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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 $M$.  
577 > where $\hat{f}_\textrm{M}$ is the unit vector pointing along the force
578 > 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
581 > function and 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.}
588 > \caption{Sample fit of the angular distribution of the force vectors
589 > accumulated using all of the studied systems.  Gaussian fits were used
590 > to obtain values for the variance in force and torque vectors.}
591   \label{fig:gaussian}
592   \end{figure}
593  
# Line 597 | Line 604 | when using the reference method (SPME).
604   when using the reference method (SPME).
605  
606   \subsection{Short-time Dynamics}
607 < Evaluation of the short-time dynamics of charged systems was performed
608 < by considering the 1000 K NaCl crystal system while using a subset of the
609 < best performing pairwise methods.  The NaCl crystal was chosen to
610 < avoid possible complications involving the propagation techniques of
611 < orientational motion in molecular systems.  All systems were started
612 < with the same initial positions and velocities.  Simulations were
613 < performed under the microcanonical ensemble, and velocity
607 >
608 > The effects of the alternative electrostatic summation methods on the
609 > short-time dynamics of charged systems were evaluated by considering a
610 > NaCl crystal at a temperature of 1000 K.  A subset of the best
611 > performing pairwise methods was used in this comparison.  The NaCl
612 > crystal was chosen to avoid possible complications from the treatment
613 > of orientational motion in molecular systems.  All systems were
614 > started with the same initial positions and velocities.  Simulations
615 > were performed under the microcanonical ensemble, and velocity
616   autocorrelation functions (Eq. \ref{eq:vCorr}) were computed for each
617   of the trajectories,
618   \begin{equation}
# Line 617 | Line 626 | functions was used for comparisons.
626   functions was used for comparisons.
627  
628   \subsection{Long-Time and Collective Motion}\label{sec:LongTimeMethods}
629 < Evaluation of the long-time dynamics of charged systems was performed
630 < by considering the NaCl crystal system, again while using a subset of
631 < the best performing pairwise methods.  To enhance the atomic motion,
632 < these crystals were equilibrated at 1000 K, near the experimental
633 < $T_m$ for NaCl.  Simulations were performed under the microcanonical
634 < ensemble, and velocity information was saved every 5 fs over 100 ps
635 < 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,
629 >
630 > The effects of the same subset of alternative electrostatic methods on
631 > the {\it long-time} dynamics of charged systems were evaluated using
632 > the same model system (NaCl crystals at 1000K).  The power spectrum
633 > ($I(\omega)$) was obtained via Fourier transform of the velocity
634 > autocorrelation function, \begin{equation} I(\omega) =
635 > \frac{1}{2\pi}\int^{\infty}_{-\infty}C_v(t)e^{-i\omega t}dt,
636   \label{eq:powerSpec}
637   \end{equation}
638   where the frequency, $\omega=0,\ 1,\ ...,\ N-1$. Again, because the
639   NaCl crystal is composed of two different atom types, the average of
640 < the two resulting power spectra was used for comparisons.
640 > the two resulting power spectra was used for comparisons. Simulations
641 > were performed under the microcanonical ensemble, and velocity
642 > information was saved every 5 fs over 100 ps trajectories.
643  
644   \subsection{Representative Simulations}\label{sec:RepSims}
645 < A variety of common and representative simulations were analyzed to
646 < determine the relative effectiveness of the pairwise summation
647 < techniques in reproducing the energetics and dynamics exhibited by
648 < SPME.  The studied systems were as follows:
645 > A variety of representative simulations were analyzed to determine the
646 > relative effectiveness of the pairwise summation techniques in
647 > reproducing the energetics and dynamics exhibited by SPME.  We wanted
648 > to span the space of modern simulations (i.e. from liquids of neutral
649 > molecules to ionic crystals), so the systems studied were:
650   \begin{enumerate}
651 < \item Liquid Water
652 < \item Crystalline Water (Ice I$_\textrm{c}$)
653 < \item NaCl Crystal
654 < \item NaCl Melt
655 < \item Low Ionic Strength Solution of NaCl in Water
656 < \item High Ionic Strength Solution of NaCl in Water
657 < \item 6 \AA\  Radius Sphere of Argon in Water
651 > \item liquid water (SPC/E),\cite{Berendsen87}
652 > \item crystalline water (Ice I$_\textrm{c}$ crystals of SPC/E),
653 > \item NaCl crystals,
654 > \item NaCl melts,
655 > \item a low ionic strength solution of NaCl in water (0.11 M),
656 > \item a high ionic strength solution of NaCl in water (1.1 M), and
657 > \item a 6 \AA\  radius sphere of Argon in water.
658   \end{enumerate}
659   By utilizing the pairwise techniques (outlined in section
660   \ref{sec:ESMethods}) in systems composed entirely of neutral groups,
661 < charged particles, and mixtures of the two, we can comment on possible
662 < system dependence and/or universal applicability of the techniques.
661 > charged particles, and mixtures of the two, we hope to discern under
662 > which conditions it will be possible to use one of the alternative
663 > summation methodologies instead of the Ewald sum.
664  
665 < Generation of the system configurations was dependent on the system
666 < type.  For the solid and liquid water configurations, configuration
667 < snapshots were taken at regular intervals from higher temperature 1000
668 < SPC/E water molecule trajectories and each equilibrated
669 < individually.\cite{Berendsen87} The solid and liquid NaCl systems
670 < consisted of 500 Na+ and 500 Cl- ions and were selected and
671 < equilibrated in the same fashion as the water systems.  For the low
672 < and high ionic strength NaCl solutions, 4 and 40 ions were first
673 < solvated in a 1000 water molecule boxes respectively.  Ion and water
674 < positions were then randomly swapped, and the resulting configurations
675 < were again equilibrated individually.  Finally, for the Argon/Water
676 < "charge void" systems, the identities of all the SPC/E waters within 6
677 < \AA\ of the center of the equilibrated water configurations were
678 < converted to argon (Fig. \ref{fig:argonSlice}).
665 > For the solid and liquid water configurations, configurations were
666 > taken at regular intervals from high temperature trajectories of 1000
667 > SPC/E water molecules.  Each configuration was equilibrated
668 > independently at a lower temperature (300~K for the liquid, 200~K for
669 > the crystal).  The solid and liquid NaCl systems consisted of 500
670 > $\textrm{Na}^{+}$ and 500 $\textrm{Cl}^{-}$ ions.  Configurations for
671 > these systems were selected and equilibrated in the same manner as the
672 > water systems.  The equilibrated temperatures were 1000~K for the NaCl
673 > crystal and 7000~K for the liquid. The ionic solutions were made by
674 > solvating 4 (or 40) ions in a periodic box containing 1000 SPC/E water
675 > molecules.  Ion and water positions were then randomly swapped, and
676 > the resulting configurations were again equilibrated individually.
677 > Finally, for the Argon / Water ``charge void'' systems, the identities
678 > of all the SPC/E waters within 6 \AA\ of the center of the
679 > equilibrated water configurations were converted to argon
680 > (Fig. \ref{fig:argonSlice}).
681  
682 + These procedures guaranteed us a set of representative configurations
683 + from chemically-relevant systems sampled from an appropriate
684 + ensemble. Force field parameters for the ions and Argon were taken
685 + from the force field utilized by {\sc oopse}.\cite{Meineke05}
686 +
687   \begin{figure}
688   \centering
689   \includegraphics[width = \linewidth]{./slice.pdf}
690 < \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.}
690 > \caption{A slice from the center of a water box used in a charge void
691 > simulation.  The darkened region represents the boundary sphere within
692 > which the water molecules were converted to argon atoms.}
693   \label{fig:argonSlice}
694   \end{figure}
695  
696 < \subsection{Electrostatic Summation Methods}\label{sec:ESMethods}
697 < Electrostatic summation method comparisons were performed using SPME,
698 < the {\sc sp} and {\sc sf} methods - both with damping
699 < parameters ($\alpha$) of 0.0, 0.1, 0.2, and 0.3 \AA$^{-1}$ (no, weak,
700 < moderate, and strong damping respectively), reaction field with an
701 < infinite dielectric constant, and an unmodified cutoff.  Group-based
702 < cutoffs with a fifth-order polynomial switching function were
703 < necessary for the reaction field simulations and were utilized in the
704 < SP, SF, and pure cutoff methods for comparison to the standard lack of
705 < group-based cutoffs with a hard truncation.  The SPME calculations
706 < were performed using the TINKER implementation of SPME,\cite{Ponder87}
707 < while all other method calculations were performed using the OOPSE
708 < molecular mechanics package.\cite{Meineke05}
696 > \subsection{Comparison of Summation Methods}\label{sec:ESMethods}
697 > We compared the following alternative summation methods with results
698 > from the reference method (SPME):
699 > \begin{itemize}
700 > \item {\sc sp} with damping parameters ($\alpha$) of 0.0, 0.1, 0.2,
701 > and 0.3 \AA$^{-1}$,
702 > \item {\sc sf} with damping parameters ($\alpha$) of 0.0, 0.1, 0.2,
703 > and 0.3 \AA$^{-1}$,
704 > \item reaction field with an infinite dielectric constant, and
705 > \item an unmodified cutoff.
706 > \end{itemize}
707 > Group-based cutoffs with a fifth-order polynomial switching function
708 > were utilized for the reaction field simulations.  Additionally, we
709 > investigated the use of these cutoffs with the SP, SF, and pure
710 > cutoff.  The SPME electrostatics were performed using the TINKER
711 > implementation of SPME,\cite{Ponder87} while all other method
712 > calculations were performed using the OOPSE molecular mechanics
713 > package.\cite{Meineke05} All other portions of the energy calculation
714 > (i.e. Lennard-Jones interactions) were handled in exactly the same
715 > manner across all systems and configurations.
716  
717 < These methods were additionally evaluated with three different cutoff
718 < radii (9, 12, and 15 \AA) to investigate possible cutoff radius
719 < dependence.  It should be noted that the damping parameter chosen in
720 < SPME, or so called ``Ewald Coefficient", has a significant effect on
721 < the energies and forces calculated.  Typical molecular mechanics
722 < packages default this to a value dependent on the cutoff radius and a
723 < tolerance (typically less than $1 \times 10^{-4}$ kcal/mol).  Smaller
724 < tolerances are typically associated with increased accuracy, but this
725 < usually means more time spent calculating the reciprocal-space portion
726 < of the summation.\cite{Perram88,Essmann95} The default TINKER
727 < tolerance of $1 \times 10^{-8}$ kcal/mol was used in all SPME
728 < calculations, resulting in Ewald Coefficients of 0.4200, 0.3119, and
729 < 0.2476 \AA$^{-1}$ for cutoff radii of 9, 12, and 15 \AA\ respectively.
717 > The althernative methods were also evaluated with three different
718 > cutoff radii (9, 12, and 15 \AA).  As noted previously, the
719 > convergence parameter ($\alpha$) plays a role in the balance of the
720 > real-space and reciprocal-space portions of the Ewald calculation.
721 > Typical molecular mechanics packages set this to a value dependent on
722 > the cutoff radius and a tolerance (typically less than $1 \times
723 > 10^{-4}$ kcal/mol).  Smaller tolerances are typically associated with
724 > increased accuracy at the expense of increased time spent calculating
725 > the reciprocal-space portion of the
726 > summation.\cite{Perram88,Essmann95} The default TINKER tolerance of $1
727 > \times 10^{-8}$ kcal/mol was used in all SPME calculations, resulting
728 > in Ewald Coefficients of 0.4200, 0.3119, and 0.2476 \AA$^{-1}$ for
729 > cutoff radii of 9, 12, and 15 \AA\ respectively.
730  
731   \section{Results and Discussion}
732  
# Line 714 | Line 740 | figure \ref{fig:delE}.
740   \begin{figure}
741   \centering
742   \includegraphics[width=5.5in]{./delEplot.pdf}
743 < \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).}
743 > \caption{Statistical analysis of the quality of configurational energy
744 > differences for a given electrostatic method compared with the
745 > reference Ewald sum.  Results with a value equal to 1 (dashed line)
746 > indicate $\Delta E$ values indistinguishable from those obtained using
747 > SPME.  Different values of the cutoff radius are indicated with
748 > different symbols (9\AA\ = circles, 12\AA\ = squares, and 15\AA\ =
749 > inverted triangles).}
750   \label{fig:delE}
751   \end{figure}
752  
753 < In this figure, it is apparent that it is unreasonable to expect
754 < realistic results using an unmodified cutoff.  This is not all that
755 < surprising since this results in large energy fluctuations as atoms or
756 < molecules move in and out of the cutoff radius.\cite{Rahman71,Adams79}
757 < These fluctuations can be alleviated to some degree by using group
758 < based cutoffs with a switching
727 < function.\cite{Adams79,Steinbach94,Leach01} The Group Switch Cutoff
728 < row doesn't show a significant improvement in this plot because the
729 < salt and salt solution systems contain non-neutral groups, see the
730 < accompanying supporting information for a comparison where all groups
731 < are neutral.
753 > The most striking feature of this plot is how well the Shifted Force
754 > ({\sc sf}) and Shifted Potential ({\sc sp}) methods capture the energy
755 > differences.  For the undamped {\sc sf} method, and the
756 > moderately-damped {\sc sp} methods, the results are nearly
757 > indistinguishable from the Ewald results.  The other common methods do
758 > significantly less well.  
759  
760 < Correcting the resulting charged cutoff sphere is one of the purposes
761 < of the damped Coulomb summation proposed by Wolf \textit{et
762 < al.},\cite{Wolf99} and this correction indeed improves the results as
763 < seen in the {\sc sp} rows.  While the undamped case of this
764 < method is a significant improvement over the pure cutoff, it still
765 < doesn't correlate that well with SPME.  Inclusion of potential damping
766 < improves the results, and using an $\alpha$ of 0.2 \AA $^{-1}$ shows
760 > The unmodified cutoff method is essentially unusable.  This is not
761 > surprising since hard cutoffs give large energy fluctuations as atoms
762 > or molecules move in and out of the cutoff
763 > radius.\cite{Rahman71,Adams79} These fluctuations can be alleviated to
764 > some degree by using group based cutoffs with a switching
765 > function.\cite{Adams79,Steinbach94,Leach01} However, we do not see
766 > significant improvement using the group-switched cutoff because the
767 > salt and salt solution systems contain non-neutral groups.  Interested
768 > readers can consult the accompanying supporting information for a
769 > comparison where all groups are neutral.
770 >
771 > For the {\sc sp} method, inclusion of potential damping improves the
772 > agreement with Ewald, and using an $\alpha$ of 0.2 \AA $^{-1}$ shows
773   an excellent correlation and quality of fit with the SPME results,
774 < particularly with a cutoff radius greater than 12 \AA .  Use of a
775 < larger damping parameter is more helpful for the shortest cutoff
776 < shown, but it has a detrimental effect on simulations with larger
777 < 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.
774 > particularly with a cutoff radius greater than 12
775 > \AA .  Use of a larger damping parameter is more helpful for the
776 > shortest cutoff shown, but it has a detrimental effect on simulations
777 > with larger cutoffs.  
778  
779 + In the {\sc sf} sets, increasing damping results in progressively
780 + worse correlation with Ewald.  Overall, the undamped case is the best
781 + performing set, as the correlation and quality of fits are
782 + consistently superior regardless of the cutoff distance.  The undamped
783 + case is also less computationally demanding (because no evaluation of
784 + the complementary error function is required).
785 +
786 + The reaction field results illustrates some of that method's
787 + limitations, primarily that it was developed for use in homogenous
788 + systems; although it does provide results that are an improvement over
789 + those from an unmodified cutoff.
790 +
791   \subsection{Magnitudes of the Force and Torque Vectors}
792  
793   Evaluation of pairwise methods for use in Molecular Dynamics

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