Thanks!
:-) Lachele
Dr. B. Lachele Foley (she/her/hers)
Associate Research Scientist
Complex Carbohydrate Research Center
The University of Georgia
Athens, GA USA
lfoley.uga.edu
http://glycam.org
________________________________
From: Neale, Christopher Andrew <cneale.lanl.gov>
Sent: Friday, March 5, 2021 9:05 PM
To: AMBER Developers Mailing List <amber-developers.ambermd.org>
Subject: Re: [AMBER-Developers] [EXTERNAL] Re: Relaxed, converged and equilibrated
[EXTERNAL SENDER - PROCEED CAUTIOUSLY]
Intrinsically disordered proteins and other systems with entropically-limited sampling might complicate the idea of assigning probable intervening energy barrier heights to unseen states based on sampling time.
For questions involving only known data, I've always liked Wei Yang's reverse cumulative averaging approach: https://aip.scitation.org/doi/pdf/10.1063/1.1638996
On 3/5/21, 6:59 PM, "B. Lachele Foley" <lfoley.ccrc.uga.edu> wrote:
I have thought also about the "don't know what you don't know" problem. I'm not saying it would be easy to apply these concepts to MD, but, as you say, there might be some things one can say, even if not everything one wants to say. I like your energy barrier idea. I have also wondered, if, for example, the fact that we know all the sources of potential energy, because we assign them, could be used to an advantage.
I will look up Dan Zuckerman. Now, back to work. Enough goofing off. :-)
:-) Lachele
Dr. B. Lachele Foley (she/her/hers)
Associate Research Scientist
Complex Carbohydrate Research Center
The University of Georgia
Athens, GA USA
lfoley.uga.edu
http://glycam.org
________________________________
From: Adrian Roitberg <roitberg.ufl.edu>
Sent: Friday, March 5, 2021 4:37 PM
To: amber-developers.ambermd.org <amber-developers.ambermd.org>
Subject: Re: [AMBER-Developers] Relaxed, converged and equilibrated
[EXTERNAL SENDER - PROCEED CAUTIOUSLY]
Ah, interesting.
The problem, which plagues every sampling method, including Markov
States, etc, is that you do not know what you don't know, and you do not
even know if there are other things you should know...
For example, if you run very good MD for a long times, many replicates,
and you never visited a conformation 'next door' but with a high
barrier, you cannot do any estimate of error or probability, unless you
already know that other conformation existed.
Dan Zuckerman has written a bit on these things.
One thing you 'could' do in 'theory', but actually doing it is hard is
to put limits to possible things you do not know about.
For example, if you ran for a certain time and you did not find a very
different conformation, you could estimate the probability of the
existence of a barrier lower than X kcal/mol.
In the limit, you could say: I ran for 1 microsecond, and nothing very
different happened. I estimate that IF there is a barrier to the
unknown, if must be larger than Y, otherwise I would have probably seen
it already.
Adrian
On 3/5/21 3:56 PM, B. Lachele Foley wrote:
> [External Email]
>
> I have thought about this, too. I wonder if we could use something equivalent to a "confidence interval" in statistics. I think any such statement should include time as a qualifier. I don't really like the following, but it's a start - "the simulation is expected to have sampled X% of ensemble-appropriate phase space in the simulated time of Y seconds at 95% confidence". Has someone already done the math on this? I expect someone has.
>
> This could help with the diamond-graphite issue. That is, one could say something like: the system is in equilibrium [at some stated conditions] at 99.999% confidence over an interval of Y million years with complete sampling occurring, on average, every Z milliseconds.
>
> This sort of statistic would be very useful when people run multiple simulations for statistical or other purposes. Running multiple simulations improves sampling. But the sampling applies to a time length defined by the individual simulations (smallest? average? median?).
>
> I do expect that someone has already done work on this. Do you know of it?
>
> :-) Lachele
>
> Dr. B. Lachele Foley (she/her/hers)
> Associate Research Scientist
> Complex Carbohydrate Research Center
> The University of Georgia
> Athens, GA USA
> lfoley.uga.edu
> https://urldefense.proofpoint.com/v2/url?u=http-3A__glycam.org&d=DwIF-g&c=sJ6xIWYx-zLMB3EPkvcnVg&r=dl7Zd5Rzbdvo14I2ndQf4w&m=ewGru8T6Xnkeb3BC2QbSdotH-IkhqW4e-KjS_hgeY2M&s=SvPhYtzBhpD_YC18O0g6AiC42KmwA15qWEiVWMINn8w&e=
> ________________________________
> From: Adrian Roitberg <roitberg.ufl.edu>
> Sent: Friday, March 5, 2021 10:37 AM
> To: amber-developers.ambermd.org <amber-developers.ambermd.org>
> Subject: Re: [AMBER-Developers] Relaxed, converged and equilibrated
>
> [EXTERNAL SENDER - PROCEED CAUTIOUSLY]
>
>
> Not quite...
>
> Feynman' example was for graphite vs diamond.
>
> You can look at diamond essentially forever, with its own phonons
> 'equilibrated', but at longer time scales, probably > 10^15 years, it
> MUST turn into graphite.
>
> So, his fast and slow were for what we would call non-ergodic systems.
>
> In our day to day simulations, if you have a protein that can
> fold/unfold in milliseconds, the time scale separation gets trickier.
>
>
> Adrian
>
>
> On 3/5/21 5:41 AM, Romain M. Wolf wrote:
>> [External Email]
>>
>> I have no strong opinion on this either, but fully agree with Lachele's classification in a strict sense.
>> Just thinking about the (funny?) definition of equilibrium from Richard Feynman's Statistical Mechanics course:
>>
>> "A system is in equilibrium when “all the fast things have happened but the slow things have not.”
>>
>> Applying this to an MD "equilibration" phase, we might argue that the system is "more or less in equilibrium" when all *very* fast things have happened, and all *slower* things are far from having happened.
>>
>> ...regards...romain
>>
>>> On 3 Mar 2021, at 08:31, B. Lachele Foley <lfoley.ccrc.uga.edu> wrote:
>>>
>>> I have no strong opinions on this, but others, notably Adrian, do. I want to make sure I have the same understanding of these words as others.
>>>
>>> The following definitions are what I think others mean and are intended as a starting point for better definitions. Do you agree with them? If not, what should they be? Or what words would you give for these definitions? I tried to avoid deep stat-mech/thermo terminology.
>>>
>>> Relaxed (commonly called 'equilibrated'):
>>> In practical terms, the system has entered a stationary phase with respect to bulk properties that are expected to be in stationary phase per the simulation setup but that are not being held constant. These will typically include one or more of total energy, pressure, volume, density, and temperature. With respect to physics, this means that the simulated system has probably begun to sample configurations of mass and energy (momentum) in proportions consistent with the simulated ensemble (not necessarily the reality being modeled).
>>>
>>> Converged:
>>> For some property, not necessarily a bulk property, a stationary phase, which might unimodal or multimodal, has been sampled enough that meaningful statistical descriptions might be made about it. The system has sampled very well, in ensemble-appropriate proportions, a persistent or metastable subset of the phase space.
>>>
>>> Equilibrated:
>>> The entire system has sampled all available configurations sufficiently that meaningful statistics can be made about any system property. That is, the system has thoroughly sampled an ensemble-appropriate portion of the phase space, in ensemble-appropriate proportions, multiple times.
>>>
>>> Most simulations of any significant complexity can only hope to attain 'converged' with respect to whatever properties are being tracked. It is very difficult to know for certain that other behaviors would not be observed were the simulation to be run longer. I think if there were an easy way to tell, then we would not very often need to do simulations. This problem also impacts our ability to know if 'relaxed' is truly 'relaxed', etc.
>>>
>>> :-) Lachele
>>>
>>> Dr. B. Lachele Foley (she/her/hers)
>>> Associate Research Scientist
>>> Complex Carbohydrate Research Center
>>> The University of Georgia
>>> Athens, GA USA
>>> lfoley.uga.edu
>>> https://urldefense.proofpoint.com/v2/url?u=http-3A__glycam.org&d=DwIGaQ&c=sJ6xIWYx-zLMB3EPkvcnVg&r=dl7Zd5Rzbdvo14I2ndQf4w&m=blvyHE3Kysn_8gKQFX5r42fwC1_ZX38vrSktxkFMmDU&s=JCSpBAobP4SY4xAwB2wzD2u-LrX2ozIoZ1eF-OuBV14&e=
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> --
> Dr. Adrian E. Roitberg
> V.T. and Louise Jackson Professor in Chemistry
> Department of Chemistry
> University of Florida
> roitberg.ufl.edu
> 352-392-6972
>
>
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--
Dr. Adrian E. Roitberg
V.T. and Louise Jackson Professor in Chemistry
Department of Chemistry
University of Florida
roitberg.ufl.edu
352-392-6972
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Received on Fri Mar 05 2021 - 18:30:02 PST
