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# Line 336 | Line 336 | With the use of an $fix$, however, comes a discontinui
336   the lack of particle images in the $x$, $y$, or $z$ directions past a
337   disance of $fix$.
338  
339 < With the use of an $fix$, however, comes a discontinuity in the potential energy curve (Fig.~\ref{fix}).
339 > With the use of an $fix$, however, comes a discontinuity in the
340 > potential energy curve (Fig.~\ref{fix}). To fix this discontinuity,
341 > one calculates the potential energy at the $r_{\text{cut}}$, and add
342 > that value to the potential.  This causes the function to go smoothly
343 > to zero at the cutoff radius.  This ensures conservation of energy
344 > when integrating the Newtonian equations of motion.
345 >
346 > The second main simplification used in this research is the Verlet
347 > neighbor list. \cite{allen87:csl} In the Verlet method, one generates
348 > a list of all neighbor atoms, $j$, surrounding atom $i$ within some
349 > cutoff $r_{\text{list}}$, where $r_{\text{list}}>r_{\text{cut}}$.
350 > This list is created the first time forces are evaluated, then on
351 > subsequent force evaluations, pair calculations are only calculated
352 > from the neighbor lists.  The lists are updated if any given particle
353 > in the system moves farther than $r_{\text{list}}-r_{\text{cut}}$,
354 > giving rise to the possibility that a particle has left or joined a
355 > neighbor list.
356  
357 + \subsection{\label{introSec:MDintegrate} Integration of the equations of motion}
358  
359 + A starting point for the discussion of molecular dynamics integrators
360 + is the Verlet algorithm. \cite{Frenkel1996} It begins with a Taylor
361 + expansion of position in time:
362 + \begin{equation}
363 + eq here
364 + \label{introEq:verletForward}
365 + \end{equation}
366 + As well as,
367 + \begin{equation}
368 + eq here
369 + \label{introEq:verletBack}
370 + \end{equation}
371 + Adding together Eq.~\ref{introEq:verletForward} and
372 + Eq.~\ref{introEq:verletBack} results in,
373 + \begin{equation}
374 + eq here
375 + \label{introEq:verletSum}
376 + \end{equation}
377 + Or equivalently,
378 + \begin{equation}
379 + eq here
380 + \label{introEq:verletFinal}
381 + \end{equation}
382 + Which contains an error in the estimate of the new positions on the
383 + order of $\Delta t^4$.
384 +
385 + In practice, however, the simulations in this research were integrated
386 + with a velocity reformulation of teh Verlet method. \cite{allen87:csl}
387 + \begin{equation}
388 + eq here
389 + \label{introEq:MDvelVerletPos}
390 + \end{equation}
391 + \begin{equation}
392 + eq here
393 + \label{introEq:MDvelVerletVel}
394 + \end{equation}
395 + The original Verlet algorithm can be regained by substituting the
396 + velocity back into Eq.~\ref{introEq:MDvelVerletPos}.  The Verlet
397 + formulations are chosen in this research because the algorithms have
398 + very little long term drift in energy conservation.  Energy
399 + conservation in a molecular dynamics simulation is of extreme
400 + importance, as it is a measure of how closely one is following the
401 + ``true'' trajectory wtih the finite integration scheme.  An exact
402 + solution to the integration will conserve area in phase space, as well
403 + as be reversible in time, that is, the trajectory integrated forward
404 + or backwards will exactly match itself.  Having a finite algorithm
405 + that both conserves area in phase space and is time reversible,
406 + therefore increases, but does not guarantee the ``correctness'' or the
407 + integrated trajectory.
408 +
409 + It can be shown, \cite{Frenkel1996} that although the Verlet algorithm
410 + does not rigorously preserve the actual Hamiltonian, it does preserve
411 + a pseudo-Hamiltonian which shadows the real one in phase space.  This
412 + pseudo-Hamiltonian is proveably area-conserving as well as time
413 + reversible.  The fact that it shadows the true Hamiltonian in phase
414 + space is acceptable in actual simulations as one is interested in the
415 + ensemble average of the observable being measured.  From the ergodic
416 + hypothesis (Sec.~\ref{introSec:StatThermo}), it is known that the time
417 + average will match the ensemble average, therefore two similar
418 + trajectories in phase space should give matching statistical averages.
419 +
420 + \subsection{\label{introSec:MDfurtheeeeer}Further Considerations}
421 + In the simulations presented in this research, a few additional
422 + parameters are needed to describe the motions.  The simulations
423 + involving water and phospholipids in Chapt.~\ref{chaptLipids} are
424 + required to integrate the equations of motions for dipoles on atoms.
425 + This involves an additional three parameters be specified for each
426 + dipole atom: $\phi$, $\theta$, and $\psi$.  These three angles are
427 + taken to be the Euler angles, where $\phi$ is a rotation about the
428 + $z$-axis, and $\theta$ is a rotation about the new $x$-axis, and
429 + $\psi$ is a final rotation about the new $z$-axis (see
430 + Fig.~\ref{introFig:euleerAngles}).  This sequence of rotations can be
431 + accumulated into a single $3\time3$ matrix $\underline{\mathbf{A}}$
432 + defined as follows:
433 + \begin{equation}
434 + eq here
435 + \label{introEq:EulerRotMat}
436 + \end{equation}
437 +
438 + The equations of motion for Euler angles can be written down as
439 + \cite{allen87:csl}
440 + \begin{equation}
441 + eq here
442 + \label{introEq:MDeuleeerPsi}
443 + \end{equation}
444 + Where $\omega^s_i$ is the angular velocity in the lab space frame
445 + along cartesian coordinate $i$.  However, a difficulty arises when
446 + attempting to integrate Eq.~\ref{introEq:MDeuleerPhi} and
447 + Eq.~\ref{introEq:MDeulerPsi}. The $\frac{1}{\sin \theta}$ present in
448 + both equations means there is a non-physical instability present when
449 + $\theta$ is 0 or $\pi$.
450 +
451 + To correct for this, the simulations integrate the rotation matrix,
452 + $\underline{\mathbf{A}}$, directly, thus avoiding the instability.
453 + This method was proposed by Dullwebber
454 + \emph{et. al.}\cite{Dullwebber:1997}, and is presented in
455 + Sec.~\ref{introSec:MDsymplecticRot}.
456 +
457 + \subsubsection{\label{introSec:MDliouville}Liouville Propagator}
458 +
459 +
460   \section{\label{introSec:chapterLayout}Chapter Layout}
461  
462   \subsection{\label{introSec:RSA}Random Sequential Adsorption}
463  
464   \subsection{\label{introSec:OOPSE}The OOPSE Simulation Package}
465  
466 < \subsection{\label{introSec:bilayers}A Mesoscale Model for Phospholipid Bilayers}
466 > \subsection{\label{introSec:bilayers}A Mesoscale Model for
467 > Phospholipid Bilayers}

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