--- trunk/ssdePaper/nptSSD.tex	2003/09/10 22:42:57	759
+++ trunk/ssdePaper/nptSSD.tex	2003/09/19 19:29:24	777
@@ -146,9 +146,9 @@ water.\cite{Ichiye96} In the original molecular dynami
 simulations using this model, Ichiye \emph{et al.} reported a
 calculation speed up of up to an order of magnitude over other
 comparable models while maintaining the structural behavior of
-water.\cite{Ichiye96} In the original molecular dynamics studies of
-SSD, it was shown that it actually improves upon the prediction of
-water's dynamical properties 3 and 4-point models.\cite{Ichiye99} This
+water.\cite{Ichiye96} In the original molecular dynamics studies, it
+was shown that SSD improves on the prediction of many of water's
+dynamical properties over TIP3P and SPC/E.\cite{Ichiye99} This
 attractive combination of speed and accurate depiction of solvent
 properties makes SSD a model of interest for the simulation of large
 scale biological systems, such as membrane phase behavior, a specific
@@ -205,14 +205,14 @@ SSD more compatible with a reaction field.
 to the use of reaction field, simulations were also performed without
 a surrounding dielectric and suggestions are proposed on how to make
 SSD more compatible with a reaction field.
- 
+
 Simulations were performed in both the isobaric-isothermal and
 microcanonical ensembles. The constant pressure simulations were
 implemented using an integral thermostat and barostat as outlined by
-Hoover.\cite{Hoover85,Hoover86} For the constant pressure
-simulations, the \emph{Q} parameter for the was set to 5.0 amu
-\(\cdot\)\AA\(^{2}\), and the relaxation time (\(\tau\))\ was set at
-100 ps.
+Hoover.\cite{Hoover85,Hoover86} All particles were treated as
+non-linear rigid bodies. Vibrational constraints are not necessary in
+simulations of SSD, because there are no explicit hydrogen atoms, and
+thus no molecular vibrational modes need to be considered.
 
 Integration of the equations of motion was carried out using the
 symplectic splitting method proposed by Dullweber \emph{et
@@ -220,11 +220,11 @@ requirement that is actually quite sensitive to errors
 deals with poor energy conservation of rigid body systems using
 quaternions. While quaternions work well for orientational motion in
 alternate ensembles, the microcanonical ensemble has a constant energy
-requirement that is actually quite sensitive to errors in the
-equations of motion. The original implementation of this code utilized
-quaternions for rotational motion propagation; however, a detailed
-investigation showed that they resulted in a steady drift in the total
-energy, something that has been observed by others.\cite{Laird97}
+requirement that is quite sensitive to errors in the equations of
+motion. The original implementation of this code utilized quaternions
+for rotational motion propagation; however, a detailed investigation
+showed that they resulted in a steady drift in the total energy,
+something that has been observed by others.\cite{Laird97}
 
 The key difference in the integration method proposed by Dullweber
 \emph{et al.} is that the entire rotation matrix is propagated from
@@ -244,11 +244,12 @@ simpler arithmetic quaternion propagation. On average,
 method, the orientational propagation involves a sequence of matrix
 evaluations to update the rotation matrix.\cite{Dullweber1997} These
 matrix rotations end up being more costly computationally than the
-simpler arithmetic quaternion propagation. On average, a 1000 SSD
-particle simulation shows a 7\% increase in computation time using the
-symplectic step method in place of quaternions. This cost is more than
-justified when comparing the energy conservation of the two methods as
-illustrated in figure \ref{timestep}. 
+simpler arithmetic quaternion propagation. With the same time step, a
+1000 SSD particle simulation shows an average 7\% increase in
+computation time using the symplectic step method in place of
+quaternions. This cost is more than justified when comparing the
+energy conservation of the two methods as illustrated in figure
+\ref{timestep}.
 
 \begin{figure}
 \includegraphics[width=61mm, angle=-90]{timeStep.epsi}
@@ -316,16 +317,9 @@ volume fluctuations dampened out in all but the very c
 increment was decreased from 25 K to 10 and then 5 K. The above
 equilibration and production times were sufficient in that the system
 volume fluctuations dampened out in all but the very cold simulations
-(below 225 K). In order to further improve statistics, five separate
-simulation progressions were performed, and the averaged results from
-the $I_h$ melting simulations are shown in figure \ref{dense1}.
-
-\begin{figure}
-\includegraphics[width=65mm, angle=-90]{1hdense.epsi}
-\caption{Average density of SSD water at increasing temperatures 
-starting from ice $I_h$ lattice.}
-\label{dense1}
-\end{figure}
+(below 225 K). In order to further improve statistics, an ensemble
+average was accumulated from five separate simulation progressions,
+each starting from a different ice crystal.
 
 \subsection{Density Behavior}
 In the initial average density versus temperature plot, the density
@@ -902,10 +896,10 @@ The authors would like to thank the National Science F
 simulations of biochemical systems.
 
 \section{Acknowledgments}
-The authors would like to thank the National Science Foundation for
-funding under grant CHE-0134881. Computation time was provided by the
-Notre Dame Bunch-of-Boxes (B.o.B) computer cluster under NSF grant DMR
-00 79647.
+Support for this project was provided by the National Science
+Foundation under grant CHE-0134881. Computation time was provided by
+the Notre Dame Bunch-of-Boxes (B.o.B) computer cluster under NSF grant
+DMR 00 79647.
 
 \bibliographystyle{jcp}
 
