MC simulations

Both MD and MC teclmiques evolve a finite-sized molecular configuration forward in time, in a step-by-step fashion. (In this context, MC simulation time has to be interpreted liberally, but there is a broad coimection between real time and simulation time (see [1, chapter 2]).) Connnon features of MD and MC simulation teclmiques are that there are limits on the typical timescales and length scales that can be investigated. The consequences of finite size must be considered both in specifying the molecular mteractions, and in analysing the results. 

Since H=K. + V, the canonical ensemble partition fiinction factorizes into ideal gas and excess parts, and as a consequence most averages of interest may be split into corresponding ideal and excess components, which sum to give the total. In MC simulations, we frequently calculate just the excess or configurational parts in this case, y consists just of the atomic coordinates, not the momenta, and the appropriate expressions are obtained from equation b3.3.2 by replacing fby the potential energy V. The ideal gas contributions are usually easily calculated from exact... 

One of the most expensive parts of a MD or MC simulations is the computation of long range interactions. Since the CPU time required for the... 

Other methods which are applied to conformational analysis and to generating multiple conformations and which can be regarded as random or stochastic techniques, since they explore the conformational space in a non-deterministic fashion, arc genetic algorithms (GA) [137, 1381 simulation methods, such as molecular dynamics (MD) and Monte Carlo (MC) simulations 1139], as well as simulated annealing [140], All of those approaches and their application to generate ensembles of conformations arc discussed in Chapter II, Section 7.2 in the Handbook. 

In Chapter 2, a brief discussion of statistical mechanics was presented. Statistical mechanics provides, in theory, a means for determining physical properties that are associated with not one molecule at one geometry, but rather, a macroscopic sample of the bulk liquid, solid, and so on. This is the net result of the properties of many molecules in many conformations, energy states, and the like. In practice, the difficult part of this process is not the statistical mechanics, but obtaining all the information about possible energy levels, conformations, and so on. Molecular dynamics (MD) and Monte Carlo (MC) simulations are two methods for obtaining this information... 

Eor many systems the ensemble that is used in an MC simulation refers to the canonical ensemble, (N, F/ T). This ensemble permits a rise and fall in the pressure of the system, P, because the temperature and volume are held constant. Thus, the probabiUty that any system of N particles, in a volume H at temperature Tis found in a configuration x is proportional to the Boltzmann weighted energy at that state, E, and it is given by... 

Monte Carlo search methods are stochastic techniques based on the use of random numbers and probability statistics to sample conformational space. The name Monte Carlo was originally coined by Metropolis and Ulam [4] during the Manhattan Project of World War II because of the similarity of this simulation technique to games of chance. Today a variety of Monte Carlo (MC) simulation methods are routinely used in diverse fields such as atmospheric studies, nuclear physics, traffic flow, and, of course, biochemistry and biophysics. In this section we focus on the application of the Monte Carlo method for... 

As stated above, MC simulations are popular in many diverse fields. Their popularity is due mainly to their ease of use and their good convergence properties. Nonetheless, straightforward and application of MC methods to biomolecules is often problematic due... 

For reasons of space and because of their prime importance, we focus here on free energy calculations based on detailed molecular dynamics (MD) or Monte Carlo (MC) simulations. However, several other computational approaches exist to calculate free energies, including continuum dielectric models and integral equation methods [4,14]. 

Interatomic potentials. All molecular dynamics simulations and some MC simulations depend on the form of the interaction between pairs of particles (atoms... 

There are basically two different computer simulation techniques known as molecular dynamics (MD) and Monte Carlo (MC) simulation. In MD molecular trajectories are computed by solving an equation of motion for equilibrium or nonequilibrium situations. Since the MD time scale is a physical one, this method permits investigations of time-dependent phenomena like, for example, transport processes [25,61-63]. In MC, on the other hand, trajectories are generated by a (biased) random walk in configuration space and, therefore, do not per se permit investigations of processes on a physical time scale (with the dynamics of spin lattices as an exception [64]). However, MC has the advantage that it can easily be applied to virtually all statistical-physical ensembles, which is of particular interest in the context of this chapter. On account of limitations of space and because excellent texts exist for the MD method [25,61-63,65], the present discussion will be restricted to the MC technique with particular emphasis on mixed stress-strain ensembles. 

FIG. 13 Scaling plot of the auto-correlation function (i EE(0) different temperatures for a bond fluctuation MC simulation [47]. 

Molecular dynamics, in contrast to MC simulations, is a typical model in which hydrodynamic effects are incorporated in the behavior of polymer solutions and may be properly accounted for. In the so-called nonequilibrium molecular dynamics method [54], Newton s equations of a (classical) many-particle problem are iteratively solved whereby quantities of both macroscopic and microscopic interest are expressed in terms of the configurational quantities such as the space coordinates or velocities of all particles. In addition, shear flow may be imposed by the homogeneous shear flow algorithm of Evans [56]. 

In systems without initiator, like wormlike mieelles, the degree of polymerization ehanges gradually with temperature (without divergenee of (L)). However, one should observe a maximum in the speeifie heat of the system, whieh aeeording to the MFA treatment [58] (Eq. (14)), should oeeur at J/k T = 4. Results from MC simulations [65] are eompared in Fig. 10 with the MFA predietion, Eq. (14), and found to be in good agreement. 

Thus, in order to reproduce the effect of an experimentally existing activation barrier for the scission/recombination process, one may introduce into the MC simulation the notion of frequency , lo, with which, every so many MC steps, an attempt for scission and/or recombination is undertaken. Clearly, as uj is reduced to zero, the average lifetime of the chains, which is proportional by detailed balance to Tbreak) will grow to infinity until the limit of conventional dead polymers is reached. In a computer experiment Lo can be easily controlled and various transport properties such as mean-square displacements (MSQ) and diffusion constants, which essentially depend on Tbreak) can be studied. 

Here (3A — Nc) is the number of degrees of freedom, equal to three times the number of particles minus the number of constraints, which typically will be 3 (corresponding to conservation of linear momentum). In a standard MC simulation the temperature is fixed NVT conditions), while it is a derived quantity in a standard MD simulation NVE conditions). 

Using successively an inverse Cluster Variation Method and an IMC algorithm, we determined a set of nine interactions for each alloy (for the IMC procedure, we used a lattice size of 4 24 ). For each alloy, the output from the inverse procedure has been used as an input interaction set in a direct MC simulation, in order to calculate a... 

An analysis of the hydration structure of water molecules in the major and minor grooves in B-DNA has shown that there is a filament of water molecules connecting both the inter and the intra phosphate groups of the two strands of B-DNA. However, such a connectivity is absent in the case of Z-DNA confirming earlier MC simulation results. The probability density distributions of the counterions around DNA shows deep penetration of the counterions in Z-DNA compared to B-DNA. Further, these distributions suggest very limited mobility for the counterions and show well defined counter-ion pattern as originally suggested in the MC study. 

MC simulations and semianalytical theories for diffusion of flexible polymers in random porous media, which have been summarized [35], indicate that the diffusion coefficient in random three-dimensional media follows the Rouse behavior (D N dependence) at short times, and approaches the reptation limit (D dependence) for long times. By contrast, the diffusion coefficient follows the reptation limit for a highly ordered media made from infinitely long rectangular rods connected at right angles in three-dimensional space (Uke a 3D grid). 

In the described MC simulation, the action of several simultaneous sources of variation is considered. The explanation of the different time courses of parameter influence on volume size between sensitivity and MCCC analyses lies in the fact that classic sensitivity analysis considers variations in model output due exclusively to the variation of one parameter component at a time, all else being equal. In these conditions, the regression coefficient between model output and parameter component value, in a small interval around the considered parameter, is approximately equal to the partial derivative of the model output with respect to the parameter component. 

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