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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
581 < function, weighted by the area on the unit sphere.  Non-linear
582 < Gaussian fits were used to measure the width of the resulting
583 < distributions.
584 <
585 < \begin{figure}
586 < \centering
587 < \includegraphics[width = \linewidth]{./gaussFit.pdf}
588 < \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.}
589 < \label{fig:gaussian}
590 < \end{figure}
591 <
592 < Figure \ref{fig:gaussian} shows an example distribution with applied
593 < non-linear fits.  The solid line is a Gaussian profile, while the
594 < dotted line is a Voigt profile, a convolution of a Gaussian and a
595 < Lorentzian.  Since this distribution is a measure of angular error
596 < between two different electrostatic summation methods, there is no
597 < {\it a priori} reason for the profile to adhere to any specific shape.
598 < Gaussian fits was used to compare all the tested methods.  The
599 < variance ($\sigma^2$) was extracted from each of these fits and was
600 < used to compare distribution widths.  Values of $\sigma^2$ near zero
601 < indicate vector directions indistinguishable from those calculated
602 < when using the reference method (SPME).
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.  Non-linear Gaussian fits were used to measure the width
581 > of the resulting distributions.
582 > %
583 > %\begin{figure}
584 > %\centering
585 > %\includegraphics[width = \linewidth]{./gaussFit.pdf}
586 > %\caption{Sample fit of the angular distribution of the force vectors
587 > %accumulated using all of the studied systems.  Gaussian fits were used
588 > %to obtain values for the variance in force and torque vectors.}
589 > %\label{fig:gaussian}
590 > %\end{figure}
591 > %
592 > %Figure \ref{fig:gaussian} shows an example distribution with applied
593 > %non-linear fits.  The solid line is a Gaussian profile, while the
594 > %dotted line is a Voigt profile, a convolution of a Gaussian and a
595 > %Lorentzian.  
596 > %Since this distribution is a measure of angular error between two
597 > %different electrostatic summation methods, there is no {\it a priori}
598 > %reason for the profile to adhere to any specific shape.
599 > %Gaussian fits was used to compare all the tested methods.  
600 > The variance ($\sigma^2$) was extracted from each of these fits and
601 > was used to compare distribution widths.  Values of $\sigma^2$ near
602 > zero indicate vector directions indistinguishable from those
603 > calculated when using the reference method (SPME).
604  
605   \subsection{Short-time Dynamics}
606 < Evaluation of the short-time dynamics of charged systems was performed
607 < by considering the 1000 K NaCl crystal system while using a subset of the
608 < best performing pairwise methods.  The NaCl crystal was chosen to
609 < avoid possible complications involving the propagation techniques of
610 < orientational motion in molecular systems.  All systems were started
611 < with the same initial positions and velocities.  Simulations were
612 < performed under the microcanonical ensemble, and velocity
606 >
607 > The effects of the alternative electrostatic summation methods on the
608 > short-time dynamics of charged systems were evaluated by considering a
609 > NaCl crystal at a temperature of 1000 K.  A subset of the best
610 > performing pairwise methods was used in this comparison.  The NaCl
611 > crystal was chosen to avoid possible complications from the treatment
612 > of orientational motion in molecular systems.  All systems were
613 > started with the same initial positions and velocities.  Simulations
614 > were performed under the microcanonical ensemble, and velocity
615   autocorrelation functions (Eq. \ref{eq:vCorr}) were computed for each
616   of the trajectories,
617   \begin{equation}
# Line 617 | Line 625 | functions was used for comparisons.
625   functions was used for comparisons.
626  
627   \subsection{Long-Time and Collective Motion}\label{sec:LongTimeMethods}
628 < Evaluation of the long-time dynamics of charged systems was performed
629 < by considering the NaCl crystal system, again while using a subset of
630 < the best performing pairwise methods.  To enhance the atomic motion,
631 < these crystals were equilibrated at 1000 K, near the experimental
632 < $T_m$ for NaCl.  Simulations were performed under the microcanonical
633 < ensemble, and velocity information was saved every 5 fs over 100 ps
634 < 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,
628 >
629 > The effects of the same subset of alternative electrostatic methods on
630 > the {\it long-time} dynamics of charged systems were evaluated using
631 > the same model system (NaCl crystals at 1000K).  The power spectrum
632 > ($I(\omega)$) was obtained via Fourier transform of the velocity
633 > autocorrelation function, \begin{equation} I(\omega) =
634 > \frac{1}{2\pi}\int^{\infty}_{-\infty}C_v(t)e^{-i\omega t}dt,
635   \label{eq:powerSpec}
636   \end{equation}
637   where the frequency, $\omega=0,\ 1,\ ...,\ N-1$. Again, because the
638   NaCl crystal is composed of two different atom types, the average of
639 < the two resulting power spectra was used for comparisons.
639 > the two resulting power spectra was used for comparisons. Simulations
640 > were performed under the microcanonical ensemble, and velocity
641 > information was saved every 5 fs over 100 ps trajectories.
642  
643   \subsection{Representative Simulations}\label{sec:RepSims}
644 < A variety of common and representative simulations were analyzed to
645 < determine the relative effectiveness of the pairwise summation
646 < techniques in reproducing the energetics and dynamics exhibited by
647 < SPME.  The studied systems were as follows:
644 > A variety of representative simulations were analyzed to determine the
645 > relative effectiveness of the pairwise summation techniques in
646 > reproducing the energetics and dynamics exhibited by SPME.  We wanted
647 > to span the space of modern simulations (i.e. from liquids of neutral
648 > molecules to ionic crystals), so the systems studied were:
649   \begin{enumerate}
650 < \item Liquid Water
651 < \item Crystalline Water (Ice I$_\textrm{c}$)
652 < \item NaCl Crystal
653 < \item NaCl Melt
654 < \item Low Ionic Strength Solution of NaCl in Water
655 < \item High Ionic Strength Solution of NaCl in Water
656 < \item 6 \AA\  Radius Sphere of Argon in Water
650 > \item liquid water (SPC/E),\cite{Berendsen87}
651 > \item crystalline water (Ice I$_\textrm{c}$ crystals of SPC/E),
652 > \item NaCl crystals,
653 > \item NaCl melts,
654 > \item a low ionic strength solution of NaCl in water (0.11 M),
655 > \item a high ionic strength solution of NaCl in water (1.1 M), and
656 > \item a 6 \AA\  radius sphere of Argon in water.
657   \end{enumerate}
658   By utilizing the pairwise techniques (outlined in section
659   \ref{sec:ESMethods}) in systems composed entirely of neutral groups,
660 < charged particles, and mixtures of the two, we can comment on possible
661 < system dependence and/or universal applicability of the techniques.
660 > charged particles, and mixtures of the two, we hope to discern under
661 > which conditions it will be possible to use one of the alternative
662 > summation methodologies instead of the Ewald sum.
663  
664 < Generation of the system configurations was dependent on the system
665 < type.  For the solid and liquid water configurations, configuration
666 < snapshots were taken at regular intervals from higher temperature 1000
667 < SPC/E water molecule trajectories and each equilibrated
668 < individually.\cite{Berendsen87} The solid and liquid NaCl systems
669 < consisted of 500 Na+ and 500 Cl- ions and were selected and
670 < equilibrated in the same fashion as the water systems.  For the low
671 < and high ionic strength NaCl solutions, 4 and 40 ions were first
672 < solvated in a 1000 water molecule boxes respectively.  Ion and water
673 < positions were then randomly swapped, and the resulting configurations
674 < were again equilibrated individually.  Finally, for the Argon/Water
675 < "charge void" systems, the identities of all the SPC/E waters within 6
676 < \AA\ of the center of the equilibrated water configurations were
677 < converted to argon (Fig. \ref{fig:argonSlice}).
678 <
679 < \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}
664 > For the solid and liquid water configurations, configurations were
665 > taken at regular intervals from high temperature trajectories of 1000
666 > SPC/E water molecules.  Each configuration was equilibrated
667 > independently at a lower temperature (300~K for the liquid, 200~K for
668 > the crystal).  The solid and liquid NaCl systems consisted of 500
669 > $\textrm{Na}^{+}$ and 500 $\textrm{Cl}^{-}$ ions.  Configurations for
670 > these systems were selected and equilibrated in the same manner as the
671 > water systems.  The equilibrated temperatures were 1000~K for the NaCl
672 > crystal and 7000~K for the liquid. The ionic solutions were made by
673 > solvating 4 (or 40) ions in a periodic box containing 1000 SPC/E water
674 > molecules.  Ion and water positions were then randomly swapped, and
675 > the resulting configurations were again equilibrated individually.
676 > Finally, for the Argon / Water ``charge void'' systems, the identities
677 > of all the SPC/E waters within 6 \AA\ of the center of the
678 > equilibrated water configurations were converted to argon.
679 > %(Fig. \ref{fig:argonSlice}).
680  
681 < \subsection{Electrostatic Summation Methods}\label{sec:ESMethods}
682 < Electrostatic summation method comparisons were performed using SPME,
683 < the {\sc sp} and {\sc sf} methods - both with damping
684 < 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}
681 > These procedures guaranteed us a set of representative configurations
682 > from chemically-relevant systems sampled from an appropriate
683 > ensemble. Force field parameters for the ions and Argon were taken
684 > from the force field utilized by {\sc oopse}.\cite{Meineke05}
685  
686 < These methods were additionally evaluated with three different cutoff
687 < radii (9, 12, and 15 \AA) to investigate possible cutoff radius
688 < dependence.  It should be noted that the damping parameter chosen in
689 < SPME, or so called ``Ewald Coefficient", has a significant effect on
690 < the energies and forces calculated.  Typical molecular mechanics
691 < packages default this to a value dependent on the cutoff radius and a
692 < tolerance (typically less than $1 \times 10^{-4}$ kcal/mol).  Smaller
693 < 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.
686 > %\begin{figure}
687 > %\centering
688 > %\includegraphics[width = \linewidth]{./slice.pdf}
689 > %\caption{A slice from the center of a water box used in a charge void
690 > %simulation.  The darkened region represents the boundary sphere within
691 > %which the water molecules were converted to argon atoms.}
692 > %\label{fig:argonSlice}
693 > %\end{figure}
694  
695 + \subsection{Comparison of Summation Methods}\label{sec:ESMethods}
696 + We compared the following alternative summation methods with results
697 + from the reference method (SPME):
698 + \begin{itemize}
699 + \item {\sc sp} with damping parameters ($\alpha$) of 0.0, 0.1, 0.2,
700 + and 0.3 \AA$^{-1}$,
701 + \item {\sc sf} with damping parameters ($\alpha$) of 0.0, 0.1, 0.2,
702 + and 0.3 \AA$^{-1}$,
703 + \item reaction field with an infinite dielectric constant, and
704 + \item an unmodified cutoff.
705 + \end{itemize}
706 + Group-based cutoffs with a fifth-order polynomial switching function
707 + were utilized for the reaction field simulations.  Additionally, we
708 + investigated the use of these cutoffs with the SP, SF, and pure
709 + cutoff.  The SPME electrostatics were performed using the TINKER
710 + implementation of SPME,\cite{Ponder87} while all other method
711 + calculations were performed using the OOPSE molecular mechanics
712 + package.\cite{Meineke05} All other portions of the energy calculation
713 + (i.e. Lennard-Jones interactions) were handled in exactly the same
714 + manner across all systems and configurations.
715 +
716 + The althernative methods were also evaluated with three different
717 + cutoff radii (9, 12, and 15 \AA).  As noted previously, the
718 + convergence parameter ($\alpha$) plays a role in the balance of the
719 + real-space and reciprocal-space portions of the Ewald calculation.
720 + Typical molecular mechanics packages set this to a value dependent on
721 + the cutoff radius and a tolerance (typically less than $1 \times
722 + 10^{-4}$ kcal/mol).  Smaller tolerances are typically associated with
723 + increased accuracy at the expense of increased time spent calculating
724 + the reciprocal-space portion of the
725 + summation.\cite{Perram88,Essmann95} The default TINKER tolerance of $1
726 + \times 10^{-8}$ kcal/mol was used in all SPME calculations, resulting
727 + in Ewald Coefficients of 0.4200, 0.3119, and 0.2476 \AA$^{-1}$ for
728 + cutoff radii of 9, 12, and 15 \AA\ respectively.
729 +
730   \section{Results and Discussion}
731  
732   \subsection{Configuration Energy Differences}\label{sec:EnergyResults}
# Line 714 | Line 739 | figure \ref{fig:delE}.
739   \begin{figure}
740   \centering
741   \includegraphics[width=5.5in]{./delEplot.pdf}
742 < \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).}
742 > \caption{Statistical analysis of the quality of configurational energy
743 > differences for a given electrostatic method compared with the
744 > reference Ewald sum.  Results with a value equal to 1 (dashed line)
745 > indicate $\Delta E$ values indistinguishable from those obtained using
746 > SPME.  Different values of the cutoff radius are indicated with
747 > different symbols (9\AA\ = circles, 12\AA\ = squares, and 15\AA\ =
748 > inverted triangles).}
749   \label{fig:delE}
750   \end{figure}
751  
752 < In this figure, it is apparent that it is unreasonable to expect
753 < realistic results using an unmodified cutoff.  This is not all that
754 < surprising since this results in large energy fluctuations as atoms or
755 < molecules move in and out of the cutoff radius.\cite{Rahman71,Adams79}
756 < These fluctuations can be alleviated to some degree by using group
757 < based cutoffs with a switching
758 < function.\cite{Adams79,Steinbach94,Leach01} The Group Switch Cutoff
759 < row doesn't show a significant improvement in this plot because the
760 < salt and salt solution systems contain non-neutral groups, see the
761 < accompanying supporting information for a comparison where all groups
762 < are neutral.
763 <
764 < Correcting the resulting charged cutoff sphere is one of the purposes
765 < of the damped Coulomb summation proposed by Wolf \textit{et
766 < al.},\cite{Wolf99} and this correction indeed improves the results as
767 < seen in the {\sc sp} rows.  While the undamped case of this
768 < method is a significant improvement over the pure cutoff, it still
769 < doesn't correlate that well with SPME.  Inclusion of potential damping
770 < improves the results, and using an $\alpha$ of 0.2 \AA $^{-1}$ shows
752 > The most striking feature of this plot is how well the Shifted Force
753 > ({\sc sf}) and Shifted Potential ({\sc sp}) methods capture the energy
754 > differences.  For the undamped {\sc sf} method, and the
755 > moderately-damped {\sc sp} methods, the results are nearly
756 > indistinguishable from the Ewald results.  The other common methods do
757 > significantly less well.  
758 >
759 > The unmodified cutoff method is essentially unusable.  This is not
760 > surprising since hard cutoffs give large energy fluctuations as atoms
761 > or molecules move in and out of the cutoff
762 > radius.\cite{Rahman71,Adams79} These fluctuations can be alleviated to
763 > some degree by using group based cutoffs with a switching
764 > function.\cite{Adams79,Steinbach94,Leach01} However, we do not see
765 > significant improvement using the group-switched cutoff because the
766 > salt and salt solution systems contain non-neutral groups.  Interested
767 > readers can consult the accompanying supporting information for a
768 > comparison where all groups are neutral.
769 >
770 > For the {\sc sp} method, inclusion of potential damping improves the
771 > agreement with Ewald, and using an $\alpha$ of 0.2 \AA $^{-1}$ shows
772   an excellent correlation and quality of fit with the SPME results,
773 < particularly with a cutoff radius greater than 12 \AA .  Use of a
774 < larger damping parameter is more helpful for the shortest cutoff
775 < shown, but it has a detrimental effect on simulations with larger
776 < 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.
773 > particularly with a cutoff radius greater than 12
774 > \AA .  Use of a larger damping parameter is more helpful for the
775 > shortest cutoff shown, but it has a detrimental effect on simulations
776 > with larger cutoffs.  
777  
778 + In the {\sc sf} sets, increasing damping results in progressively
779 + worse correlation with Ewald.  Overall, the undamped case is the best
780 + performing set, as the correlation and quality of fits are
781 + consistently superior regardless of the cutoff distance.  The undamped
782 + case is also less computationally demanding (because no evaluation of
783 + the complementary error function is required).
784 +
785 + The reaction field results illustrates some of that method's
786 + limitations, primarily that it was developed for use in homogenous
787 + systems; although it does provide results that are an improvement over
788 + those from an unmodified cutoff.
789 +
790   \subsection{Magnitudes of the Force and Torque Vectors}
791  
792   Evaluation of pairwise methods for use in Molecular Dynamics
# Line 766 | Line 800 | accumulated analysis over all the system types.
800   \begin{figure}
801   \centering
802   \includegraphics[width=5.5in]{./frcMagplot.pdf}
803 < \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).}
803 > \caption{Statistical analysis of the quality of the force vector
804 > magnitudes for a given electrostatic method compared with the
805 > reference Ewald sum.  Results with a value equal to 1 (dashed line)
806 > indicate force magnitude values indistinguishable from those obtained
807 > using SPME.  Different values of the cutoff radius are indicated with
808 > different symbols (9\AA\ = circles, 12\AA\ = squares, and 15\AA\ =
809 > inverted triangles).}
810   \label{fig:frcMag}
811   \end{figure}
812  
# Line 792 | Line 832 | performs more favorably.
832   \begin{figure}
833   \centering
834   \includegraphics[width=5.5in]{./trqMagplot.pdf}
835 < \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).}
835 > \caption{Statistical analysis of the quality of the torque vector
836 > magnitudes for a given electrostatic method compared with the
837 > reference Ewald sum.  Results with a value equal to 1 (dashed line)
838 > indicate torque magnitude values indistinguishable from those obtained
839 > using SPME.  Different values of the cutoff radius are indicated with
840 > different symbols (9\AA\ = circles, 12\AA\ = squares, and 15\AA\ =
841 > inverted triangles).}
842   \label{fig:trqMag}
843   \end{figure}
844  
# Line 822 | Line 868 | error distributions of the combined set over all syste
868   \begin{figure}
869   \centering
870   \includegraphics[width=5.5in]{./frcTrqAngplot.pdf}
871 < \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).}
871 > \caption{Statistical analysis of the quality of the Gaussian fit of
872 > the force and torque vector angular distributions for a given
873 > electrostatic method compared with the reference Ewald sum.  Results
874 > with a variance ($\sigma^2$) equal to zero (dashed line) indicate
875 > force and torque directions indistinguishable from those obtained
876 > using SPME.  Different values of the cutoff radius are indicated with
877 > different symbols (9\AA\ = circles, 12\AA\ = squares, and 15\AA\ =
878 > inverted triangles).}
879   \label{fig:frcTrqAng}
880   \end{figure}
881  
# Line 846 | Line 899 | investigated further in the accompanying supporting in
899  
900   \begin{table}[htbp]
901     \centering
902 <   \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$^2$.}  
902 >   \caption{Variance ($\sigma^2$) of the force (top set) and torque
903 > (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$^2$.}      
904     \begin{tabular}{@{} ccrrrrrrrr @{}}
905        \\
906        \toprule
# Line 934 | Line 988 | summation methods from the above results.
988   \begin{figure}
989   \centering
990   \includegraphics[width = \linewidth]{./vCorrPlot.pdf}
991 < \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.}
991 > \caption{Velocity auto-correlation functions of NaCl crystals at
992 > 1000 K while using SPME, {\sc sf} ($\alpha$ = 0.0, 0.1, \& 0.2), and
993 > {\sc sp} ($\alpha$ = 0.2). The inset is a magnification of the first
994 > trough. The times to first collision are nearly identical, but the
995 > differences can be seen in the peaks and troughs, where the undamped
996 > to weakly damped methods are stiffer than the moderately damped and
997 > SPME methods.}
998   \label{fig:vCorrPlot}
999   \end{figure}
1000  
# Line 969 | Line 1029 | displayed in figure \ref{fig:methodPS}.
1029   \begin{figure}
1030   \centering
1031   \includegraphics[width = \linewidth]{./spectraSquare.pdf}
1032 < \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.}
1032 > \caption{Power spectra obtained from the velocity auto-correlation
1033 > functions of NaCl crystals at 1000 K while using SPME, {\sc sf}
1034 > ($\alpha$ = 0, 0.1, \& 0.2), and {\sc sp} ($\alpha$ = 0.2).
1035 > Apodization of the correlation functions via a cubic switching
1036 > function between 40 and 50 ps was used to clear up the spectral noise
1037 > resulting from data truncation, and had no noticeable effect on peak
1038 > location or magnitude.  The inset shows the frequency region below 100
1039 > cm$^{-1}$ to highlight where the spectra begin to differ.}
1040   \label{fig:methodPS}
1041   \end{figure}
1042  
# Line 1011 | Line 1078 | accurate reproduction of crystal dynamics.
1078   \begin{figure}
1079   \centering
1080   \includegraphics[width = \linewidth]{./comboSquare.pdf}
1081 < \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.}
1081 > \caption{Regions of spectra showing the low-frequency correlated
1082 > motions for NaCl crystals at 1000 K using various electrostatic
1083 > summation methods.  The upper plot is a zoomed inset from figure
1084 > \ref{fig:methodPS}.  As the damping value for the {\sc sf} potential
1085 > increases, the low-frequency peaks red-shift.  The lower plot is of
1086 > spectra when using SPME and a simple damped Coulombic sum with damping
1087 > coefficients ($\alpha$) ranging from 0.15 to 0.3 \AA$^{-1}$.  As
1088 > $\alpha$ increases, the peaks are red-shifted toward and eventually
1089 > beyond the values given by SPME.  The larger $\alpha$ values weaken
1090 > the real-space electrostatics, explaining this shift towards less
1091 > strongly correlated motions in the crystal.}
1092   \label{fig:dampInc}
1093   \end{figure}
1094  

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