial configuration 
>>> >> 5.) Increase the min to only update parts of the potential 
>>> >> 6.) Longer coarse-grained simulations 
>>> >> 7.) Apply a transformation on the rdf before doing the update 
>>> >> 8.) Use an initial guess (pot.in) on a bigger interval with 
>>> premolded 
>>> >> structure 
>>> >> 
>>> >> Christoph 
>>> >> 
>>> >> > 
>>> >> > 
>>> >> > Thanks in advance, 
>>> >> > 
>>> >> > Dan. 
>>> >> > 
>>> >> > -- 
>>> >> > You received this message because you are subscribed to the Google 
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>>> send 
>>> >> > an 
>>> >> > email to [email protected]. 
>>> >> > To post to this group, send email to [email protected]. 
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>>> >> > For more options, visit https://groups.google.com/d/optout. 
>>> >> 
>>> >> 
>>> >> 
>>> >> -- 
>>> >> Christoph Junghans 
>>> >> Web: http://www.compphys.de 
>>> > 
>>> > -- 
>>> > You received this message because you are subscribed to the Google 
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>>>
>>>
>>>
>>> -- 
>>> Christoph Junghans 
>>> Web: http://www.compphys.de 
>>>
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>

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