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# Line 18 | Line 18 | In this chapter, I present and detail the capabilities
18   \section{\label{oopseSec:foreword}Foreword}
19  
20   In this chapter, I present and detail the capabilities of the open
21 < source simulation package {\sc oopse}. It is important to note, that a
22 < simulation package of this size and scope would not have been possible
21 > source simulation program {\sc oopse}. It is important to note that a
22 > simulation program of this size and scope would not have been possible
23   without the collaborative efforts of my colleagues: Charles
24   F.~Vardeman II, Teng Lin, Christopher J.~Fennell and J.~Daniel
25   Gezelter. Although my contributions to {\sc oopse} are major,
26   consideration of my work apart from the others would not give a
27 < complete description to the package's capabilities. As such, all
27 > complete description to the program's capabilities. As such, all
28   contributions to {\sc oopse} to date are presented in this chapter.
29  
30   Charles Vardeman is responsible for the parallelization of the long
# Line 70 | Line 70 | researchers try to develop techniques or energetic mod
70  
71   Despite their utility, problems with these packages arise when
72   researchers try to develop techniques or energetic models that the
73 < code was not originally designed to simulate. Examples of uncommonly
74 < implemented techniques and energetics include; dipole-dipole
75 < interactions, rigid body dynamics, and metallic embedded
76 < potentials. When faced with these obstacles, a researcher must either
77 < develop their own code or license and extend one of the commercial
78 < packages. What we have elected to do, is develop a package of
79 < simulation code capable of implementing the types of models upon which
80 < our research is based.
73 > code was not originally designed to simulate. Examples of techniques
74 > and energetics not commonly implemented include; dipole-dipole
75 > interactions, rigid body dynamics, and metallic potentials. When faced
76 > with these obstacles, a researcher must either develop their own code
77 > or license and extend one of the commercial packages. What we have
78 > elected to do is develop a body of simulation code capable of
79 > implementing the types of models upon which our research is based.
80  
81   In developing {\sc oopse}, we have adhered to the precepts of Open
82   Source development, and are releasing our source code with a
# Line 173 | Line 172 | maintained for each rigid body. At a minimum, the rota
172   each rigid body. In order to move between the space fixed and body
173   fixed coordinate axes, parameters describing the orientation must be
174   maintained for each rigid body. At a minimum, the rotation matrix
175 < (\textbf{A}) can be described by the three Euler angles ($\phi,
176 < \theta,$ and $\psi$), where the elements of \textbf{A} are composed of
175 > ($\mathsf{A}$) can be described by the three Euler angles ($\phi,
176 > \theta,$ and $\psi$), where the elements of $\mathsf{A}$ are composed of
177   trigonometric operations involving $\phi, \theta,$ and
178   $\psi$.\cite{Goldstein01} In order to avoid numerical instabilities
179   inherent in using the Euler angles, the four parameter ``quaternion''
180 < scheme is often used. The elements of \textbf{A} can be expressed as
180 > scheme is often used. The elements of $\mathsf{A}$ can be expressed as
181   arithmetic operations involving the four quaternions ($q_0, q_1, q_2,$
182   and $q_3$).\cite{allen87:csl} Use of quaternions also leads to
183   performance enhancements, particularly for very small
# Line 194 | Line 193 | molecule{
193  
194   \begin{lstlisting}[float,caption={[Defining rigid bodies]A sample definition of a rigid body},label={sch:rigidBody}]
195   molecule{
196 <  name = "TIP3P_water";
196 >  name = "TIP3P";
197 >  nAtoms = 3;
198 >  atom[0]{
199 >    type = "O_TIP3P";
200 >    position( 0.0, 0.0, -0.06556 );
201 >  }
202 >  atom[1]{
203 >    type = "H_TIP3P";
204 >    position( 0.0, 0.75695, 0.52032 );
205 >  }
206 >  atom[2]{
207 >    type = "H_TIP3P";
208 >    position( 0.0, -0.75695, 0.52032 );
209 >  }
210 >
211    nRigidBodies = 1;
212 <  rigidBody[0]{
213 <    nAtoms = 3;
214 <    atom[0]{
202 <      type = "O_TIP3P";
203 <      position( 0.0, 0.0, -0.06556 );    
204 <    }                                    
205 <    atom[1]{
206 <      type = "H_TIP3P";
207 <      position( 0.0, 0.75695, 0.52032 );
208 <    }
209 <    atom[2]{
210 <      type = "H_TIP3P";
211 <      position( 0.0, -0.75695, 0.52032 );
212 <    }
213 <    position( 0.0, 0.0, 0.0 );
214 <    orientation( 0.0, 0.0, 1.0 );
212 >  rigidBody[0]{
213 >    nMembers = 3;
214 >    members(0, 1, 2);
215    }
216   }
217   \end{lstlisting}
# Line 233 | Line 233 | $\epsilon_{ij}$ scales the well depth of the potential
233   Where $r_{ij}$ is the distance between particles $i$ and $j$,
234   $\sigma_{ij}$ scales the length of the interaction, and
235   $\epsilon_{ij}$ scales the well depth of the potential. Scheme
236 < \ref{sch:LJFF} gives and example \texttt{.bass} file that
236 > \ref{sch:LJFF} gives an example \texttt{.bass} file that
237   sets up a system of 108 Ar particles to be simulated using the
238   Lennard-Jones force field.
239  
# Line 264 | Line 264 | cut-off radius, and preserves conservation of energy i
264   the energy value at $r_{\text{cut}}$ is subtracted from the
265   potential. This causes the potential to go to zero smoothly at the
266   cut-off radius, and preserves conservation of energy in integrating
267 < the equations of motion.
267 > the equations of motion. There still remains a discontinuity in the derivative (the forces), however, this does not significantly affect the dynamics.
268  
269   Interactions between dissimilar particles requires the generation of
270   cross term parameters for $\sigma$ and $\epsilon$. These are
# Line 299 | Line 299 | As an example, lipid head-groups in {\sc duff} are rep
299   include a reaction field to mimic larger range interactions.
300  
301   As an example, lipid head-groups in {\sc duff} are represented as
302 < point dipole interaction sites. By placing a dipole at the head group
303 < center of mass, our model mimics the charge separation found in common
304 < phospholipids such as phosphatidylcholine.\cite{Cevc87} Additionally,
305 < a large Lennard-Jones site is located at the pseudoatom's center of
306 < mass. The model is illustrated by the red atom in
307 < Fig.~\ref{oopseFig:lipidModel}. The water model we use to complement
308 < the dipoles of the lipids is our reparameterization of the soft sticky
309 < dipole (SSD) model of Ichiye
302 > point dipole interaction sites. By placing a dipole at the head
303 > group's center of mass, our model mimics the charge separation found
304 > in common phospholipid head groups such as
305 > phosphatidylcholine.\cite{Cevc87} Additionally, a large Lennard-Jones
306 > site is located at the pseudoatom's center of mass. The model is
307 > illustrated by the red atom in Fig.~\ref{oopseFig:lipidModel}. The
308 > water model we use to complement the dipoles of the lipids is our
309 > reparameterization of the soft sticky dipole (SSD) model of Ichiye
310   \emph{et al.}\cite{liu96:new_model}
311  
312   \begin{figure}
313   \centering
314 < \includegraphics[width=\linewidth]{lipidModel.eps}
314 > \includegraphics[width=\linewidth]{twoChainFig.eps}
315   \caption[A representation of a lipid model in {\sc duff}]{A representation of the lipid model. $\phi$ is the torsion angle, $\theta$ %
316 < is the bend angle, $\mu$ is the dipole moment of the head group, and n
317 < is the chain length.}
316 > is the bend angle, and $\mu$ is the dipole moment of the head group.}
317   \label{oopseFig:lipidModel}
318   \end{figure}
319  
# Line 338 | Line 337 | illustrated in Scheme \ref{sch:DUFF}.
337   integrating the equations of motion. A simulation using {\sc duff} is
338   illustrated in Scheme \ref{sch:DUFF}.
339  
340 < \begin{lstlisting}[float,caption={[Invocation of {\sc duff}]Sample \texttt{.bass} file showing a simulation utilizing {\sc duff}},label={sch:DUFF}]
340 > \begin{lstlisting}[float,caption={[Invocation of {\sc duff}]A portion of a \texttt{.bass} file showing a simulation utilizing {\sc duff}},label={sch:DUFF}]
341  
342   #include "water.mdl"
343   #include "lipid.mdl"
# Line 382 | Line 381 | for all 1, 4 bonded pairs. The pairwise portions of th
381   Here $V_{\text{bend}}$ is the bend potential for all 1, 3 bonded pairs
382   within the molecule $I$, and $V_{\text{torsion}}$ is the torsion potential
383   for all 1, 4 bonded pairs. The pairwise portions of the internal
384 < potential are excluded for pairs that are closer than three bonds,
386 < i.e.~atom pairs farther away than a torsion are included in the
387 < pair-wise loop.
384 > potential are excluded for atom pairs that are involved in the same bond, bend, or torsion. All other atom pairs within the molecule are subject to the LJ pair potential.
385  
386  
387   The bend potential of a molecule is represented by the following function:
# Line 574 | Line 571 | is recommended that the parameters be modified to thos
571   exhibits improved liquid structure and transport behavior. If the use
572   of a reaction field long-range interaction correction is desired, it
573   is recommended that the parameters be modified to those of the SSD/RF
574 < model. Solvent parameters can be easily modified in an accompanying
574 > model (an SSD variant  parameterized for reaction field). Solvent parameters can be easily modified in an accompanying
575   \texttt{.bass} file as illustrated in the scheme below. A table of the
576   parameter values and the drawbacks and benefits of the different
577   density corrected SSD models can be found in
578   reference~\cite{Gezelter04}.
579  
580 < \begin{lstlisting}[float,caption={[A simulation of {\sc ssd} water]An example file showing a simulation including {\sc ssd} water.},label={sch:ssd}]
580 > \begin{lstlisting}[float,caption={[A simulation of {\sc ssd} water]A portion of a \texttt{.bass} file showing a simulation including {\sc ssd} water.},label={sch:ssd}]
581  
582   #include "water.mdl"
583  
# Line 644 | Line 641 | metals Cu, Ag, Au, Ni, Pd, Pt and alloys of these meta
641   surrounding atom $i$ for both the density $\rho$ and pairwise $\phi$
642   interactions. Foiles \emph{et al}.~fit {\sc eam} potentials for the fcc
643   metals Cu, Ag, Au, Ni, Pd, Pt and alloys of these metals.\cite{FBD86}
644 < These fits, are included in {\sc oopse}.
644 > These fits are included in {\sc oopse}.
645  
646   \subsection{\label{oopseSec:pbc}Periodic Boundary Conditions}
647  
# Line 664 | Line 661 | size of the simulation box. $\mathsf{H}$ is defined:
661   \begin{equation}
662   \mathsf{H} = ( \mathbf{h}_x, \mathbf{h}_y, \mathbf{h}_z )
663   \end{equation}
664 < Where $\mathbf{h}_j$ is the column vector of the $j$th axis of the
664 > Where $\mathbf{h}_{\alpha}$ is the column vector of the $\alpha$ axis of the
665   box.  During the course of the simulation both the size and shape of
666   the box can be changed to allow volume fluctuations when constraining
667   the pressure.
# Line 679 | Line 676 | first convert it to its corresponding vector in box sp
676   lengths in the $\mathbf{h}_x$, $\mathbf{h}_y$, and $\mathbf{h}_z$
677   directions. To find the minimum image of a vector $\mathbf{r}$, we
678   first convert it to its corresponding vector in box space, and then,
679 < cast each element to lie on the in the range $[-0.5,0.5]$:
679 > cast each element to lie in the range $[-0.5,0.5]$:
680   \begin{equation}
681   s_{i}^{\prime}=s_{i}-\roundme(s_{i})
682   \end{equation}
683   Where $s_i$ is the $i$th element of $\mathbf{s}$, and
684 < $\roundme(s_i)$is given by
684 > $\roundme(s_i)$ is given by
685   \begin{equation}
686   \roundme(x) =
687          \begin{cases}
# Line 811 | Line 808 | output files.
808   entities are written out using quanternions, to save space in the
809   output files.
810  
811 < \begin{lstlisting}[float,caption={[The format of the coordinate files]Shows the format of the coordinate files. The fist line is the number of atoms. The second line begins with the time stamp followed by the three $\mathsf{H}$ column vectors. It is important to note, that for extended system ensembles, additional information pertinent to the integrators may be stored on this line as well.. The next lines are the atomic coordinates for all atoms in the system. First is the name followed by position, velocity, quanternions, and lastly angular velocities.},label=sch:dumpFormat]
811 > \begin{lstlisting}[float,caption={[The format of the coordinate files]Shows the format of the coordinate files. The fist line is the number of atoms. The second line begins with the time stamp followed by the three $\mathsf{H}$ column vectors. It is important to note, that for extended system ensembles, additional information pertinent to the integrators may be stored on this line as well. The next lines are the atomic coordinates for all atoms in the system. First is the name followed by position, velocity, quanternions, and lastly angular velocities.},label=sch:dumpFormat]
812  
813   nAtoms
814   time; Hxx Hyx Hzx; Hxy Hyy Hzy; Hxz Hyz Hzz;
# Line 867 | Line 864 | statistics file is denoted with the \texttt{.stat} fil
864  
865   \section{\label{oopseSec:mechanics}Mechanics}
866  
870
871 \section{\label{sec:mechanics}Mechanics}
872
867   \subsection{\label{oopseSec:integrate}Integrating the Equations of Motion: the
868   DLM method}
869  
# Line 879 | Line 873 | standard velocity-Verlet integrator which is known to
873   (DLM).\cite{Dullweber1997} When there are no directional atoms or
874   rigid bodies present in the simulation, this integrator becomes the
875   standard velocity-Verlet integrator which is known to sample the
876 < microcanonical (NVE) ensemble.\cite{}
876 > microcanonical (NVE) ensemble.\cite{Frenkel1996}
877  
878   Previous integration methods for orientational motion have problems
879   that are avoided in the DLM method.  Direct propagation of the Euler
# Line 914 | Line 908 | V\left(\left\{{\bf r}\right\}, \left\{\mathsf{A}\right
908   {\bf j}_i \right) +
909   V\left(\left\{{\bf r}\right\}, \left\{\mathsf{A}\right\}\right)
910   \end{equation}
911 < where ${\bf r}_i$ and ${\bf v}_i$ are the cartesian position vector
912 < and velocity of the center of mass of particle $i$, and ${\bf j}_i$
913 < and $\overleftrightarrow{\mathsf{I}}_i$ are the body-fixed angular
914 < momentum and moment of inertia tensor, respectively.  $\mathsf{A}_i$
911 > Where ${\bf r}_i$ and ${\bf v}_i$ are the cartesian position vector
912 > and velocity of the center of mass of particle $i$, and ${\bf j}_i$,
913 > $\overleftrightarrow{\mathsf{I}}_i$ are the body-fixed angular
914 > momentum and moment of inertia tensor respectively, and the
915 > superscript $T$ denotes the transpose of the vector.  $\mathsf{A}_i$
916   is the $3 \times 3$ rotation matrix describing the instantaneous
917   orientation of the particle.  $V$ is the potential energy function
918   which may depend on both the positions $\left\{{\bf r}\right\}$ and
# Line 998 | Line 993 | Monte Carlo applications, and
993   {\it symplectic}),
994   \item the integrator is time-{\it reversible}, making it suitable for Hybrid
995   Monte Carlo applications, and
996 < \item the error for a single time step is of order $O\left(h^3\right)$
996 > \item the error for a single time step is of order $\mathcal{O}\left(h^4\right)$
997   for timesteps of length $h$.
998   \end{enumerate}
999  
1000   The integration of the equations of motion is carried out in a
1001 < velocity-Verlet style 2-part algorithm:
1001 > velocity-Verlet style 2-part algorithm, where $h= \delta t$:
1002  
1003   {\tt moveA:}
1004 < \begin{eqnarray}
1005 < {\bf v}\left(t + \delta t / 2\right)  & \leftarrow & {\bf
1006 < v}(t) + \frac{\delta t}{2} \left( {\bf f}(t) / m \right) \\
1007 < {\bf r}(t + \delta t) & \leftarrow & {\bf r}(t) + \delta t  {\bf
1008 < v}\left(t + \delta t / 2 \right) \\
1009 < {\bf j}\left(t + \delta t / 2 \right)  & \leftarrow & {\bf
1010 < j}(t) + \frac{\delta t}{2} {\bf \tau}^b(t)  \\
1011 < \mathsf{A}(t + \delta t) & \leftarrow & \mathrm{rot}\left( \delta t
1012 < {\bf j}(t + \delta t / 2) \cdot \overleftrightarrow{\mathsf{I}}^{-1}
1013 < \right)
1014 < \end{eqnarray}
1004 > \begin{align*}
1005 > {\bf v}\left(t + h / 2\right)  &\leftarrow  {\bf v}(t)
1006 >        + \frac{h}{2} \left( {\bf f}(t) / m \right) \\
1007 > %
1008 > {\bf r}(t + h) &\leftarrow {\bf r}(t)
1009 >        + h  {\bf v}\left(t + h / 2 \right) \\
1010 > %
1011 > {\bf j}\left(t + h / 2 \right)  &\leftarrow {\bf j}(t)
1012 >        + \frac{h}{2} {\bf \tau}^b(t)  \\
1013 > %
1014 > \mathsf{A}(t + h) &\leftarrow \mathrm{rotate}\left( h {\bf j}
1015 >        (t + h / 2) \cdot \overleftrightarrow{\mathsf{I}}^{-1} \right)
1016 > \end{align*}
1017  
1018 < In this context, the $\mathrm{rot}$ function is the reversible product
1018 > In this context, the $\mathrm{rotate}$ function is the reversible product
1019   of the three body-fixed rotations,
1020   \begin{equation}
1021 < \mathrm{rot}({\bf a}) = \mathsf{G}_x(a_x / 2) \cdot
1021 > \mathrm{rotate}({\bf a}) = \mathsf{G}_x(a_x / 2) \cdot
1022   \mathsf{G}_y(a_y / 2) \cdot \mathsf{G}_z(a_z) \cdot \mathsf{G}_y(a_y /
1023   2) \cdot \mathsf{G}_x(a_x /2)
1024   \end{equation}
# Line 1058 | Line 1055 | torques are calculated at the new positions and orient
1055   torques are calculated at the new positions and orientations
1056  
1057   {\tt doForces:}
1058 < \begin{eqnarray}
1059 < {\bf f}(t + \delta t) & \leftarrow & - \left(\frac{\partial V}{\partial {\bf
1060 < r}}\right)_{{\bf r}(t + \delta t)} \\
1061 < {\bf \tau}^{s}(t + \delta t) & \leftarrow & {\bf u}(t + \delta t)
1062 < \times \frac{\partial V}{\partial {\bf u}} \\
1063 < {\bf \tau}^{b}(t + \delta t) & \leftarrow & \mathsf{A}(t + \delta t)
1064 < \cdot {\bf \tau}^s(t + \delta t)
1065 < \end{eqnarray}
1058 > \begin{align*}
1059 > {\bf f}(t + h) &\leftarrow  
1060 >        - \left(\frac{\partial V}{\partial {\bf r}}\right)_{{\bf r}(t + h)} \\
1061 > %
1062 > {\bf \tau}^{s}(t + h) &\leftarrow {\bf u}(t + h)
1063 >        \times \frac{\partial V}{\partial {\bf u}} \\
1064 > %
1065 > {\bf \tau}^{b}(t + h) &\leftarrow \mathsf{A}(t + h)
1066 >        \cdot {\bf \tau}^s(t + h)
1067 > \end{align*}
1068  
1069   {\sc oopse} automatically updates ${\bf u}$ when the rotation matrix
1070   $\mathsf{A}$ is calculated in {\tt moveA}.  Once the forces and
# Line 1073 | Line 1072 | advanced to the same time value.
1072   advanced to the same time value.
1073  
1074   {\tt moveB:}
1075 < \begin{eqnarray}
1076 < {\bf v}\left(t + \delta t \right)  & \leftarrow & {\bf
1077 < v}\left(t + \delta t / 2 \right) + \frac{\delta t}{2} \left(
1078 < {\bf f}(t + \delta t) / m \right) \\
1079 < {\bf j}\left(t + \delta t \right)  & \leftarrow & {\bf
1080 < j}\left(t + \delta t / 2 \right) + \frac{\delta t}{2} {\bf
1081 < \tau}^b(t + \delta t)  
1083 < \end{eqnarray}
1075 > \begin{align*}
1076 > {\bf v}\left(t + h \right)  &\leftarrow  {\bf v}\left(t + h / 2 \right)
1077 >        + \frac{h}{2} \left( {\bf f}(t + h) / m \right) \\
1078 > %
1079 > {\bf j}\left(t + h \right)  &\leftarrow {\bf j}\left(t + h / 2 \right)
1080 >        + \frac{h}{2} {\bf \tau}^b(t + h)  
1081 > \end{align*}
1082  
1083   The matrix rotations used in the DLM method end up being more costly
1084   computationally than the simpler arithmetic quaternion
# Line 1088 | Line 1086 | comparing the energy conservation of the two methods a
1086   shows an average 7\% increase in computation time using the DLM method
1087   in place of quaternions. This cost is more than justified when
1088   comparing the energy conservation of the two methods as illustrated in
1089 < figure \ref{timestep}.
1089 > Fig.~\ref{timestep}.
1090  
1091   \begin{figure}
1092   \centering
# Line 1102 | Line 1100 | energy baseline for clarity.}
1100   \label{timestep}
1101   \end{figure}
1102  
1103 < In figure \ref{timestep}, the resulting energy drift at various time
1103 > In Fig.~\ref{timestep}, the resulting energy drift at various time
1104   steps for both the DLM and quaternion integration schemes is
1105   compared. All of the 1000 molecule water simulations started with the
1106   same configuration, and the only difference was the method for
# Line 1122 | Line 1120 | default value} \\  
1120   \begin{tabular}{llll}
1121   {\bf variable} & {\bf {\tt .bass} keyword} & {\bf units} & {\bf
1122   default value} \\  
1123 < $\delta t$ & {\tt dt = 2.0;} & fs & none
1123 > $h$ & {\tt dt = 2.0;} & fs & none
1124   \end{tabular}
1125   \end{center}
1126  
# Line 1136 | Line 1134 | integrator can selected with the {\tt ensemble} keywor
1134   \begin{center}
1135   \begin{tabular}{lll}
1136   {\bf Integrator} & {\bf Ensemble} & {\bf {\tt .bass} line} \\
1137 < NVE & microcanonical & {\tt ensemble = ``NVE''; } \\
1138 < NVT & canonical & {\tt ensemble = ``NVT''; } \\
1139 < NPTi & isobaric-isothermal (with isotropic volume changes) & {\tt
1140 < ensemble = ``NPTi'';} \\
1141 < NPTf & isobaric-isothermal (with changes to box shape) & {\tt
1142 < ensemble = ``NPTf'';} \\
1143 < NPTxyz & approximate isobaric-isothermal & {\tt ensemble =
1144 < ``NPTxyz'';} \\
1147 < &  (with separate barostats on each box dimension) &
1137 > NVE & microcanonical & {\tt ensemble = NVE; } \\
1138 > NVT & canonical & {\tt ensemble = NVT; } \\
1139 > NPTi & isobaric-isothermal & {\tt ensemble = NPTi;} \\
1140 >  &  (with isotropic volume changes) & \\
1141 > NPTf & isobaric-isothermal & {\tt ensemble = NPTf;} \\
1142 >  & (with changes to box shape) & \\
1143 > NPTxyz & approximate isobaric-isothermal & {\tt ensemble = NPTxyz;} \\
1144 > &  (with separate barostats on each box dimension) & \\
1145   \end{tabular}
1146   \end{center}
1147  
1148 < The relatively well-known Nos\'e-Hoover thermostat is implemented in
1149 < {\sc oopse}'s NVT integrator.  This method couples an extra degree of
1150 < freedom (the thermostat) to the kinetic energy of the system, and has
1151 < been shown to sample the canonical distribution in the system degrees
1152 < of freedom while conserving a quantity that is, to within a constant,
1153 < the Helmholtz free energy.
1148 > The relatively well-known Nos\'e-Hoover thermostat\cite{Hoover85} is
1149 > implemented in {\sc oopse}'s NVT integrator.  This method couples an
1150 > extra degree of freedom (the thermostat) to the kinetic energy of the
1151 > system, and has been shown to sample the canonical distribution in the
1152 > system degrees of freedom while conserving a quantity that is, to
1153 > within a constant, the Helmholtz free energy.\cite{melchionna93}
1154  
1155   NPT algorithms attempt to maintain constant pressure in the system by
1156   coupling the volume of the system to a barostat.  {\sc oopse} contains
1157   three different constant pressure algorithms.  The first two, NPTi and
1158   NPTf have been shown to conserve a quantity that is, to within a
1159 < constant, the Gibbs free energy.  The Melchionna modification to the
1160 < Hoover barostat is implemented in both NPTi and NPTf.  NPTi allows
1161 < only isotropic changes in the simulation box, while box {\it shape}
1162 < variations are allowed in NPTf.  The NPTxyz integrator has {\it not}
1163 < been shown to sample from the isobaric-isothermal ensemble.  It is
1164 < useful, however, in that it maintains orthogonality for the axes of
1165 < the simulation box while attempting to equalize pressure along the
1166 < three perpendicular directions in the box.
1159 > constant, the Gibbs free energy.\cite{melchionna93} The Melchionna
1160 > modification to the Hoover barostat is implemented in both NPTi and
1161 > NPTf.  NPTi allows only isotropic changes in the simulation box, while
1162 > box {\it shape} variations are allowed in NPTf.  The NPTxyz integrator
1163 > has {\it not} been shown to sample from the isobaric-isothermal
1164 > ensemble.  It is useful, however, in that it maintains orthogonality
1165 > for the axes of the simulation box while attempting to equalize
1166 > pressure along the three perpendicular directions in the box.
1167  
1168   Each of the extended system integrators requires additional keywords
1169   to set target values for the thermodynamic state variables that are
# Line 1174 | Line 1171 | variables.
1171   characteristic decay times for the dynamics of the extended
1172   variables.
1173  
1174 + \begin{center}
1175   \begin{tabular}{llll}
1176   {\bf variable} & {\bf {\tt .bass} keyword} & {\bf units} & {\bf
1177   default value} \\  
# Line 1182 | Line 1180 | $\tau_B$ & {\tt tauBarostat = 5e3;} & fs  & none \\
1180   $\tau_T$ & {\tt tauThermostat = 1e3;} & fs & none \\
1181   $\tau_B$ & {\tt tauBarostat = 5e3;} & fs  & none \\
1182           & {\tt resetTime = 200;} & fs & none \\
1183 <         & {\tt useInitialExtendedSystemState = ``true'';} & logical &
1184 < false
1183 >         & {\tt useInitialExtendedSystemState = true;} & logical &
1184 > true
1185   \end{tabular}
1186 + \end{center}
1187  
1188   Two additional keywords can be used to either clear the extended
1189   system variables periodically ({\tt resetTime}), or to maintain the
# Line 1192 | Line 1191 | and their use in the integrators follows below.
1191   useInitialExtendedSystemState}).  More details on these variables
1192   and their use in the integrators follows below.
1193  
1194 < \subsubsection{\label{oopseSec:noseHooverThermo}Nos\'{e}-Hoover Thermostatting}
1194 > \subsection{\label{oopseSec:noseHooverThermo}Nos\'{e}-Hoover Thermostatting}
1195  
1196   The Nos\'e-Hoover equations of motion are given by\cite{Hoover85}
1197   \begin{eqnarray}
# Line 1239 | Line 1238 | part algorithm:
1238   part algorithm:
1239  
1240   {\tt moveA:}
1241 < \begin{eqnarray}
1242 < T(t) & \leftarrow & \left\{{\bf v}(t)\right\}, \left\{{\bf j}(t)\right\} \\
1243 < {\bf v}\left(t + \delta t / 2\right)  & \leftarrow & {\bf
1244 < v}(t) + \frac{\delta t}{2} \left( \frac{{\bf f}(t)}{m} - {\bf v}(t)
1245 < \chi(t)\right) \\
1246 < {\bf r}(t + \delta t) & \leftarrow & {\bf r}(t) + \delta t {\bf
1247 < v}\left(t + \delta t / 2 \right) \\
1248 < {\bf j}\left(t + \delta t / 2 \right)  & \leftarrow & {\bf
1249 < j}(t) + \frac{\delta t}{2} \left( {\bf \tau}^b(t) - {\bf j}(t)
1250 < \chi(t) \right) \\
1251 < \mathsf{A}(t + \delta t) & \leftarrow & \mathrm{rot}\left(\delta t *
1252 < {\bf j}(t + \delta t / 2) \overleftrightarrow{\mathsf{I}}^{-1} \right) \\
1253 < \chi\left(t + \delta t / 2 \right) & \leftarrow & \chi(t) +
1254 < \frac{\delta t}{2 \tau_T^2} \left( \frac{T(t)}{T_{\mathrm{target}}} - 1
1255 < \right)
1256 < \end{eqnarray}
1241 > \begin{align*}
1242 > T(t) &\leftarrow \left\{{\bf v}(t)\right\}, \left\{{\bf j}(t)\right\} \\
1243 > %
1244 > {\bf v}\left(t + h / 2\right)  &\leftarrow {\bf v}(t)
1245 >        + \frac{h}{2} \left( \frac{{\bf f}(t)}{m} - {\bf v}(t)
1246 >        \chi(t)\right) \\
1247 > %
1248 > {\bf r}(t + h) &\leftarrow {\bf r}(t)
1249 >        + h {\bf v}\left(t + h / 2 \right) \\
1250 > %
1251 > {\bf j}\left(t + h / 2 \right)  &\leftarrow {\bf j}(t)
1252 >        + \frac{h}{2} \left( {\bf \tau}^b(t) - {\bf j}(t)
1253 >        \chi(t) \right) \\
1254 > %
1255 > \mathsf{A}(t + h) &\leftarrow \mathrm{rotate}
1256 >        \left(h * {\bf j}(t + h / 2)
1257 >        \overleftrightarrow{\mathsf{I}}^{-1} \right) \\
1258 > %
1259 > \chi\left(t + h / 2 \right) &\leftarrow \chi(t)
1260 >        + \frac{h}{2 \tau_T^2} \left( \frac{T(t)}
1261 >        {T_{\mathrm{target}}} - 1 \right)
1262 > \end{align*}
1263  
1264 < Here $\mathrm{rot}(\delta t * {\bf j}
1264 > Here $\mathrm{rotate}(h * {\bf j}
1265   \overleftrightarrow{\mathsf{I}}^{-1})$ is the same symplectic Trotter
1266   factorization of the three rotation operations that was discussed in
1267   the section on the DLM integrator.  Note that this operation modifies
# Line 1272 | Line 1277 | advanced to the same time value.
1277   advanced to the same time value.
1278  
1279   {\tt moveB:}
1280 < \begin{eqnarray}
1281 < T(t + \delta t) & \leftarrow & \left\{{\bf v}(t + \delta t)\right\},
1282 < \left\{{\bf j}(t + \delta t)\right\} \\
1283 < \chi\left(t + \delta t \right) & \leftarrow & \chi\left(t + \delta t /
1284 < 2 \right) + \frac{\delta t}{2 \tau_T^2} \left( \frac{T(t+\delta
1285 < t)}{T_{\mathrm{target}}} - 1 \right) \\
1286 < {\bf v}\left(t + \delta t \right)  & \leftarrow & {\bf
1287 < v}\left(t + \delta t / 2 \right) + \frac{\delta t}{2} \left(
1288 < \frac{{\bf f}(t + \delta t)}{m} - {\bf v}(t + \delta t)
1289 < \chi(t \delta t)\right) \\
1290 < {\bf j}\left(t + \delta t \right)  & \leftarrow & {\bf
1291 < j}\left(t + \delta t / 2 \right) + \frac{\delta t}{2} \left( {\bf
1292 < \tau}^b(t + \delta t) - {\bf j}(t + \delta t)
1293 < \chi(t + \delta t) \right)
1294 < \end{eqnarray}
1280 > \begin{align*}
1281 > T(t + h) &\leftarrow \left\{{\bf v}(t + h)\right\},
1282 >        \left\{{\bf j}(t + h)\right\} \\
1283 > %
1284 > \chi\left(t + h \right) &\leftarrow \chi\left(t + h /
1285 >        2 \right) + \frac{h}{2 \tau_T^2} \left( \frac{T(t+h)}
1286 >        {T_{\mathrm{target}}} - 1 \right) \\
1287 > %
1288 > {\bf v}\left(t + h \right)  &\leftarrow {\bf v}\left(t
1289 >        + h / 2 \right) + \frac{h}{2} \left(
1290 >        \frac{{\bf f}(t + h)}{m} - {\bf v}(t + h)
1291 >        \chi(t h)\right) \\
1292 > %
1293 > {\bf j}\left(t + h \right) &\leftarrow {\bf j}\left(t
1294 >        + h / 2 \right) + \frac{h}{2}
1295 >        \left( {\bf \tau}^b(t + h) - {\bf j}(t + h)
1296 >        \chi(t + h) \right)
1297 > \end{align*}
1298  
1299 < Since ${\bf v}(t + \delta t)$ and ${\bf j}(t + \delta t)$ are required
1300 < to caclculate $T(t + \delta t)$ as well as $\chi(t + \delta t)$, they
1301 < indirectly depend on their own values at time $t + \delta t$.  {\tt
1302 < moveB} is therefore done in an iterative fashion until $\chi(t +
1303 < \delta t)$ becomes self-consistent.  The relative tolerance for the
1304 < self-consistency check defaults to a value of $\mbox{10}^{-6}$, but
1305 < {\sc oopse} will terminate the iteration after 4 loops even if the
1298 < consistency check has not been satisfied.
1299 > Since ${\bf v}(t + h)$ and ${\bf j}(t + h)$ are required to caclculate
1300 > $T(t + h)$ as well as $\chi(t + h)$, they indirectly depend on their
1301 > own values at time $t + h$.  {\tt moveB} is therefore done in an
1302 > iterative fashion until $\chi(t + h)$ becomes self-consistent.  The
1303 > relative tolerance for the self-consistency check defaults to a value
1304 > of $\mbox{10}^{-6}$, but {\sc oopse} will terminate the iteration
1305 > after 4 loops even if the consistency check has not been satisfied.
1306  
1307   The Nos\'e-Hoover algorithm is known to conserve a Hamiltonian for the
1308   extended system that is, to within a constant, identical to the
1309 < Helmholtz free energy,
1309 > Helmholtz free energy,\cite{melchionna93}
1310   \begin{equation}
1311   H_{\mathrm{NVT}} = V + K + f k_B T_{\mathrm{target}} \left(
1312   \frac{\tau_{T}^2 \chi^2(t)}{2} + \int_{0}^{t} \chi(t^\prime) dt^\prime
1313   \right)
1314   \end{equation}
1315 < Poor choices of $\delta t$ or $\tau_T$ can result in non-conservation
1315 > Poor choices of $h$ or $\tau_T$ can result in non-conservation
1316   of $H_{\mathrm{NVT}}$, so the conserved quantity is maintained in the
1317   last column of the {\tt .stat} file to allow checks on the quality of
1318   the integration.
# Line 1314 | Line 1321 | algorithms are given in section \ref{oopseSec:rattle}.
1321   {\tt moveB} portions of the algorithm.  Details on the constraint
1322   algorithms are given in section \ref{oopseSec:rattle}.
1323  
1324 < \subsubsection{\label{sec:NPTi}Constant-pressure integration with
1324 > \subsection{\label{sec:NPTi}Constant-pressure integration with
1325   isotropic box deformations (NPTi)}
1326  
1327   To carry out isobaric-isothermal ensemble calculations {\sc oopse}
# Line 1382 | Line 1389 | velocity-Verlet style 2 part algorithm:
1389   velocity-Verlet style 2 part algorithm:
1390  
1391   {\tt moveA:}
1392 < \begin{eqnarray}
1393 < T(t) & \leftarrow & \left\{{\bf v}(t)\right\}, \left\{{\bf j}(t)\right\} \\
1394 < P(t) & \leftarrow & \left\{{\bf r}(t)\right\}, \left\{{\bf v}(t)\right\}, \left\{{\bf f}(t)\right\} \\
1395 < {\bf v}\left(t + \delta t / 2\right)  & \leftarrow & {\bf
1396 < v}(t) + \frac{\delta t}{2} \left( \frac{{\bf f}(t)}{m} - {\bf v}(t)
1397 < \left(\chi(t) + \eta(t) \right) \right) \\
1398 < {\bf j}\left(t + \delta t / 2 \right)  & \leftarrow & {\bf
1399 < j}(t) + \frac{\delta t}{2} \left( {\bf \tau}^b(t) - {\bf j}(t)
1400 < \chi(t) \right) \\
1401 < \mathsf{A}(t + \delta t) & \leftarrow & \mathrm{rot}\left(\delta t *
1402 < {\bf j}(t + \delta t / 2) \overleftrightarrow{\mathsf{I}}^{-1} \right) \\
1403 < \chi\left(t + \delta t / 2 \right) & \leftarrow & \chi(t) +
1404 < \frac{\delta t}{2 \tau_T^2} \left( \frac{T(t)}{T_{\mathrm{target}}} - 1
1405 < \right) \\
1406 < \eta(t + \delta t / 2) & \leftarrow & \eta(t) + \frac{\delta t \mathcal{V}(t)}{2 N k_B
1407 < T(t) \tau_B^2} \left( P(t) - P_{\mathrm{target}} \right) \\
1408 < {\bf r}(t + \delta t) & \leftarrow & {\bf r}(t) + \delta t \left\{ {\bf
1409 < v}\left(t + \delta t / 2 \right) + \eta(t + \delta t / 2)\left[ {\bf
1410 < r}(t + \delta t) - {\bf R}_0 \right] \right\} \\
1411 < \mathsf{H}(t + \delta t) & \leftarrow & e^{-\delta t \eta(t + \delta t
1412 < / 2)} \mathsf{H}(t)
1413 < \end{eqnarray}
1392 > \begin{align*}
1393 > T(t) &\leftarrow \left\{{\bf v}(t)\right\}, \left\{{\bf j}(t)\right\} \\
1394 > %
1395 > P(t) &\leftarrow \left\{{\bf r}(t)\right\}, \left\{{\bf v}(t)\right\} \\
1396 > %
1397 > {\bf v}\left(t + h / 2\right)  &\leftarrow {\bf v}(t)
1398 >        + \frac{h}{2} \left( \frac{{\bf f}(t)}{m} - {\bf v}(t)
1399 >        \left(\chi(t) + \eta(t) \right) \right) \\
1400 > %
1401 > {\bf j}\left(t + h / 2 \right)  &\leftarrow {\bf j}(t)
1402 >        + \frac{h}{2} \left( {\bf \tau}^b(t) - {\bf j}(t)
1403 >        \chi(t) \right) \\
1404 > %
1405 > \mathsf{A}(t + h) &\leftarrow \mathrm{rotate}\left(h *
1406 >        {\bf j}(t + h / 2) \overleftrightarrow{\mathsf{I}}^{-1}
1407 >        \right) \\
1408 > %
1409 > \chi\left(t + h / 2 \right) &\leftarrow \chi(t) +
1410 >        \frac{h}{2 \tau_T^2} \left( \frac{T(t)}{T_{\mathrm{target}}} - 1
1411 >        \right) \\
1412 > %
1413 > \eta(t + h / 2) &\leftarrow \eta(t) + \frac{h
1414 >        \mathcal{V}(t)}{2 N k_B T(t) \tau_B^2} \left( P(t)
1415 >        - P_{\mathrm{target}} \right) \\
1416 > %
1417 > {\bf r}(t + h) &\leftarrow {\bf r}(t) + h
1418 >        \left\{ {\bf v}\left(t + h / 2 \right)
1419 >        + \eta(t + h / 2)\left[ {\bf r}(t + h)
1420 >        - {\bf R}_0 \right] \right\} \\
1421 > %
1422 > \mathsf{H}(t + h) &\leftarrow e^{-h \eta(t + h / 2)}
1423 >        \mathsf{H}(t)
1424 > \end{align*}
1425  
1426   Most of these equations are identical to their counterparts in the NVT
1427 < integrator, but the propagation of positions to time $t + \delta t$
1427 > integrator, but the propagation of positions to time $t + h$
1428   depends on the positions at the same time.  {\sc oopse} carries out
1429   this step iteratively (with a limit of 5 passes through the iterative
1430   loop).  Also, the simulation box $\mathsf{H}$ is scaled uniformly for
1431   one full time step by an exponential factor that depends on the value
1432   of $\eta$ at time $t +
1433 < \delta t / 2$.  Reshaping the box uniformly also scales the volume of
1433 > h / 2$.  Reshaping the box uniformly also scales the volume of
1434   the box by
1435   \begin{equation}
1436 < \mathcal{V}(t + \delta t) \leftarrow e^{ - 3 \delta t \eta(t + \delta t /2)}
1436 > \mathcal{V}(t + h) \leftarrow e^{ - 3 h \eta(t + h /2)}
1437   \mathcal{V}(t)
1438   \end{equation}
1439  
# Line 1425 | Line 1443 | the same time value.
1443   the same time value.
1444  
1445   {\tt moveB:}
1446 < \begin{eqnarray}
1447 < T(t + \delta t) & \leftarrow & \left\{{\bf v}(t + \delta t)\right\},
1448 < \left\{{\bf j}(t + \delta t)\right\} \\
1449 < P(t + \delta t) & \leftarrow & \left\{{\bf r}(t + \delta t)\right\},
1450 < \left\{{\bf v}(t + \delta t)\right\}, \left\{{\bf f}(t + \delta t)\right\} \\
1451 < \chi\left(t + \delta t \right) & \leftarrow & \chi\left(t + \delta t /
1452 < 2 \right) + \frac{\delta t}{2 \tau_T^2} \left( \frac{T(t+\delta
1453 < t)}{T_{\mathrm{target}}} - 1 \right) \\
1454 < \eta(t + \delta t) & \leftarrow & \eta(t + \delta t / 2) +
1455 < \frac{\delta t \mathcal{V}(t + \delta t)}{2 N k_B T(t + \delta t) \tau_B^2}
1456 < \left( P(t + \delta t) - P_{\mathrm{target}}
1457 < \right) \\
1458 < {\bf v}\left(t + \delta t \right)  & \leftarrow & {\bf
1459 < v}\left(t + \delta t / 2 \right) + \frac{\delta t}{2} \left(
1460 < \frac{{\bf f}(t + \delta t)}{m} - {\bf v}(t + \delta t)
1461 < (\chi(t + \delta t) + \eta(t + \delta t)) \right) \\
1462 < {\bf j}\left(t + \delta t \right)  & \leftarrow & {\bf
1463 < j}\left(t + \delta t / 2 \right) + \frac{\delta t}{2} \left( {\bf
1464 < \tau}^b(t + \delta t) - {\bf j}(t + \delta t)
1465 < \chi(t + \delta t) \right)
1466 < \end{eqnarray}
1446 > \begin{align*}
1447 > T(t + h) &\leftarrow \left\{{\bf v}(t + h)\right\},
1448 >        \left\{{\bf j}(t + h)\right\} \\
1449 > %
1450 > P(t + h) &\leftarrow  \left\{{\bf r}(t + h)\right\},
1451 >        \left\{{\bf v}(t + h)\right\} \\
1452 > %
1453 > \chi\left(t + h \right) &\leftarrow \chi\left(t + h /
1454 >        2 \right) + \frac{h}{2 \tau_T^2} \left( \frac{T(t+h)}
1455 >        {T_{\mathrm{target}}} - 1 \right) \\
1456 > %
1457 > \eta(t + h) &\leftarrow \eta(t + h / 2) +
1458 >        \frac{h \mathcal{V}(t + h)}{2 N k_B T(t + h)
1459 >        \tau_B^2} \left( P(t + h) - P_{\mathrm{target}} \right) \\
1460 > %
1461 > {\bf v}\left(t + h \right)  &\leftarrow {\bf v}\left(t
1462 >        + h / 2 \right) + \frac{h}{2} \left(
1463 >        \frac{{\bf f}(t + h)}{m} - {\bf v}(t + h)
1464 >        (\chi(t + h) + \eta(t + h)) \right) \\
1465 > %
1466 > {\bf j}\left(t + h \right)  &\leftarrow {\bf j}\left(t
1467 >        + h / 2 \right) + \frac{h}{2} \left( {\bf
1468 >        \tau}^b(t + h) - {\bf j}(t + h)
1469 >        \chi(t + h) \right)
1470 > \end{align*}
1471  
1472 < Once again, since ${\bf v}(t + \delta t)$ and ${\bf j}(t + \delta t)$
1473 < are required to caclculate $T(t + \delta t)$, $P(t + \delta t)$, $\chi(t +
1474 < \delta t)$, and $\eta(t + \delta t)$, they indirectly depend on their
1475 < own values at time $t + \delta t$.  {\tt moveB} is therefore done in
1476 < an iterative fashion until $\chi(t + \delta t)$ and $\eta(t + \delta
1477 < t)$ become self-consistent.  The relative tolerance for the
1478 < self-consistency check defaults to a value of $\mbox{10}^{-6}$, but
1457 < {\sc oopse} will terminate the iteration after 4 loops even if the
1472 > Once again, since ${\bf v}(t + h)$ and ${\bf j}(t + h)$ are required
1473 > to caclculate $T(t + h)$, $P(t + h)$, $\chi(t + h)$, and $\eta(t +
1474 > h)$, they indirectly depend on their own values at time $t + h$.  {\tt
1475 > moveB} is therefore done in an iterative fashion until $\chi(t + h)$
1476 > and $\eta(t + h)$ become self-consistent.  The relative tolerance for
1477 > the self-consistency check defaults to a value of $\mbox{10}^{-6}$,
1478 > but {\sc oopse} will terminate the iteration after 4 loops even if the
1479   consistency check has not been satisfied.
1480  
1481   The Melchionna modification of the Nos\'e-Hoover-Andersen algorithm is
# Line 1481 | Line 1502 | algorithms are given in section \ref{oopseSec:rattle}.
1502   {\tt moveB} portions of the algorithm.  Details on the constraint
1503   algorithms are given in section \ref{oopseSec:rattle}.
1504  
1505 < \subsubsection{\label{sec:NPTf}Constant-pressure integration with a
1505 > \subsection{\label{sec:NPTf}Constant-pressure integration with a
1506   flexible box (NPTf)}
1507  
1508   There is a relatively simple generalization of the
# Line 1493 | Line 1514 | the box shape.  The equations of motion for this metho
1514   \begin{eqnarray}
1515   \dot{{\bf r}} & = & {\bf v} + \overleftrightarrow{\eta} \cdot \left( {\bf r} - {\bf R}_0 \right) \\
1516   \dot{{\bf v}} & = & \frac{{\bf f}}{m} - (\overleftrightarrow{\eta} +
1517 < \chi \mathsf{1}) {\bf v} \\
1517 > \chi \cdot \mathsf{1}) {\bf v} \\
1518   \dot{\mathsf{A}} & = & \mathsf{A} \cdot
1519   \mbox{ skew}\left(\overleftrightarrow{I}^{-1} \cdot {\bf j}\right) \\
1520   \dot{{\bf j}} & = & {\bf j} \times \left( \overleftrightarrow{I}^{-1}
# Line 1501 | Line 1522 | V}{\partial \mathsf{A}} \right) - \chi {\bf j} \\
1522   V}{\partial \mathsf{A}} \right) - \chi {\bf j} \\
1523   \dot{\chi} & = & \frac{1}{\tau_{T}^2} \left(
1524   \frac{T}{T_{\mathrm{target}}} - 1 \right) \\
1525 < \dot{\overleftrightarrow{eta}} & = & \frac{1}{\tau_{B}^2 f k_B
1525 > \dot{\overleftrightarrow{\eta}} & = & \frac{1}{\tau_{B}^2 f k_B
1526   T_{\mathrm{target}}} V \left( \overleftrightarrow{\mathsf{P}} - P_{\mathrm{target}}\mathsf{1} \right) \\
1527   \dot{\mathsf{H}} & = &  \overleftrightarrow{\eta} \cdot \mathsf{H}
1528   \label{eq:melchionna2}
# Line 1515 | Line 1536 | NPTi integration:
1536   NPTi integration:
1537  
1538   {\tt moveA:}
1539 < \begin{eqnarray}
1540 < T(t) & \leftarrow & \left\{{\bf v}(t)\right\}, \left\{{\bf j}(t)\right\} \\
1541 < \overleftrightarrow{\mathsf{P}}(t) & \leftarrow & \left\{{\bf r}(t)\right\}, \left\{{\bf v}(t)\right\}, \left\{{\bf f}(t)\right\} \\
1542 < {\bf v}\left(t + \delta t / 2\right)  & \leftarrow & {\bf
1543 < v}(t) + \frac{\delta t}{2} \left( \frac{{\bf f}(t)}{m} -
1544 < \left(\chi(t)\mathsf{1} + \overleftrightarrow{\eta}(t) \right) \cdot
1545 < {\bf v}(t) \right) \\
1546 < {\bf j}\left(t + \delta t / 2 \right)  & \leftarrow & {\bf
1547 < j}(t) + \frac{\delta t}{2} \left( {\bf \tau}^b(t) - {\bf j}(t)
1548 < \chi(t) \right) \\
1549 < \mathsf{A}(t + \delta t) & \leftarrow & \mathrm{rot}\left(\delta t *
1550 < {\bf j}(t + \delta t / 2) \overleftrightarrow{\mathsf{I}}^{-1} \right) \\
1551 < \chi\left(t + \delta t / 2 \right) & \leftarrow & \chi(t) +
1552 < \frac{\delta t}{2 \tau_T^2} \left( \frac{T(t)}{T_{\mathrm{target}}} - 1
1553 < \right) \\
1554 < \overleftrightarrow{\eta}(t + \delta t / 2) & \leftarrow & \overleftrightarrow{\eta}(t) + \frac{\delta t \mathcal{V}(t)}{2 N k_B
1555 < T(t) \tau_B^2} \left( \overleftrightarrow{\mathsf{P}}(t) - P_{\mathrm{target}}\mathsf{1} \right) \\
1556 < {\bf r}(t + \delta t) & \leftarrow & {\bf r}(t) + \delta t \left\{ {\bf
1557 < v}\left(t + \delta t / 2 \right) + \overleftrightarrow{\eta}(t +
1558 < \delta t / 2) \cdot \left[ {\bf
1559 < r}(t + \delta t) - {\bf R}_0 \right] \right\} \\
1560 < \mathsf{H}(t + \delta t) & \leftarrow & \mathsf{H}(t) \cdot e^{-\delta t
1561 < \overleftrightarrow{\eta}(t + \delta t / 2)}
1562 < \end{eqnarray}
1539 > \begin{align*}
1540 > T(t) &\leftarrow \left\{{\bf v}(t)\right\}, \left\{{\bf j}(t)\right\} \\
1541 > %
1542 > \overleftrightarrow{\mathsf{P}}(t) &\leftarrow \left\{{\bf r}(t)\right\},
1543 >        \left\{{\bf v}(t)\right\} \\
1544 > %
1545 > {\bf v}\left(t + h / 2\right)  &\leftarrow {\bf v}(t)
1546 >        + \frac{h}{2} \left( \frac{{\bf f}(t)}{m} -
1547 >        \left(\chi(t)\mathsf{1} + \overleftrightarrow{\eta}(t) \right) \cdot
1548 >        {\bf v}(t) \right) \\
1549 > %
1550 > {\bf j}\left(t + h / 2 \right)  &\leftarrow {\bf j}(t)
1551 >        + \frac{h}{2} \left( {\bf \tau}^b(t) - {\bf j}(t)
1552 >        \chi(t) \right) \\
1553 > %
1554 > \mathsf{A}(t + h) &\leftarrow \mathrm{rotate}\left(h *
1555 >        {\bf j}(t + h / 2) \overleftrightarrow{\mathsf{I}}^{-1}
1556 >        \right) \\
1557 > %
1558 > \chi\left(t + h / 2 \right) &\leftarrow \chi(t) +
1559 >        \frac{h}{2 \tau_T^2} \left( \frac{T(t)}{T_{\mathrm{target}}}
1560 >        - 1 \right) \\
1561 > %
1562 > \overleftrightarrow{\eta}(t + h / 2) &\leftarrow
1563 >        \overleftrightarrow{\eta}(t) + \frac{h \mathcal{V}(t)}{2 N k_B
1564 >        T(t) \tau_B^2} \left( \overleftrightarrow{\mathsf{P}}(t)
1565 >        - P_{\mathrm{target}}\mathsf{1} \right) \\
1566 > %
1567 > {\bf r}(t + h) &\leftarrow {\bf r}(t) + h \left\{ {\bf v}
1568 >        \left(t + h / 2 \right) + \overleftrightarrow{\eta}(t +
1569 >        h / 2) \cdot \left[ {\bf r}(t + h)
1570 >        - {\bf R}_0 \right] \right\} \\
1571 > %
1572 > \mathsf{H}(t + h) &\leftarrow \mathsf{H}(t) \cdot e^{-h
1573 >        \overleftrightarrow{\eta}(t + h / 2)}
1574 > \end{align*}
1575   {\sc oopse} uses a power series expansion truncated at second order
1576   for the exponential operation which scales the simulation box.
1577  
# Line 1546 | Line 1579 | NPTi integrator:
1579   NPTi integrator:
1580  
1581   {\tt moveB:}
1582 < \begin{eqnarray}
1583 < T(t + \delta t) & \leftarrow & \left\{{\bf v}(t + \delta t)\right\},
1584 < \left\{{\bf j}(t + \delta t)\right\} \\
1585 < \overleftrightarrow{\mathsf{P}}(t + \delta t) & \leftarrow & \left\{{\bf r}(t + \delta t)\right\},
1586 < \left\{{\bf v}(t + \delta t)\right\}, \left\{{\bf f}(t + \delta t)\right\} \\
1587 < \chi\left(t + \delta t \right) & \leftarrow & \chi\left(t + \delta t /
1588 < 2 \right) + \frac{\delta t}{2 \tau_T^2} \left( \frac{T(t+\delta
1589 < t)}{T_{\mathrm{target}}} - 1 \right) \\
1590 < \overleftrightarrow{\eta}(t + \delta t) & \leftarrow & \overleftrightarrow{\eta}(t + \delta t / 2) +
1591 < \frac{\delta t \mathcal{V}(t + \delta t)}{2 N k_B T(t + \delta t) \tau_B^2}
1592 < \left( \overleftrightarrow{P}(t + \delta t) - P_{\mathrm{target}}\mathsf{1}
1593 < \right) \\
1594 < {\bf v}\left(t + \delta t \right)  & \leftarrow & {\bf
1595 < v}\left(t + \delta t / 2 \right) + \frac{\delta t}{2} \left(
1596 < \frac{{\bf f}(t + \delta t)}{m} -
1597 < (\chi(t + \delta t)\mathsf{1} + \overleftrightarrow{\eta}(t + \delta
1598 < t)) \right) \cdot {\bf v}(t + \delta t) \\
1599 < {\bf j}\left(t + \delta t \right)  & \leftarrow & {\bf
1600 < j}\left(t + \delta t / 2 \right) + \frac{\delta t}{2} \left( {\bf
1601 < \tau}^b(t + \delta t) - {\bf j}(t + \delta t)
1602 < \chi(t + \delta t) \right)
1603 < \end{eqnarray}
1582 > \begin{align*}
1583 > T(t + h) &\leftarrow \left\{{\bf v}(t + h)\right\},
1584 >        \left\{{\bf j}(t + h)\right\} \\
1585 > %
1586 > \overleftrightarrow{\mathsf{P}}(t + h) &\leftarrow \left\{{\bf r}
1587 >        (t + h)\right\}, \left\{{\bf v}(t
1588 >        + h)\right\}, \left\{{\bf f}(t + h)\right\} \\
1589 > %
1590 > \chi\left(t + h \right) &\leftarrow \chi\left(t + h /
1591 >        2 \right) + \frac{h}{2 \tau_T^2} \left( \frac{T(t+
1592 >        h)}{T_{\mathrm{target}}} - 1 \right) \\
1593 > %
1594 > \overleftrightarrow{\eta}(t + h) &\leftarrow
1595 >        \overleftrightarrow{\eta}(t + h / 2) +
1596 >        \frac{h \mathcal{V}(t + h)}{2 N k_B T(t + h)
1597 >        \tau_B^2} \left( \overleftrightarrow{P}(t + h)
1598 >        - P_{\mathrm{target}}\mathsf{1} \right) \\
1599 > %
1600 > {\bf v}\left(t + h \right)  &\leftarrow {\bf v}\left(t
1601 >        + h / 2 \right) + \frac{h}{2} \left(
1602 >        \frac{{\bf f}(t + h)}{m} -
1603 >        (\chi(t + h)\mathsf{1} + \overleftrightarrow{\eta}(t
1604 >        + h)) \right) \cdot {\bf v}(t + h) \\
1605 > %
1606 > {\bf j}\left(t + h \right)  &\leftarrow {\bf j}\left(t
1607 >        + h / 2 \right) + \frac{h}{2} \left( {\bf \tau}^b(t
1608 >        + h) - {\bf j}(t + h) \chi(t + h) \right)
1609 > \end{align*}
1610  
1611   The iterative schemes for both {\tt moveA} and {\tt moveB} are
1612   identical to those described for the NPTi integrator.
# Line 1585 | Line 1624 | elongated and sheared geometries which become smaller
1624   simulations.  Liquids have very small restoring forces in the
1625   off-diagonal directions, and the simulation box can very quickly form
1626   elongated and sheared geometries which become smaller than the
1627 < electrostatic or Lennard-Jones cutoff radii.  It finds most use in
1628 < simulating crystals or liquid crystals which assume non-orthorhombic
1629 < geometries.
1627 > electrostatic or Lennard-Jones cutoff radii.  The NPTf integrator
1628 > finds most use in simulating crystals or liquid crystals which assume
1629 > non-orthorhombic geometries.
1630  
1631 < \subsubsection{\label{nptxyz}Constant pressure in 3 axes (NPTxyz)}
1631 > \subsection{\label{nptxyz}Constant pressure in 3 axes (NPTxyz)}
1632  
1633   There is one additional extended system integrator which is somewhat
1634   simpler than the NPTf method described above.  In this case, the three
# Line 1617 | Line 1656 | formulation of the {\sc shake} method\cite{ryckaert77}
1656   oopse}, we have implemented the {\sc rattle} algorithm of
1657   Andersen.\cite{andersen83} The algorithm is a velocity verlet
1658   formulation of the {\sc shake} method\cite{ryckaert77} of iteratively
1659 < solving the Lagrange multipliers of constraint. The system of lagrange
1659 > solving the Lagrange multipliers of constraint. The system of Lagrange
1660   multipliers allows one to reformulate the equations of motion with
1661   explicit constraint forces.\cite{fowles99:lagrange}
1662  
# Line 1911 | Line 1950 | F_{\beta i} = F_{\beta i} - \frac{m_{\beta i} \sum_{\a
1950   F_{\beta i} = F_{\beta i} - \frac{m_{\beta i} \sum_{\alpha} G_{\alpha}}
1951          {\sum_{\beta}\sum_i m_{\beta i}}
1952   \end{equation}
1953 < Where $\beta$ are all of the unconstrained molecules in the system.
1953 > Where $\beta$ are all of the unconstrained molecules in the
1954 > system. Similarly, the velocities of the unconstrained molecules must
1955 > also be scaled.
1956 > \begin{equation}
1957 > v_{\beta i} = v_{\beta i} + \sum_{\alpha}
1958 >        \frac{\sum_i m_{\alpha i} v_{\alpha i}}{\sum_i m_{\alpha i}}
1959 > \end{equation}
1960  
1961   At the very beginning of the simulation, the molecules may not be at their
1962   constrained positions. To move a z-constrained molecule to its specified
# Line 1939 | Line 1984 | can be found in Table~\ref{oopseTb:gofrs}
1984   can be found in Table~\ref{oopseTb:gofrs}
1985  
1986   \begin{table}
1987 < \caption[The list of pair correlations in \texttt{staticProps}]{The different pair correlations in \texttt{staticProps} along with whether atom A or B must be directional.}
1987 > \caption[The list of pair correlations in \texttt{staticProps}]{THE DIFFERENT PAIR CORRELATIONS IN \texttt{staticProps}}
1988   \label{oopseTb:gofrs}
1989   \begin{center}
1990   \begin{tabular}{|l|c|c|}
# Line 1952 | Line 1997 | $\langle \cos \omega \rangle_{\text{AB}}(r)$ & Eq.~\re
1997   $\langle \cos \omega \rangle_{\text{AB}}(r)$ & Eq.~\ref{eq:cosOmegaOfR} &%
1998          both \\ \hline
1999   \end{tabular}
2000 + \begin{minipage}{\linewidth}
2001 + \centering
2002 + \vspace{2mm}
2003 + The third column specifies which atom, if any, need be a directional entity.
2004 + \end{minipage}
2005   \end{center}
2006   \end{table}
2007  
# Line 2120 | Line 2170 | duration of the simulation. Computational cost scales
2170   Algorithmically simplest of the three methods is atomic decomposition
2171   where N particles in a simulation are split among P processors for the
2172   duration of the simulation. Computational cost scales as an optimal
2173 < $O(N/P)$ for atomic decomposition. Unfortunately all processors must
2174 < communicate positions and forces with all other processors at every
2175 < force evaluation, leading communication costs to scale as an
2176 < unfavorable $O(N)$, \emph{independent of the number of processors}. This
2177 < communication bottleneck led to the development of spatial and force
2178 < decomposition methods in which communication among processors scales
2179 < much more favorably. Spatial or domain decomposition divides the
2180 < physical spatial domain into 3D boxes in which each processor is
2181 < responsible for calculation of forces and positions of particles
2182 < located in its box. Particles are reassigned to different processors
2183 < as they move through simulation space. To calculate forces on a given
2184 < particle, a processor must know the positions of particles within some
2185 < cutoff radius located on nearby processors instead of the positions of
2186 < particles on all processors. Both communication between processors and
2187 < computation scale as $O(N/P)$ in the spatial method. However, spatial
2173 > $\mathcal{O}(N/P)$ for atomic decomposition. Unfortunately all
2174 > processors must communicate positions and forces with all other
2175 > processors at every force evaluation, leading communication costs to
2176 > scale as an unfavorable $\mathcal{O}(N)$, \emph{independent of the
2177 > number of processors}. This communication bottleneck led to the
2178 > development of spatial and force decomposition methods in which
2179 > communication among processors scales much more favorably. Spatial or
2180 > domain decomposition divides the physical spatial domain into 3D boxes
2181 > in which each processor is responsible for calculation of forces and
2182 > positions of particles located in its box. Particles are reassigned to
2183 > different processors as they move through simulation space. To
2184 > calculate forces on a given particle, a processor must know the
2185 > positions of particles within some cutoff radius located on nearby
2186 > processors instead of the positions of particles on all
2187 > processors. Both communication between processors and computation
2188 > scale as $\mathcal{O}(N/P)$ in the spatial method. However, spatial
2189   decomposition adds algorithmic complexity to the simulation code and
2190   is not very efficient for small N since the overall communication
2191 < scales as the surface to volume ratio $(N/P)^{2/3}$ in three
2192 < dimensions.
2191 > scales as the surface to volume ratio $\mathcal{O}(N/P)^{2/3}$ in
2192 > three dimensions.
2193  
2194   The parallelization method used in {\sc oopse} is the force
2195   decomposition method.  Force decomposition assigns particles to
# Line 2147 | Line 2198 | assignment. Force decomposition is less complex to imp
2198   and column processor groups. Forces are calculated on particles in a
2199   given row by particles located in that processors column
2200   assignment. Force decomposition is less complex to implement than the
2201 < spatial method but still scales computationally as $O(N/P)$ and scales
2202 < as $O(N/\sqrt{P})$ in communication cost. Plimpton has also found that
2203 < force decompositions scale more favorably than spatial decompositions
2204 < for systems up to 10,000 atoms and favorably compete with spatial
2205 < methods up to 100,000 atoms.\cite{plimpton95}
2201 > spatial method but still scales computationally as $\mathcal{O}(N/P)$
2202 > and scales as $\mathcal{O}(N/\sqrt{P})$ in communication
2203 > cost. Plimpton has also found that force decompositions scale more
2204 > favorably than spatial decompositions for systems up to 10,000 atoms
2205 > and favorably compete with spatial methods up to 100,000
2206 > atoms.\cite{plimpton95}
2207  
2208   \subsection{\label{oopseSec:memAlloc}Memory Issues in Trajectory Analysis}
2209  
# Line 2177 | Line 2229 | second block of the trajectory is read, and the cross
2229   \texttt{dynamicProps} will calculate all of the time correlation frame
2230   pairs within the block. After in-block correlations are complete, a
2231   second block of the trajectory is read, and the cross correlations are
2232 < calculated between the two blocks. this second block is then freed and
2232 > calculated between the two blocks. This second block is then freed and
2233   then incremented and the process repeated until the end of the
2234   trajectory. Once the end is reached, the first block is freed then
2235   incremented, and the again the internal time correlations are
# Line 2207 | Line 2259 | These features are all brought together in a single op
2259   z-constraint method.
2260  
2261   These features are all brought together in a single open-source
2262 < program. Allowing researchers to not only benefit from
2262 > program. This allows researchers to not only benefit from
2263   {\sc oopse}, but also contribute to {\sc oopse}'s development as
2264 < well.Documentation and source code for {\sc oopse} can be downloaded
2213 < from \texttt{http://www.openscience.org/oopse/}.
2264 > well.
2265  

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