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    Monte Carlo And More: The Achille's Heel Of Simulation
    By News Staff | February 3rd 2013 01:00 PM | 2 comments | Print | E-mail | Track Comments

    A new paper outlines the many pitfalls associated with simulation methods such as Monte Carlo algorithms and other commonly used molecular dynamics approaches.

    The context of this paper is the exponential development of computing power in the past 60 years, estimated to have increased by a factor of 1015, in line with Moore's law., and the ability to try and simulate new things without understand models. Today, short simulations can reproduce a system the size of a bacterium.

    But there are many examples of issues arising when seemingly simple simulation methods are not applied with the due level of care. For example, simulations of small-scale systems, such as cubic boxes representing a unit cell as part of a crystal or liquid crystal, display effects that are linked to the fact that the sample is of finite size. Therefore, these simulations can only imitate, not reproduce, macroscopic effects unless effects that occur at microscopic scale, such as surface effects, are effectively removed.

    This is typically done by using periodic repetition of a small system in all directions.

    Daan Frenkel from the University of Cambridge, also focuses on methods that, at first blush, appear reasonable, but are flawed and are akin to attempting to compare apples and oranges.

     For example, computing a mechanical property of a system—say the potential energy—using a Monte Carlo simulation, which can be based on thermal averages, does not allow us to compute the thermal properties of such a system—such as entropy—in terms of thermal averages. Finally, the article also takes great care to debunk common myths and misconceptions pertaining to simulations, for instance, newer simulation methods are not necessarily better than older ones.


    Published in EPJ Plus 


    Comments

    Bonny Bonobo alias Brat
    For example, computing a mechanical property of a system—say the potential energy—using a Monte Carlo simulation, which can be based on thermal averages, does not allow us to compute the thermal properties of such a system—such as entropy—in terms of thermal averages.
    OK, so where does the thermal heat generated from wet hay for example, that according to Gerhard is often responsible for causing spontaneous barn fires, fit into this equation?
    My latest forum article 'Australian Researchers Discover Potential Blue Green Algae Cause & Treatment of Motor Neuron Disease (MND)&(ALS)' Parkinsons's and Alzheimer's can be found at http://www.science20.com/forums/medicine
    Helen - the article is about the limitations of a method of simulation where the system is essentially too complex and/or random to model exhausively. The Monte Carlo methods get a representative sample of the possibilities.  In a system which is reasonably well understood - like spontaneous combustion - it could be used to refine our understanding of the microscopic details - the dynamics of a handful of molecules reacting together, for instance. It's clearly impossible to consider every possible thermal vibration, so if you needed that level of simulation you would just try out a representative set. A paper raising the alarm about how these methods can go wrong if applied indiscrimately is not going to undermine our basic understanding of the processes.