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# Line 140 | Line 140 | V_\textrm{elec} = \frac{1}{2}& \sum_{i=1}^N\sum_{j=1}^
140   \end{split}
141   \label{eq:EwaldSum}
142   \end{equation}
143 < where $\alpha$ is a damping parameter, or separation constant, with
144 < units of \AA$^{-1}$, $\mathbf{k}$ are the reciprocal vectors and are
145 < equal to $2\pi\mathbf{n}/L^2$, and $\epsilon_\textrm{S}$ is the
146 < dielectric constant of the surrounding medium. The final two terms of
143 > where $\alpha$ is the damping or convergence parameter with units of
144 > \AA$^{-1}$, $\mathbf{k}$ are the reciprocal vectors and are equal to
145 > $2\pi\mathbf{n}/L^2$, and $\epsilon_\textrm{S}$ is the dielectric
146 > constant of the surrounding medium. The final two terms of
147   eq. (\ref{eq:EwaldSum}) are a particle-self term and a dipolar term
148   for interacting with a surrounding dielectric.\cite{Allen87} This
149   dipolar term was neglected in early applications in molecular
# Line 159 | Line 159 | convergent behavior.  Indeed, it has often been observ
159   convergence.  In more modern simulations, the simulation boxes have
160   grown large enough that a real-space cutoff could potentially give
161   convergent behavior.  Indeed, it has often been observed that the
162 < reciprocal-space portion of the Ewald sum can be vanishingly
163 < small compared to the real-space portion.\cite{XXX}
162 > reciprocal-space portion of the Ewald sum can be small and rapidly
163 > convergent compared to the real-space portion with the choice of small
164 > $\alpha$.\cite{Karasawa89,Kolafa92}
165  
166   \begin{figure}
167   \centering
# Line 176 | Line 177 | The original Ewald summation is an $\mathscr{O}(N^2)$
177   \end{figure}
178  
179   The original Ewald summation is an $\mathscr{O}(N^2)$ algorithm.  The
180 < separation constant $(\alpha)$ plays an important role in balancing
180 > convergence parameter $(\alpha)$ plays an important role in balancing
181   the computational cost between the direct and reciprocal-space
182   portions of the summation.  The choice of this value allows one to
183   select whether the real-space or reciprocal space portion of the
# Line 492 | Line 493 | particle sites, but they use these summations in diffe
493   techniques utilize pairwise summations of interactions between
494   particle sites, but they use these summations in different ways.
495  
496 < In MC, the potential energy difference between two subsequent
497 < configurations dictates the progression of MC sampling.  Going back to
498 < the origins of this method, the acceptance criterion for the canonical
499 < ensemble laid out by Metropolis \textit{et al.} states that a
500 < subsequent configuration is accepted if $\Delta E < 0$ or if $\xi <
501 < \exp(-\Delta E/kT)$, where $\xi$ is a random number between 0 and
502 < 1.\cite{Metropolis53} Maintaining the correct $\Delta E$ when using an
503 < alternate method for handling the long-range electrostatics will
504 < ensure proper sampling from the ensemble.
496 > In MC, the potential energy difference between configurations dictates
497 > the progression of MC sampling.  Going back to the origins of this
498 > method, the acceptance criterion for the canonical ensemble laid out
499 > by Metropolis \textit{et al.} states that a subsequent configuration
500 > is accepted if $\Delta E < 0$ or if $\xi < \exp(-\Delta E/kT)$, where
501 > $\xi$ is a random number between 0 and 1.\cite{Metropolis53}
502 > Maintaining the correct $\Delta E$ when using an alternate method for
503 > handling the long-range electrostatics will ensure proper sampling
504 > from the ensemble.
505  
506   In MD, the derivative of the potential governs how the system will
507   progress in time.  Consequently, the force and torque vectors on each
# Line 513 | Line 514 | vectors will diverge from each other more rapidly.
514   vectors will diverge from each other more rapidly.
515  
516   \subsection{Monte Carlo and the Energy Gap}\label{sec:MCMethods}
517 +
518   The pairwise summation techniques (outlined in section
519   \ref{sec:ESMethods}) were evaluated for use in MC simulations by
520   studying the energy differences between conformations.  We took the
521   SPME-computed energy difference between two conformations to be the
522   correct behavior. An ideal performance by an alternative method would
523 < reproduce these energy differences exactly.  Since none of the methods
524 < provide exact energy differences, we used linear least squares
525 < regressions of the $\Delta E$ values between configurations using SPME
526 < against $\Delta E$ values using tested methods provides a quantitative
527 < comparison of this agreement.  Unitary results for both the
528 < correlation and correlation coefficient for these regressions indicate
529 < equivalent energetic results between the method under consideration
530 < and electrostatics handled using SPME.  Sample correlation plots for
531 < two alternate methods are shown in Fig. \ref{fig:linearFit}.
523 > reproduce these energy differences exactly (even if the absolute
524 > energies calculated by the methods are different).  Since none of the
525 > methods provide exact energy differences, we used linear least squares
526 > regressions of energy gap data to evaluate how closely the methods
527 > mimicked the Ewald energy gaps.  Unitary results for both the
528 > correlation (slope) and correlation coefficient for these regressions
529 > indicate perfect agreement between the alternative method and SPME.
530 > Sample correlation plots for two alternate methods are shown in
531 > Fig. \ref{fig:linearFit}.
532  
533   \begin{figure}
534   \centering
535   \includegraphics[width = \linewidth]{./dualLinear.pdf}
536 < \caption{Example least squares regressions of the configuration energy differences for SPC/E water systems. The upper plot shows a data set with a poor correlation coefficient ($R^2$), while the lower plot shows a data set with a good correlation coefficient.}
537 < \label{fig:linearFit}
536 > \caption{Example least squares regressions of the configuration energy
537 > differences for SPC/E water systems. The upper plot shows a data set
538 > with a poor correlation coefficient ($R^2$), while the lower plot
539 > shows a data set with a good correlation coefficient.}
540 > \label{fig:linearFit}
541   \end{figure}
542  
543   Each system type (detailed in section \ref{sec:RepSims}) was
544   represented using 500 independent configurations.  Additionally, we
545 < used seven different system types, so each of the alternate
545 > used seven different system types, so each of the alternative
546   (non-Ewald) electrostatic summation methods was evaluated using
547   873,250 configurational energy differences.
548  
# Line 567 | Line 572 | between those computed from the particular method and
572   investigated through measurement of the angle ($\theta$) formed
573   between those computed from the particular method and those from SPME,
574   \begin{equation}
575 < \theta_f = \cos^{-1} \left(\hat{f}_\textrm{SPME} \cdot \hat{f}_\textrm{Method}\right),
575 > \theta_f = \cos^{-1} \left(\hat{F}_\textrm{SPME} \cdot \hat{F}_\textrm{M}\right),
576   \end{equation}
577 < where $\hat{f}_\textrm{M}$ is the unit vector pointing along the
578 < force vector computed using method $M$.  
579 <
580 < Each of these $\theta$ values was accumulated in a distribution
576 < function, weighted by the area on the unit sphere.  Non-linear
577 < Gaussian fits were used to measure the width of the resulting
578 < distributions.
579 <
580 < \begin{figure}
581 < \centering
582 < \includegraphics[width = \linewidth]{./gaussFit.pdf}
583 < \caption{Sample fit of the angular distribution of the force vectors over all of the studied systems.  Gaussian fits were used to obtain values for the variance in force and torque vectors used in the following figure.}
584 < \label{fig:gaussian}
585 < \end{figure}
586 <
587 < Figure \ref{fig:gaussian} shows an example distribution with applied
588 < non-linear fits.  The solid line is a Gaussian profile, while the
589 < dotted line is a Voigt profile, a convolution of a Gaussian and a
590 < Lorentzian.  Since this distribution is a measure of angular error
577 > where $\hat{f}_\textrm{M}$ is the unit vector pointing along the force
578 > vector computed using method M.  Each of these $\theta$ values was
579 > accumulated in a distribution function and weighted by the area on the
580 > unit sphere.  Since this distribution is a measure of angular error
581   between two different electrostatic summation methods, there is no
582 < {\it a priori} reason for the profile to adhere to any specific shape.
583 < Gaussian fits was used to compare all the tested methods.  The
584 < variance ($\sigma^2$) was extracted from each of these fits and was
585 < used to compare distribution widths.  Values of $\sigma^2$ near zero
586 < indicate vector directions indistinguishable from those calculated
587 < when using the reference method (SPME).
582 > {\it a priori} reason for the profile to adhere to any specific
583 > shape. Thus, gaussian fits were used to measure the width of the
584 > resulting distributions.
585 > %
586 > %\begin{figure}
587 > %\centering
588 > %\includegraphics[width = \linewidth]{./gaussFit.pdf}
589 > %\caption{Sample fit of the angular distribution of the force vectors
590 > %accumulated using all of the studied systems.  Gaussian fits were used
591 > %to obtain values for the variance in force and torque vectors.}
592 > %\label{fig:gaussian}
593 > %\end{figure}
594 > %
595 > %Figure \ref{fig:gaussian} shows an example distribution with applied
596 > %non-linear fits.  The solid line is a Gaussian profile, while the
597 > %dotted line is a Voigt profile, a convolution of a Gaussian and a
598 > %Lorentzian.  
599 > %Since this distribution is a measure of angular error between two
600 > %different electrostatic summation methods, there is no {\it a priori}
601 > %reason for the profile to adhere to any specific shape.
602 > %Gaussian fits was used to compare all the tested methods.  
603 > The variance ($\sigma^2$) was extracted from each of these fits and
604 > was used to compare distribution widths.  Values of $\sigma^2$ near
605 > zero indicate vector directions indistinguishable from those
606 > calculated when using the reference method (SPME).
607  
608   \subsection{Short-time Dynamics}
609 < Evaluation of the short-time dynamics of charged systems was performed
610 < by considering the 1000 K NaCl crystal system while using a subset of the
611 < best performing pairwise methods.  The NaCl crystal was chosen to
612 < avoid possible complications involving the propagation techniques of
613 < orientational motion in molecular systems.  All systems were started
614 < with the same initial positions and velocities.  Simulations were
615 < performed under the microcanonical ensemble, and velocity
609 >
610 > The effects of the alternative electrostatic summation methods on the
611 > short-time dynamics of charged systems were evaluated by considering a
612 > NaCl crystal at a temperature of 1000 K.  A subset of the best
613 > performing pairwise methods was used in this comparison.  The NaCl
614 > crystal was chosen to avoid possible complications from the treatment
615 > of orientational motion in molecular systems.  All systems were
616 > started with the same initial positions and velocities.  Simulations
617 > were performed under the microcanonical ensemble, and velocity
618   autocorrelation functions (Eq. \ref{eq:vCorr}) were computed for each
619   of the trajectories,
620   \begin{equation}
# Line 617 | Line 628 | functions was used for comparisons.
628   functions was used for comparisons.
629  
630   \subsection{Long-Time and Collective Motion}\label{sec:LongTimeMethods}
631 < Evaluation of the long-time dynamics of charged systems was performed
632 < by considering the NaCl crystal system, again while using a subset of
633 < the best performing pairwise methods.  To enhance the atomic motion,
634 < these crystals were equilibrated at 1000 K, near the experimental
635 < $T_m$ for NaCl.  Simulations were performed under the microcanonical
636 < ensemble, and velocity information was saved every 5 fs over 100 ps
637 < trajectories.  The power spectrum ($I(\omega)$) was obtained via
627 < Fourier transform of the velocity autocorrelation function
628 < \begin{equation}
629 < I(\omega) = \frac{1}{2\pi}\int^{\infty}_{-\infty}C_v(t)e^{-i\omega t}dt,
631 >
632 > The effects of the same subset of alternative electrostatic methods on
633 > the {\it long-time} dynamics of charged systems were evaluated using
634 > the same model system (NaCl crystals at 1000K).  The power spectrum
635 > ($I(\omega)$) was obtained via Fourier transform of the velocity
636 > autocorrelation function, \begin{equation} I(\omega) =
637 > \frac{1}{2\pi}\int^{\infty}_{-\infty}C_v(t)e^{-i\omega t}dt,
638   \label{eq:powerSpec}
639   \end{equation}
640   where the frequency, $\omega=0,\ 1,\ ...,\ N-1$. Again, because the
641   NaCl crystal is composed of two different atom types, the average of
642 < the two resulting power spectra was used for comparisons.
642 > the two resulting power spectra was used for comparisons. Simulations
643 > were performed under the microcanonical ensemble, and velocity
644 > information was saved every 5 fs over 100 ps trajectories.
645  
646   \subsection{Representative Simulations}\label{sec:RepSims}
647 < A variety of common and representative simulations were analyzed to
648 < determine the relative effectiveness of the pairwise summation
649 < techniques in reproducing the energetics and dynamics exhibited by
650 < SPME.  The studied systems were as follows:
647 > A variety of representative simulations were analyzed to determine the
648 > relative effectiveness of the pairwise summation techniques in
649 > reproducing the energetics and dynamics exhibited by SPME.  We wanted
650 > to span the space of modern simulations (i.e. from liquids of neutral
651 > molecules to ionic crystals), so the systems studied were:
652   \begin{enumerate}
653 < \item Liquid Water
654 < \item Crystalline Water (Ice I$_\textrm{c}$)
655 < \item NaCl Crystal
656 < \item NaCl Melt
657 < \item Low Ionic Strength Solution of NaCl in Water
658 < \item High Ionic Strength Solution of NaCl in Water
659 < \item 6 \AA\  Radius Sphere of Argon in Water
653 > \item liquid water (SPC/E),\cite{Berendsen87}
654 > \item crystalline water (Ice I$_\textrm{c}$ crystals of SPC/E),
655 > \item NaCl crystals,
656 > \item NaCl melts,
657 > \item a low ionic strength solution of NaCl in water (0.11 M),
658 > \item a high ionic strength solution of NaCl in water (1.1 M), and
659 > \item a 6 \AA\  radius sphere of Argon in water.
660   \end{enumerate}
661   By utilizing the pairwise techniques (outlined in section
662   \ref{sec:ESMethods}) in systems composed entirely of neutral groups,
663 < charged particles, and mixtures of the two, we can comment on possible
664 < system dependence and/or universal applicability of the techniques.
663 > charged particles, and mixtures of the two, we hope to discern under
664 > which conditions it will be possible to use one of the alternative
665 > summation methodologies instead of the Ewald sum.
666  
667 < Generation of the system configurations was dependent on the system
668 < type.  For the solid and liquid water configurations, configuration
669 < snapshots were taken at regular intervals from higher temperature 1000
670 < SPC/E water molecule trajectories and each equilibrated
671 < individually.\cite{Berendsen87} The solid and liquid NaCl systems
672 < consisted of 500 Na+ and 500 Cl- ions and were selected and
673 < equilibrated in the same fashion as the water systems.  For the low
674 < and high ionic strength NaCl solutions, 4 and 40 ions were first
675 < solvated in a 1000 water molecule boxes respectively.  Ion and water
676 < positions were then randomly swapped, and the resulting configurations
677 < were again equilibrated individually.  Finally, for the Argon/Water
678 < "charge void" systems, the identities of all the SPC/E waters within 6
679 < \AA\ of the center of the equilibrated water configurations were
680 < converted to argon (Fig. \ref{fig:argonSlice}).
681 <
682 < \begin{figure}
671 < \centering
672 < \includegraphics[width = \linewidth]{./slice.pdf}
673 < \caption{A slice from the center of a water box used in a charge void simulation.  The darkened region represents the boundary sphere within which the water molecules were converted to argon atoms.}
674 < \label{fig:argonSlice}
675 < \end{figure}
667 > For the solid and liquid water configurations, configurations were
668 > taken at regular intervals from high temperature trajectories of 1000
669 > SPC/E water molecules.  Each configuration was equilibrated
670 > independently at a lower temperature (300~K for the liquid, 200~K for
671 > the crystal).  The solid and liquid NaCl systems consisted of 500
672 > $\textrm{Na}^{+}$ and 500 $\textrm{Cl}^{-}$ ions.  Configurations for
673 > these systems were selected and equilibrated in the same manner as the
674 > water systems.  The equilibrated temperatures were 1000~K for the NaCl
675 > crystal and 7000~K for the liquid. The ionic solutions were made by
676 > solvating 4 (or 40) ions in a periodic box containing 1000 SPC/E water
677 > molecules.  Ion and water positions were then randomly swapped, and
678 > the resulting configurations were again equilibrated individually.
679 > Finally, for the Argon / Water ``charge void'' systems, the identities
680 > of all the SPC/E waters within 6 \AA\ of the center of the
681 > equilibrated water configurations were converted to argon.
682 > %(Fig. \ref{fig:argonSlice}).
683  
684 < \subsection{Electrostatic Summation Methods}\label{sec:ESMethods}
685 < Electrostatic summation method comparisons were performed using SPME,
686 < the {\sc sp} and {\sc sf} methods - both with damping
687 < parameters ($\alpha$) of 0.0, 0.1, 0.2, and 0.3 \AA$^{-1}$ (no, weak,
681 < moderate, and strong damping respectively), reaction field with an
682 < infinite dielectric constant, and an unmodified cutoff.  Group-based
683 < cutoffs with a fifth-order polynomial switching function were
684 < necessary for the reaction field simulations and were utilized in the
685 < SP, SF, and pure cutoff methods for comparison to the standard lack of
686 < group-based cutoffs with a hard truncation.  The SPME calculations
687 < were performed using the TINKER implementation of SPME,\cite{Ponder87}
688 < while all other method calculations were performed using the OOPSE
689 < molecular mechanics package.\cite{Meineke05}
684 > These procedures guaranteed us a set of representative configurations
685 > from chemically-relevant systems sampled from an appropriate
686 > ensemble. Force field parameters for the ions and Argon were taken
687 > from the force field utilized by {\sc oopse}.\cite{Meineke05}
688  
689 < These methods were additionally evaluated with three different cutoff
690 < radii (9, 12, and 15 \AA) to investigate possible cutoff radius
691 < dependence.  It should be noted that the damping parameter chosen in
692 < SPME, or so called ``Ewald Coefficient", has a significant effect on
693 < the energies and forces calculated.  Typical molecular mechanics
694 < packages default this to a value dependent on the cutoff radius and a
695 < tolerance (typically less than $1 \times 10^{-4}$ kcal/mol).  Smaller
696 < tolerances are typically associated with increased accuracy, but this
699 < usually means more time spent calculating the reciprocal-space portion
700 < of the summation.\cite{Perram88,Essmann95} The default TINKER
701 < tolerance of $1 \times 10^{-8}$ kcal/mol was used in all SPME
702 < calculations, resulting in Ewald Coefficients of 0.4200, 0.3119, and
703 < 0.2476 \AA$^{-1}$ for cutoff radii of 9, 12, and 15 \AA\ respectively.
689 > %\begin{figure}
690 > %\centering
691 > %\includegraphics[width = \linewidth]{./slice.pdf}
692 > %\caption{A slice from the center of a water box used in a charge void
693 > %simulation.  The darkened region represents the boundary sphere within
694 > %which the water molecules were converted to argon atoms.}
695 > %\label{fig:argonSlice}
696 > %\end{figure}
697  
698 + \subsection{Comparison of Summation Methods}\label{sec:ESMethods}
699 + We compared the following alternative summation methods with results
700 + from the reference method (SPME):
701 + \begin{itemize}
702 + \item {\sc sp} with damping parameters ($\alpha$) of 0.0, 0.1, 0.2,
703 + and 0.3 \AA$^{-1}$,
704 + \item {\sc sf} with damping parameters ($\alpha$) of 0.0, 0.1, 0.2,
705 + and 0.3 \AA$^{-1}$,
706 + \item reaction field with an infinite dielectric constant, and
707 + \item an unmodified cutoff.
708 + \end{itemize}
709 + Group-based cutoffs with a fifth-order polynomial switching function
710 + were utilized for the reaction field simulations.  Additionally, we
711 + investigated the use of these cutoffs with the SP, SF, and pure
712 + cutoff.  The SPME electrostatics were performed using the TINKER
713 + implementation of SPME,\cite{Ponder87} while all other method
714 + calculations were performed using the OOPSE molecular mechanics
715 + package.\cite{Meineke05} All other portions of the energy calculation
716 + (i.e. Lennard-Jones interactions) were handled in exactly the same
717 + manner across all systems and configurations.
718 +
719 + The althernative methods were also evaluated with three different
720 + cutoff radii (9, 12, and 15 \AA).  As noted previously, the
721 + convergence parameter ($\alpha$) plays a role in the balance of the
722 + real-space and reciprocal-space portions of the Ewald calculation.
723 + Typical molecular mechanics packages set this to a value dependent on
724 + the cutoff radius and a tolerance (typically less than $1 \times
725 + 10^{-4}$ kcal/mol).  Smaller tolerances are typically associated with
726 + increased accuracy at the expense of increased time spent calculating
727 + the reciprocal-space portion of the
728 + summation.\cite{Perram88,Essmann95} The default TINKER tolerance of $1
729 + \times 10^{-8}$ kcal/mol was used in all SPME calculations, resulting
730 + in Ewald Coefficients of 0.4200, 0.3119, and 0.2476 \AA$^{-1}$ for
731 + cutoff radii of 9, 12, and 15 \AA\ respectively.
732 +
733   \section{Results and Discussion}
734  
735   \subsection{Configuration Energy Differences}\label{sec:EnergyResults}
# Line 714 | Line 742 | figure \ref{fig:delE}.
742   \begin{figure}
743   \centering
744   \includegraphics[width=5.5in]{./delEplot.pdf}
745 < \caption{Statistical analysis of the quality of configurational energy differences for a given electrostatic method compared with the reference Ewald sum.  Results with a value equal to 1 (dashed line) indicate $\Delta E$ values indistinguishable from those obtained using SPME.  Different values of the cutoff radius are indicated with different symbols (9\AA\ = circles, 12\AA\ = squares, and 15\AA\ = inverted triangles).}
745 > \caption{Statistical analysis of the quality of configurational energy
746 > differences for a given electrostatic method compared with the
747 > reference Ewald sum.  Results with a value equal to 1 (dashed line)
748 > indicate $\Delta E$ values indistinguishable from those obtained using
749 > SPME.  Different values of the cutoff radius are indicated with
750 > different symbols (9\AA\ = circles, 12\AA\ = squares, and 15\AA\ =
751 > inverted triangles).}
752   \label{fig:delE}
753   \end{figure}
754  
755 < In this figure, it is apparent that it is unreasonable to expect
756 < realistic results using an unmodified cutoff.  This is not all that
757 < surprising since this results in large energy fluctuations as atoms or
758 < molecules move in and out of the cutoff radius.\cite{Rahman71,Adams79}
759 < These fluctuations can be alleviated to some degree by using group
760 < based cutoffs with a switching
761 < function.\cite{Adams79,Steinbach94,Leach01} The Group Switch Cutoff
762 < row doesn't show a significant improvement in this plot because the
763 < salt and salt solution systems contain non-neutral groups, see the
764 < accompanying supporting information for a comparison where all groups
765 < are neutral.
766 <
767 < Correcting the resulting charged cutoff sphere is one of the purposes
768 < of the damped Coulomb summation proposed by Wolf \textit{et
769 < al.},\cite{Wolf99} and this correction indeed improves the results as
770 < seen in the {\sc sp} rows.  While the undamped case of this
771 < method is a significant improvement over the pure cutoff, it still
772 < doesn't correlate that well with SPME.  Inclusion of potential damping
773 < improves the results, and using an $\alpha$ of 0.2 \AA $^{-1}$ shows
755 > The most striking feature of this plot is how well the Shifted Force
756 > ({\sc sf}) and Shifted Potential ({\sc sp}) methods capture the energy
757 > differences.  For the undamped {\sc sf} method, and the
758 > moderately-damped {\sc sp} methods, the results are nearly
759 > indistinguishable from the Ewald results.  The other common methods do
760 > significantly less well.  
761 >
762 > The unmodified cutoff method is essentially unusable.  This is not
763 > surprising since hard cutoffs give large energy fluctuations as atoms
764 > or molecules move in and out of the cutoff
765 > radius.\cite{Rahman71,Adams79} These fluctuations can be alleviated to
766 > some degree by using group based cutoffs with a switching
767 > function.\cite{Adams79,Steinbach94,Leach01} However, we do not see
768 > significant improvement using the group-switched cutoff because the
769 > salt and salt solution systems contain non-neutral groups.  Interested
770 > readers can consult the accompanying supporting information for a
771 > comparison where all groups are neutral.
772 >
773 > For the {\sc sp} method, inclusion of potential damping improves the
774 > agreement with Ewald, and using an $\alpha$ of 0.2 \AA $^{-1}$ shows
775   an excellent correlation and quality of fit with the SPME results,
776 < particularly with a cutoff radius greater than 12 \AA .  Use of a
777 < larger damping parameter is more helpful for the shortest cutoff
778 < shown, but it has a detrimental effect on simulations with larger
779 < cutoffs.  In the {\sc sf} sets, increasing damping results in
745 < progressively poorer correlation.  Overall, the undamped case is the
746 < best performing set, as the correlation and quality of fits are
747 < consistently superior regardless of the cutoff distance.  This result
748 < is beneficial in that the undamped case is less computationally
749 < prohibitive do to the lack of complimentary error function calculation
750 < when performing the electrostatic pair interaction.  The reaction
751 < field results illustrates some of that method's limitations, primarily
752 < that it was developed for use in homogenous systems; although it does
753 < provide results that are an improvement over those from an unmodified
754 < cutoff.
776 > particularly with a cutoff radius greater than 12
777 > \AA .  Use of a larger damping parameter is more helpful for the
778 > shortest cutoff shown, but it has a detrimental effect on simulations
779 > with larger cutoffs.  
780  
781 + In the {\sc sf} sets, increasing damping results in progressively
782 + worse correlation with Ewald.  Overall, the undamped case is the best
783 + performing set, as the correlation and quality of fits are
784 + consistently superior regardless of the cutoff distance.  The undamped
785 + case is also less computationally demanding (because no evaluation of
786 + the complementary error function is required).
787 +
788 + The reaction field results illustrates some of that method's
789 + limitations, primarily that it was developed for use in homogenous
790 + systems; although it does provide results that are an improvement over
791 + those from an unmodified cutoff.
792 +
793   \subsection{Magnitudes of the Force and Torque Vectors}
794  
795   Evaluation of pairwise methods for use in Molecular Dynamics
# Line 766 | Line 803 | accumulated analysis over all the system types.
803   \begin{figure}
804   \centering
805   \includegraphics[width=5.5in]{./frcMagplot.pdf}
806 < \caption{Statistical analysis of the quality of the force vector magnitudes for a given electrostatic method compared with the reference Ewald sum.  Results with a value equal to 1 (dashed line) indicate force magnitude values indistinguishable from those obtained using SPME.  Different values of the cutoff radius are indicated with different symbols (9\AA\ = circles, 12\AA\ = squares, and 15\AA\ = inverted triangles).}
806 > \caption{Statistical analysis of the quality of the force vector
807 > magnitudes for a given electrostatic method compared with the
808 > reference Ewald sum.  Results with a value equal to 1 (dashed line)
809 > indicate force magnitude values indistinguishable from those obtained
810 > using SPME.  Different values of the cutoff radius are indicated with
811 > different symbols (9\AA\ = circles, 12\AA\ = squares, and 15\AA\ =
812 > inverted triangles).}
813   \label{fig:frcMag}
814   \end{figure}
815  
# Line 792 | Line 835 | performs more favorably.
835   \begin{figure}
836   \centering
837   \includegraphics[width=5.5in]{./trqMagplot.pdf}
838 < \caption{Statistical analysis of the quality of the torque vector magnitudes for a given electrostatic method compared with the reference Ewald sum.  Results with a value equal to 1 (dashed line) indicate torque magnitude values indistinguishable from those obtained using SPME.  Different values of the cutoff radius are indicated with different symbols (9\AA\ = circles, 12\AA\ = squares, and 15\AA\ = inverted triangles).}
838 > \caption{Statistical analysis of the quality of the torque vector
839 > magnitudes for a given electrostatic method compared with the
840 > reference Ewald sum.  Results with a value equal to 1 (dashed line)
841 > indicate torque magnitude values indistinguishable from those obtained
842 > using SPME.  Different values of the cutoff radius are indicated with
843 > different symbols (9\AA\ = circles, 12\AA\ = squares, and 15\AA\ =
844 > inverted triangles).}
845   \label{fig:trqMag}
846   \end{figure}
847  
# Line 822 | Line 871 | error distributions of the combined set over all syste
871   \begin{figure}
872   \centering
873   \includegraphics[width=5.5in]{./frcTrqAngplot.pdf}
874 < \caption{Statistical analysis of the quality of the Gaussian fit of the force and torque vector angular distributions for a given electrostatic method compared with the reference Ewald sum.  Results with a variance ($\sigma^2$) equal to zero (dashed line) indicate force and torque directions indistinguishable from those obtained using SPME.  Different values of the cutoff radius are indicated with different symbols (9\AA\ = circles, 12\AA\ = squares, and 15\AA\ = inverted triangles).}
874 > \caption{Statistical analysis of the quality of the Gaussian fit of
875 > the force and torque vector angular distributions for a given
876 > electrostatic method compared with the reference Ewald sum.  Results
877 > with a variance ($\sigma^2$) equal to zero (dashed line) indicate
878 > force and torque directions indistinguishable from those obtained
879 > using SPME.  Different values of the cutoff radius are indicated with
880 > different symbols (9\AA\ = circles, 12\AA\ = squares, and 15\AA\ =
881 > inverted triangles).}
882   \label{fig:frcTrqAng}
883   \end{figure}
884  
# Line 846 | Line 902 | investigated further in the accompanying supporting in
902  
903   \begin{table}[htbp]
904     \centering
905 <   \caption{Variance ($\sigma^2$) of the force (top set) and torque (bottom set) vector angle difference distributions for the Shifted Potential and Shifted Force methods.  Calculations were performed both with (Y) and without (N) group based cutoffs and a switching function.  The $\alpha$ values have units of \AA$^{-1}$ and the variance values have units of degrees$^2$.}  
905 >   \caption{Variance ($\sigma^2$) of the force (top set) and torque
906 > (bottom set) vector angle difference distributions for the Shifted Potential and Shifted Force methods.  Calculations were performed both with (Y) and without (N) group based cutoffs and a switching function.  The $\alpha$ values have units of \AA$^{-1}$ and the variance values have units of degrees$^2$.}      
907     \begin{tabular}{@{} ccrrrrrrrr @{}}
908        \\
909        \toprule
# Line 934 | Line 991 | summation methods from the above results.
991   \begin{figure}
992   \centering
993   \includegraphics[width = \linewidth]{./vCorrPlot.pdf}
994 < \caption{Velocity auto-correlation functions of NaCl crystals at 1000 K while using SPME, {\sc sf} ($\alpha$ = 0.0, 0.1, \& 0.2), and {\sc sp} ($\alpha$ = 0.2). The inset is a magnification of the first trough. The times to first collision are nearly identical, but the differences can be seen in the peaks and troughs, where the undamped to weakly damped methods are stiffer than the moderately damped and SPME methods.}
994 > \caption{Velocity auto-correlation functions of NaCl crystals at
995 > 1000 K while using SPME, {\sc sf} ($\alpha$ = 0.0, 0.1, \& 0.2), and
996 > {\sc sp} ($\alpha$ = 0.2). The inset is a magnification of the first
997 > trough. The times to first collision are nearly identical, but the
998 > differences can be seen in the peaks and troughs, where the undamped
999 > to weakly damped methods are stiffer than the moderately damped and
1000 > SPME methods.}
1001   \label{fig:vCorrPlot}
1002   \end{figure}
1003  
# Line 969 | Line 1032 | displayed in figure \ref{fig:methodPS}.
1032   \begin{figure}
1033   \centering
1034   \includegraphics[width = \linewidth]{./spectraSquare.pdf}
1035 < \caption{Power spectra obtained from the velocity auto-correlation functions of NaCl crystals at 1000 K while using SPME, {\sc sf} ($\alpha$ = 0, 0.1, \& 0.2), and {\sc sp} ($\alpha$ = 0.2).  Apodization of the correlation functions via a cubic switching function between 40 and 50 ps was used to clear up the spectral noise resulting from data truncation, and had no noticeable effect on peak location or magnitude.  The inset shows the frequency region below 100 cm$^{-1}$ to highlight where the spectra begin to differ.}
1035 > \caption{Power spectra obtained from the velocity auto-correlation
1036 > functions of NaCl crystals at 1000 K while using SPME, {\sc sf}
1037 > ($\alpha$ = 0, 0.1, \& 0.2), and {\sc sp} ($\alpha$ = 0.2).
1038 > Apodization of the correlation functions via a cubic switching
1039 > function between 40 and 50 ps was used to clear up the spectral noise
1040 > resulting from data truncation, and had no noticeable effect on peak
1041 > location or magnitude.  The inset shows the frequency region below 100
1042 > cm$^{-1}$ to highlight where the spectra begin to differ.}
1043   \label{fig:methodPS}
1044   \end{figure}
1045  
# Line 1011 | Line 1081 | accurate reproduction of crystal dynamics.
1081   \begin{figure}
1082   \centering
1083   \includegraphics[width = \linewidth]{./comboSquare.pdf}
1084 < \caption{Regions of spectra showing the low-frequency correlated motions for NaCl crystals at 1000 K using various electrostatic summation methods.  The upper plot is a zoomed inset from figure \ref{fig:methodPS}.  As the damping value for the {\sc sf} potential increases, the low-frequency peaks red-shift.  The lower plot is of spectra when using SPME and a simple damped Coulombic sum with damping coefficients ($\alpha$) ranging from 0.15 to 0.3 \AA$^{-1}$.  As $\alpha$ increases, the peaks are red-shifted toward and eventually beyond the values given by SPME.  The larger $\alpha$ values weaken the real-space electrostatics, explaining this shift towards less strongly correlated motions in the crystal.}
1084 > \caption{Regions of spectra showing the low-frequency correlated
1085 > motions for NaCl crystals at 1000 K using various electrostatic
1086 > summation methods.  The upper plot is a zoomed inset from figure
1087 > \ref{fig:methodPS}.  As the damping value for the {\sc sf} potential
1088 > increases, the low-frequency peaks red-shift.  The lower plot is of
1089 > spectra when using SPME and a simple damped Coulombic sum with damping
1090 > coefficients ($\alpha$) ranging from 0.15 to 0.3 \AA$^{-1}$.  As
1091 > $\alpha$ increases, the peaks are red-shifted toward and eventually
1092 > beyond the values given by SPME.  The larger $\alpha$ values weaken
1093 > the real-space electrostatics, explaining this shift towards less
1094 > strongly correlated motions in the crystal.}
1095   \label{fig:dampInc}
1096   \end{figure}
1097  

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