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867  
868   \section{\label{oopseSec:mechanics}Mechanics}
869  
870 \subsection{\label{oopseSec:integrate}Integrating the Equations of Motion: the Symplectic Step Integrator}
870  
871 < Integration of the equations of motion was carried out using the
872 < symplectic splitting method proposed by Dullweber \emph{et
873 < al.}.\cite{Dullweber1997} The reason for the selection of this
874 < integrator, is the poor energy conservation of rigid body systems
875 < using quaternion dynamics. While quaternions work well for
876 < orientational motion in alternate ensembles, the microcanonical
877 < ensemble has a constant energy requirement that is quite sensitive to
878 < errors in the equations of motion. The original implementation of {\sc
879 < oopse} utilized quaternions for rotational motion propagation;
880 < however, a detailed investigation showed that they resulted in a
881 < steady drift in the total energy, something that has been observed by
882 < others.\cite{Laird97}
871 > \section{\label{sec:mechanics}Mechanics}
872 >
873 > \subsection{\label{oopseSec:integrate}Integrating the Equations of Motion: the
874 > DLM method}
875 >
876 > The default method for integrating the equations of motion in {\sc
877 > oopse} is a velocity-Verlet version of the symplectic splitting method
878 > proposed by Dullweber, Leimkuhler and McLachlan
879 > (DLM).\cite{Dullweber1997} When there are no directional atoms or
880 > rigid bodies present in the simulation, this integrator becomes the
881 > standard velocity-Verlet integrator which is known to sample the
882 > microcanonical (NVE) ensemble.\cite{}
883 >
884 > Previous integration methods for orientational motion have problems
885 > that are avoided in the DLM method.  Direct propagation of the Euler
886 > angles has a known $1/\sin\theta$ divergence in the equations of
887 > motion for $\phi$ and $\psi$,\cite{allen87:csl} leading to
888 > numerical instabilities any time one of the directional atoms or rigid
889 > bodies has an orientation near $\theta=0$ or $\theta=\pi$.  More
890 > modern quaternion-based integration methods have relatively poor
891 > energy conservation.  While quaternions work well for orientational
892 > motion in other ensembles, the microcanonical ensemble has a
893 > constant energy requirement that is quite sensitive to errors in the
894 > equations of motion.  An earlier implementation of {\sc oopse}
895 > utilized quaternions for propagation of rotational motion; however, a
896 > detailed investigation showed that they resulted in a steady drift in
897 > the total energy, something that has been observed by
898 > Laird {\it et al.}\cite{Laird97}      
899  
900   The key difference in the integration method proposed by Dullweber
901 < \emph{et al}.~({\sc dlm}) is that the entire rotation matrix is propagated from
902 < one time step to the next. In the past, this would not have been a
903 < feasible option, since the rotation matrix for a single body is nine
904 < elements long as opposed to three or four elements for Euler angles
905 < and quaternions respectively. System memory has become much less of an
906 < issue in recent times, and the {\sc dlm} method has used memory in
907 < exchange for substantial benefits in energy conservation.
901 > \emph{et al.} is that the entire $3 \times 3$ rotation matrix is
902 > propagated from one time step to the next. In the past, this would not
903 > have been feasible, since the rotation matrix for a single body has
904 > nine elements compared with the more memory-efficient methods (using
905 > three Euler angles or 4 quaternions).  Computer memory has become much
906 > less costly in recent years, and this can be translated into
907 > substantial benefits in energy conservation.
908  
909 < The {\sc dlm} method allows for Verlet style integration of both
910 < linear and angular motion of rigid bodies. In the integration method,
911 < the orientational propagation involves a sequence of matrix
912 < evaluations to update the rotation matrix.\cite{Dullweber1997} These
913 < matrix rotations are more costly computationally than the simpler
914 < arithmetic quaternion propagation. With the same time step, a 1000 SSD
915 < particle simulation shows an average 7\% increase in computation time
916 < using the {\sc dlm} method in place of quaternions. This cost is more
917 < than justified when comparing the energy conservation of the two
918 < methods as illustrated in Fig.~\ref{timestep}.
909 > The basic equations of motion being integrated are derived from the
910 > Hamiltonian for conservative systems containing rigid bodies,
911 > \begin{equation}
912 > H = \sum_{i} \left( \frac{1}{2} m_i {\bf v}_i^T \cdot {\bf v}_i +
913 > \frac{1}{2} {\bf j}_i^T \cdot \overleftrightarrow{\mathsf{I}}_i^{-1} \cdot
914 > {\bf j}_i \right) +
915 > V\left(\left\{{\bf r}\right\}, \left\{\mathsf{A}\right\}\right)
916 > \end{equation}
917 > where ${\bf r}_i$ and ${\bf v}_i$ are the cartesian position vector
918 > and velocity of the center of mass of particle $i$, and ${\bf j}_i$
919 > and $\overleftrightarrow{\mathsf{I}}_i$ are the body-fixed angular
920 > momentum and moment of inertia tensor, respectively.  $\mathsf{A}_i$
921 > is the $3 \times 3$ rotation matrix describing the instantaneous
922 > orientation of the particle.  $V$ is the potential energy function
923 > which may depend on both the positions $\left\{{\bf r}\right\}$ and
924 > orientations $\left\{\mathsf{A}\right\}$ of all particles.  The
925 > equations of motion for the particle centers of mass are derived from
926 > Hamilton's equations and are quite simple,
927 > \begin{eqnarray}
928 > \dot{{\bf r}} & = & {\bf v} \\
929 > \dot{{\bf v}} & = & \frac{{\bf f}}{m}
930 > \end{eqnarray}
931 > where ${\bf f}$ is the instantaneous force on the center of mass
932 > of the particle,
933 > \begin{equation}
934 > {\bf f} = - \frac{\partial}{\partial
935 > {\bf r}} V(\left\{{\bf r}(t)\right\}, \left\{\mathsf{A}(t)\right\}).
936 > \end{equation}
937 >
938 > The equations of motion for the orientational degrees of freedom are
939 > \begin{eqnarray}
940 > \dot{\mathsf{A}} & = & \mathsf{A} \cdot
941 > \mbox{ skew}\left(\overleftrightarrow{\mathsf{I}}^{-1} \cdot {\bf j}\right) \\
942 > \dot{{\bf j}} & = & {\bf j} \times \left( \overleftrightarrow{\mathsf{I}}^{-1}
943 > \cdot {\bf j} \right) - \mbox{ rot}\left(\mathsf{A}^{T} \cdot \frac{\partial
944 > V}{\partial \mathsf{A}} \right)
945 > \end{eqnarray}
946 > In these equations of motion, the $\mbox{skew}$ matrix of a vector
947 > ${\bf v} = \left( v_1, v_2, v_3 \right)$ is defined:
948 > \begin{equation}
949 > \mbox{skew}\left( {\bf v} \right) := \left(
950 > \begin{array}{ccc}
951 > 0 & v_3 & - v_2 \\
952 > -v_3 & 0 & v_1 \\
953 > v_2 & -v_1 & 0
954 > \end{array}
955 > \right)
956 > \end{equation}
957 > The $\mbox{rot}$ notation refers to the mapping of the $3 \times 3$
958 > rotation matrix to a vector of orientations by first computing the
959 > skew-symmetric part $\left(\mathsf{A} - \mathsf{A}^{T}\right)$ and
960 > then associating this with a length 3 vector by inverting the
961 > $\mbox{skew}$ function above:
962 > \begin{equation}
963 > \mbox{rot}\left(\mathsf{A}\right) := \mbox{ skew}^{-1}\left(\mathsf{A}
964 > - \mathsf{A}^{T} \right)
965 > \end{equation}
966 > Written this way, the $\mbox{rot}$ operation creates a set of
967 > conjugate angle coordinates to the body-fixed angular momenta
968 > represented by ${\bf j}$.  This equation of motion for angular momenta
969 > is equivalent to the more familiar body-fixed forms,
970 > \begin{eqnarray}
971 > \dot{j_{x}} & = & \tau^b_x(t)  +
972 > \left(\overleftrightarrow{\mathsf{I}}_{yy} - \overleftrightarrow{\mathsf{I}}_{zz} \right) j_y j_z \\
973 > \dot{j_{y}} & = & \tau^b_y(t) +
974 > \left(\overleftrightarrow{\mathsf{I}}_{zz} - \overleftrightarrow{\mathsf{I}}_{xx} \right) j_z j_x \\
975 > \dot{j_{z}} & = & \tau^b_z(t) +
976 > \left(\overleftrightarrow{\mathsf{I}}_{xx} - \overleftrightarrow{\mathsf{I}}_{yy} \right) j_x j_y
977 > \end{eqnarray}
978 > which utilize the body-fixed torques, ${\bf \tau}^b$. Torques are
979 > most easily derived in the space-fixed frame,
980 > \begin{equation}
981 > {\bf \tau}^b(t) = \mathsf{A}(t) \cdot {\bf \tau}^s(t)
982 > \end{equation}
983 > where the torques are either derived from the forces on the
984 > constituent atoms of the rigid body, or for directional atoms,
985 > directly from derivatives of the potential energy,
986 > \begin{equation}
987 > {\bf \tau}^s(t) = - \hat{\bf u}(t) \times \left( \frac{\partial}
988 > {\partial \hat{\bf u}} V\left(\left\{ {\bf r}(t) \right\}, \left\{
989 > \mathsf{A}(t) \right\}\right) \right).
990 > \end{equation}
991 > Here $\hat{\bf u}$ is a unit vector pointing along the principal axis
992 > of the particle in the space-fixed frame.
993 >
994 > The DLM method uses a Trotter factorization of the orientational
995 > propagator.  This has three effects:
996 > \begin{enumerate}
997 > \item the integrator is area-preserving in phase space (i.e. it is
998 > {\it symplectic}),
999 > \item the integrator is time-{\it reversible}, making it suitable for Hybrid
1000 > Monte Carlo applications, and
1001 > \item the error for a single time step is of order $O\left(h^3\right)$
1002 > for timesteps of length $h$.
1003 > \end{enumerate}
1004 >
1005 > The integration of the equations of motion is carried out in a
1006 > velocity-Verlet style 2-part algorithm:
1007 >
1008 > {\tt moveA:}
1009 > \begin{eqnarray}
1010 > {\bf v}\left(t + \delta t / 2\right)  & \leftarrow & {\bf
1011 > v}(t) + \frac{\delta t}{2} \left( {\bf f}(t) / m \right) \\
1012 > {\bf r}(t + \delta t) & \leftarrow & {\bf r}(t) + \delta t  {\bf
1013 > v}\left(t + \delta t / 2 \right) \\
1014 > {\bf j}\left(t + \delta t / 2 \right)  & \leftarrow & {\bf
1015 > j}(t) + \frac{\delta t}{2} {\bf \tau}^b(t)  \\
1016 > \mathsf{A}(t + \delta t) & \leftarrow & \mathrm{rot}\left( \delta t
1017 > {\bf j}(t + \delta t / 2) \cdot \overleftrightarrow{\mathsf{I}}^{-1}
1018 > \right)
1019 > \end{eqnarray}
1020 >
1021 > In this context, the $\mathrm{rot}$ function is the reversible product
1022 > of the three body-fixed rotations,
1023 > \begin{equation}
1024 > \mathrm{rot}({\bf a}) = \mathsf{G}_x(a_x / 2) \cdot
1025 > \mathsf{G}_y(a_y / 2) \cdot \mathsf{G}_z(a_z) \cdot \mathsf{G}_y(a_y /
1026 > 2) \cdot \mathsf{G}_x(a_x /2)
1027 > \end{equation}
1028 > where each rotational propagator, $\mathsf{G}_\alpha(\theta)$, rotates
1029 > both the rotation matrix ($\mathsf{A}$) and the body-fixed angular
1030 > momentum (${\bf j}$) by an angle $\theta$ around body-fixed axis
1031 > $\alpha$,
1032 > \begin{equation}
1033 > \mathsf{G}_\alpha( \theta ) = \left\{
1034 > \begin{array}{lcl}
1035 > \mathsf{A}(t) & \leftarrow & \mathsf{A}(0) \cdot \mathsf{R}_\alpha(\theta)^T \\
1036 > {\bf j}(t) & \leftarrow & \mathsf{R}_\alpha(\theta) \cdot {\bf j}(0)
1037 > \end{array}
1038 > \right.
1039 > \end{equation}
1040 > $\mathsf{R}_\alpha$ is a quadratic approximation to
1041 > the single-axis rotation matrix.  For example, in the small-angle
1042 > limit, the rotation matrix around the body-fixed x-axis can be
1043 > approximated as
1044 > \begin{equation}
1045 > \mathsf{R}_x(\theta) \approx \left(
1046 > \begin{array}{ccc}
1047 > 1 & 0 & 0 \\
1048 > 0 & \frac{1-\theta^2 / 4}{1 + \theta^2 / 4}  & -\frac{\theta}{1+
1049 > \theta^2 / 4} \\
1050 > 0 & \frac{\theta}{1+
1051 > \theta^2 / 4} & \frac{1-\theta^2 / 4}{1 + \theta^2 / 4}
1052 > \end{array}
1053 > \right).
1054 > \end{equation}
1055 > All other rotations follow in a straightforward manner.
1056  
1057 + After the first part of the propagation, the forces and body-fixed
1058 + torques are calculated at the new positions and orientations
1059 +
1060 + {\tt doForces:}
1061 + \begin{eqnarray}
1062 + {\bf f}(t + \delta t) & \leftarrow & - \left(\frac{\partial V}{\partial {\bf
1063 + r}}\right)_{{\bf r}(t + \delta t)} \\
1064 + {\bf \tau}^{s}(t + \delta t) & \leftarrow & {\bf u}(t + \delta t)
1065 + \times \frac{\partial V}{\partial {\bf u}} \\
1066 + {\bf \tau}^{b}(t + \delta t) & \leftarrow & \mathsf{A}(t + \delta t)
1067 + \cdot {\bf \tau}^s(t + \delta t)
1068 + \end{eqnarray}
1069 +
1070 + {\sc oopse} automatically updates ${\bf u}$ when the rotation matrix
1071 + $\mathsf{A}$ is calculated in {\tt moveA}.  Once the forces and
1072 + torques have been obtained at the new time step, the velocities can be
1073 + advanced to the same time value.
1074 +
1075 + {\tt moveB:}
1076 + \begin{eqnarray}
1077 + {\bf v}\left(t + \delta t \right)  & \leftarrow & {\bf
1078 + v}\left(t + \delta t / 2 \right) + \frac{\delta t}{2} \left(
1079 + {\bf f}(t + \delta t) / m \right) \\
1080 + {\bf j}\left(t + \delta t \right)  & \leftarrow & {\bf
1081 + j}\left(t + \delta t / 2 \right) + \frac{\delta t}{2} {\bf
1082 + \tau}^b(t + \delta t)  
1083 + \end{eqnarray}
1084 +
1085 + The matrix rotations used in the DLM method end up being more costly
1086 + computationally than the simpler arithmetic quaternion
1087 + propagation. With the same time step, a 1000-molecule water simulation
1088 + shows an average 7\% increase in computation time using the DLM method
1089 + in place of quaternions. This cost is more than justified when
1090 + comparing the energy conservation of the two methods as illustrated in
1091 + figure \ref{timestep}.
1092 +
1093   \begin{figure}
1094   \centering
1095   \includegraphics[width=\linewidth]{timeStep.eps}
1096 < \caption[Energy conservation for quaternion versus {\sc dlm} dynamics]{Energy conservation using quaternion based integration versus
1097 < the {\sc dlm} method with
1098 < increasing time step. For each time step, the dotted line is total
1099 < energy using the {\sc dlm} integrator, and the solid line comes
1100 < from the quaternion integrator. The larger time step plots are shifted
1101 < up from the true energy baseline for clarity.}
1096 > \caption[Energy conservation for quaternion versus DLM dynamics]{Energy conservation using quaternion based integration versus
1097 > the method proposed by Dullweber \emph{et al.} with increasing time
1098 > step. For each time step, the dotted line is total energy using the
1099 > DLM integrator, and the solid line comes from the quaternion
1100 > integrator. The larger time step plots are shifted up from the true
1101 > energy baseline for clarity.}
1102   \label{timestep}
1103   \end{figure}
1104  
1105 < In Fig.~\ref{timestep}, the resulting energy drift at various time
1106 < steps for both the {\sc dlm} and quaternion integration schemes
1107 < is compared. All of the 1000 SSD particle simulations started with the
1105 > In figure \ref{timestep}, the resulting energy drift at various time
1106 > steps for both the DLM and quaternion integration schemes is
1107 > compared. All of the 1000 molecule water simulations started with the
1108   same configuration, and the only difference was the method for
1109   handling rotational motion. At time steps of 0.1 and 0.5 fs, both
1110 < methods for propagating particle rotation conserve energy fairly well,
1110 > methods for propagating molecule rotation conserve energy fairly well,
1111   with the quaternion method showing a slight energy drift over time in
1112   the 0.5 fs time step simulation. At time steps of 1 and 2 fs, the
1113 < energy conservation benefits of the {\sc dlm} method are clearly
1113 > energy conservation benefits of the DLM method are clearly
1114   demonstrated. Thus, while maintaining the same degree of energy
1115   conservation, one can take considerably longer time steps, leading to
1116   an overall reduction in computation time.
1117  
1118 < Energy drift in these SSD particle simulations was unnoticeable for
1119 < time steps up to three femtoseconds. A slight energy drift on the
932 < order of 0.012 kcal/mol per nanosecond was observed at a time step of
933 < four femtoseconds, and as expected, this drift increases dramatically
934 < with increasing time step.
1118 > There is only one specific keyword relevant to the default integrator,
1119 > and that is the time step for integrating the equations of motion.
1120  
1121 + \begin{center}
1122 + \begin{tabular}{llll}
1123 + {\bf variable} & {\bf {\tt .bass} keyword} & {\bf units} & {\bf
1124 + default value} \\  
1125 + $\delta t$ & {\tt dt = 2.0;} & fs & none
1126 + \end{tabular}
1127 + \end{center}
1128  
1129   \subsection{\label{sec:extended}Extended Systems for other Ensembles}
1130  
1131 + {\sc oopse} implements a number of extended system integrators for
1132 + sampling from other ensembles relevant to chemical physics.  The
1133 + integrator can selected with the {\tt ensemble} keyword in the
1134 + {\tt .bass} file:
1135  
1136 < {\sc oopse} implements a
1136 > \begin{center}
1137 > \begin{tabular}{lll}
1138 > {\bf Integrator} & {\bf Ensemble} & {\bf {\tt .bass} line} \\
1139 > NVE & microcanonical & {\tt ensemble = ``NVE''; } \\
1140 > NVT & canonical & {\tt ensemble = ``NVT''; } \\
1141 > NPTi & isobaric-isothermal (with isotropic volume changes) & {\tt
1142 > ensemble = ``NPTi'';} \\
1143 > NPTf & isobaric-isothermal (with changes to box shape) & {\tt
1144 > ensemble = ``NPTf'';} \\
1145 > NPTxyz & approximate isobaric-isothermal & {\tt ensemble =
1146 > ``NPTxyz'';} \\
1147 > &  (with separate barostats on each box dimension) &
1148 > \end{tabular}
1149 > \end{center}
1150  
1151 + The relatively well-known Nos\'e-Hoover thermostat is implemented in
1152 + {\sc oopse}'s NVT integrator.  This method couples an extra degree of
1153 + freedom (the thermostat) to the kinetic energy of the system, and has
1154 + been shown to sample the canonical distribution in the system degrees
1155 + of freedom while conserving a quantity that is, to within a constant,
1156 + the Helmholtz free energy.
1157  
1158 < \subsection{\label{oopseSec:noseHooverThermo}Nose-Hoover Thermostatting}
1158 > NPT algorithms attempt to maintain constant pressure in the system by
1159 > coupling the volume of the system to a barostat.  {\sc oopse} contains
1160 > three different constant pressure algorithms.  The first two, NPTi and
1161 > NPTf have been shown to conserve a quantity that is, to within a
1162 > constant, the Gibbs free energy.  The Melchionna modification to the
1163 > Hoover barostat is implemented in both NPTi and NPTf.  NPTi allows
1164 > only isotropic changes in the simulation box, while box {\it shape}
1165 > variations are allowed in NPTf.  The NPTxyz integrator has {\it not}
1166 > been shown to sample from the isobaric-isothermal ensemble.  It is
1167 > useful, however, in that it maintains orthogonality for the axes of
1168 > the simulation box while attempting to equalize pressure along the
1169 > three perpendicular directions in the box.
1170  
1171 < To mimic the effects of being in a constant temperature ({\sc nvt})
1172 < ensemble, {\sc oopse} uses the Nose-Hoover extended system
1173 < approach.\cite{Hoover85} In this method, the equations of motion for
1174 < the particle positions and velocities are
1171 > Each of the extended system integrators requires additional keywords
1172 > to set target values for the thermodynamic state variables that are
1173 > being held constant.  Keywords are also required to set the
1174 > characteristic decay times for the dynamics of the extended
1175 > variables.
1176 >
1177 > \begin{tabular}{llll}
1178 > {\bf variable} & {\bf {\tt .bass} keyword} & {\bf units} & {\bf
1179 > default value} \\  
1180 > $T_{\mathrm{target}}$ & {\tt targetTemperature = 300;} &  K & none \\
1181 > $P_{\mathrm{target}}$ & {\tt targetPressure = 1;} & atm & none \\
1182 > $\tau_T$ & {\tt tauThermostat = 1e3;} & fs & none \\
1183 > $\tau_B$ & {\tt tauBarostat = 5e3;} & fs  & none \\
1184 >         & {\tt resetTime = 200;} & fs & none \\
1185 >         & {\tt useInitialExtendedSystemState = ``true'';} & logical &
1186 > false
1187 > \end{tabular}
1188 >
1189 > Two additional keywords can be used to either clear the extended
1190 > system variables periodically ({\tt resetTime}), or to maintain the
1191 > state of the extended system variables between simulations ({\tt
1192 > useInitialExtendedSystemState}).  More details on these variables
1193 > and their use in the integrators follows below.
1194 >
1195 > \subsubsection{\label{oopseSec:noseHooverThermo}Nos\'{e}-Hoover Thermostatting}
1196 >
1197 > The Nos\'e-Hoover equations of motion are given by\cite{Hoover85}
1198   \begin{eqnarray}
1199   \dot{{\bf r}} & = & {\bf v} \\
1200 < \dot{{\bf v}} & = & \frac{{\bf f}}{m} - \chi {\bf v}
1200 > \dot{{\bf v}} & = & \frac{{\bf f}}{m} - \chi {\bf v} \\
1201 > \dot{\mathsf{A}} & = & \mathsf{A} \cdot
1202 > \mbox{ skew}\left(\overleftrightarrow{\mathsf{I}}^{-1} \cdot {\bf j}\right) \\
1203 > \dot{{\bf j}} & = & {\bf j} \times \left( \overleftrightarrow{\mathsf{I}}^{-1}
1204 > \cdot {\bf j} \right) - \mbox{ rot}\left(\mathsf{A}^{T} \cdot \frac{\partial
1205 > V}{\partial \mathsf{A}} \right) - \chi {\bf j}
1206   \label{eq:nosehoovereom}
1207   \end{eqnarray}
1208  
1209   $\chi$ is an ``extra'' variable included in the extended system, and
1210   it is propagated using the first order equation of motion
1211   \begin{equation}
1212 < \dot{\chi} = \frac{1}{\tau_{T}} \left( \frac{T}{T_{target}} - 1 \right)
1212 > \dot{\chi} = \frac{1}{\tau_{T}^2} \left( \frac{T}{T_{\mathrm{target}}} - 1 \right).
1213   \label{eq:nosehooverext}
1214   \end{equation}
961 where $T_{target}$ is the target temperature for the simulation, and
962 $\tau_{T}$ is a time constant for the thermostat.  
1215  
1216 < To select the Nose-Hoover {\sc nvt} ensemble, the {\tt ensemble = NVT;}
1217 < command would be used in the simulation's {\sc bass} file.  There is
1218 < some subtlety in choosing values for $\tau_{T}$, and it is usually set
1219 < to values of a few ps.  Within a {\sc bass} file, $\tau_{T}$ could be
1220 < set to 1 ps using the {\tt tauThermostat = 1000; } command.
1216 > The instantaneous temperature $T$ is proportional to the total kinetic
1217 > energy (both translational and orientational) and is given by
1218 > \begin{equation}
1219 > T = \frac{2 K}{f k_B}
1220 > \end{equation}
1221 > Here, $f$ is the total number of degrees of freedom in the system,
1222 > \begin{equation}
1223 > f = 3 N + 3 N_{\mathrm{orient}} - N_{\mathrm{constraints}}
1224 > \end{equation}
1225 > and $K$ is the total kinetic energy,
1226 > \begin{equation}
1227 > K = \sum_{i=1}^{N} \frac{1}{2} m_i {\bf v}_i^T \cdot {\bf v}_i +
1228 > \sum_{i=1}^{N_{\mathrm{orient}}}  \frac{1}{2} {\bf j}_i^T \cdot
1229 > \overleftrightarrow{\mathsf{I}}_i^{-1} \cdot {\bf j}_i
1230 > \end{equation}
1231  
1232 + In eq.(\ref{eq:nosehooverext}), $\tau_T$ is the time constant for
1233 + relaxation of the temperature to the target value.  To set values for
1234 + $\tau_T$ or $T_{\mathrm{target}}$ in a simulation, one would use the
1235 + {\tt tauThermostat} and {\tt targetTemperature} keywords in the {\tt
1236 + .bass} file.  The units for {\tt tauThermostat} are fs, and the units
1237 + for the {\tt targetTemperature} are degrees K.   The integration of
1238 + the equations of motion is carried out in a velocity-Verlet style 2
1239 + part algorithm:
1240 +
1241 + {\tt moveA:}
1242 + \begin{eqnarray}
1243 + T(t) & \leftarrow & \left\{{\bf v}(t)\right\}, \left\{{\bf j}(t)\right\} \\
1244 + {\bf v}\left(t + \delta t / 2\right)  & \leftarrow & {\bf
1245 + v}(t) + \frac{\delta t}{2} \left( \frac{{\bf f}(t)}{m} - {\bf v}(t)
1246 + \chi(t)\right) \\
1247 + {\bf r}(t + \delta t) & \leftarrow & {\bf r}(t) + \delta t {\bf
1248 + v}\left(t + \delta t / 2 \right) \\
1249 + {\bf j}\left(t + \delta t / 2 \right)  & \leftarrow & {\bf
1250 + j}(t) + \frac{\delta t}{2} \left( {\bf \tau}^b(t) - {\bf j}(t)
1251 + \chi(t) \right) \\
1252 + \mathsf{A}(t + \delta t) & \leftarrow & \mathrm{rot}\left(\delta t *
1253 + {\bf j}(t + \delta t / 2) \overleftrightarrow{\mathsf{I}}^{-1} \right) \\
1254 + \chi\left(t + \delta t / 2 \right) & \leftarrow & \chi(t) +
1255 + \frac{\delta t}{2 \tau_T^2} \left( \frac{T(t)}{T_{\mathrm{target}}} - 1
1256 + \right)
1257 + \end{eqnarray}
1258 +
1259 + Here $\mathrm{rot}(\delta t * {\bf j}
1260 + \overleftrightarrow{\mathsf{I}}^{-1})$ is the same symplectic Trotter
1261 + factorization of the three rotation operations that was discussed in
1262 + the section on the DLM integrator.  Note that this operation modifies
1263 + both the rotation matrix $\mathsf{A}$ and the angular momentum ${\bf
1264 + j}$.  {\tt moveA} propagates velocities by a half time step, and
1265 + positional degrees of freedom by a full time step.  The new positions
1266 + (and orientations) are then used to calculate a new set of forces and
1267 + torques in exactly the same way they are calculated in the {\tt
1268 + doForces} portion of the DLM integrator.
1269 +
1270 + Once the forces and torques have been obtained at the new time step,
1271 + the temperature, velocities, and the extended system variable can be
1272 + advanced to the same time value.
1273 +
1274 + {\tt moveB:}
1275 + \begin{eqnarray}
1276 + T(t + \delta t) & \leftarrow & \left\{{\bf v}(t + \delta t)\right\},
1277 + \left\{{\bf j}(t + \delta t)\right\} \\
1278 + \chi\left(t + \delta t \right) & \leftarrow & \chi\left(t + \delta t /
1279 + 2 \right) + \frac{\delta t}{2 \tau_T^2} \left( \frac{T(t+\delta
1280 + t)}{T_{\mathrm{target}}} - 1 \right) \\
1281 + {\bf v}\left(t + \delta t \right)  & \leftarrow & {\bf
1282 + v}\left(t + \delta t / 2 \right) + \frac{\delta t}{2} \left(
1283 + \frac{{\bf f}(t + \delta t)}{m} - {\bf v}(t + \delta t)
1284 + \chi(t \delta t)\right) \\
1285 + {\bf j}\left(t + \delta t \right)  & \leftarrow & {\bf
1286 + j}\left(t + \delta t / 2 \right) + \frac{\delta t}{2} \left( {\bf
1287 + \tau}^b(t + \delta t) - {\bf j}(t + \delta t)
1288 + \chi(t + \delta t) \right)
1289 + \end{eqnarray}
1290 +
1291 + Since ${\bf v}(t + \delta t)$ and ${\bf j}(t + \delta t)$ are required
1292 + to caclculate $T(t + \delta t)$ as well as $\chi(t + \delta t)$, they
1293 + indirectly depend on their own values at time $t + \delta t$.  {\tt
1294 + moveB} is therefore done in an iterative fashion until $\chi(t +
1295 + \delta t)$ becomes self-consistent.  The relative tolerance for the
1296 + self-consistency check defaults to a value of $\mbox{10}^{-6}$, but
1297 + {\sc oopse} will terminate the iteration after 4 loops even if the
1298 + consistency check has not been satisfied.
1299 +
1300 + The Nos\'e-Hoover algorithm is known to conserve a Hamiltonian for the
1301 + extended system that is, to within a constant, identical to the
1302 + Helmholtz free energy,
1303 + \begin{equation}
1304 + H_{\mathrm{NVT}} = V + K + f k_B T_{\mathrm{target}} \left(
1305 + \frac{\tau_{T}^2 \chi^2(t)}{2} + \int_{0}^{t} \chi(t^\prime) dt^\prime
1306 + \right)
1307 + \end{equation}
1308 + Poor choices of $\delta t$ or $\tau_T$ can result in non-conservation
1309 + of $H_{\mathrm{NVT}}$, so the conserved quantity is maintained in the
1310 + last column of the {\tt .stat} file to allow checks on the quality of
1311 + the integration.
1312 +
1313 + Bond constraints are applied at the end of both the {\tt moveA} and
1314 + {\tt moveB} portions of the algorithm.  Details on the constraint
1315 + algorithms are given in section \ref{oopseSec:rattle}.
1316 +
1317 + \subsubsection{\label{sec:NPTi}Constant-pressure integration with
1318 + isotropic box deformations (NPTi)}
1319 +
1320 + To carry out isobaric-isothermal ensemble calculations {\sc oopse}
1321 + implements the Melchionna modifications to the Nos\'e-Hoover-Andersen
1322 + equations of motion,\cite{melchionna93}
1323 +
1324 + \begin{eqnarray}
1325 + \dot{{\bf r}} & = & {\bf v} + \eta \left( {\bf r} - {\bf R}_0 \right) \\
1326 + \dot{{\bf v}} & = & \frac{{\bf f}}{m} - (\eta + \chi) {\bf v} \\
1327 + \dot{\mathsf{A}} & = & \mathsf{A} \cdot
1328 + \mbox{ skew}\left(\overleftrightarrow{I}^{-1} \cdot {\bf j}\right) \\
1329 + \dot{{\bf j}} & = & {\bf j} \times \left( \overleftrightarrow{I}^{-1}
1330 + \cdot {\bf j} \right) - \mbox{ rot}\left(\mathsf{A}^{T} \cdot \frac{\partial
1331 + V}{\partial \mathsf{A}} \right) - \chi {\bf j} \\
1332 + \dot{\chi} & = & \frac{1}{\tau_{T}^2} \left(
1333 + \frac{T}{T_{\mathrm{target}}} - 1 \right) \\
1334 + \dot{\eta} & = & \frac{1}{\tau_{B}^2 f k_B T_{\mathrm{target}}} V \left( P -
1335 + P_{\mathrm{target}} \right) \\
1336 + \dot{\mathcal{V}} & = & 3 \mathcal{V} \eta
1337 + \label{eq:melchionna1}
1338 + \end{eqnarray}
1339 +
1340 + $\chi$ and $\eta$ are the ``extra'' degrees of freedom in the extended
1341 + system.  $\chi$ is a thermostat, and it has the same function as it
1342 + does in the Nos\'e-Hoover NVT integrator.  $\eta$ is a barostat which
1343 + controls changes to the volume of the simulation box.  ${\bf R}_0$ is
1344 + the location of the center of mass for the entire system, and
1345 + $\mathcal{V}$ is the volume of the simulation box.  At any time, the
1346 + volume can be calculated from the determinant of the matrix which
1347 + describes the box shape:
1348 + \begin{equation}
1349 + \mathcal{V} = \det(\mathsf{H})
1350 + \end{equation}
1351 +
1352 + The NPTi integrator requires an instantaneous pressure. This quantity
1353 + is calculated via the pressure tensor,
1354 + \begin{equation}
1355 + \overleftrightarrow{\mathsf{P}}(t) = \frac{1}{\mathcal{V}(t)} \left(
1356 + \sum_{i=1}^{N} m_i {\bf v}_i(t) \otimes {\bf v}_i(t) \right) +
1357 + \overleftrightarrow{\mathsf{W}}(t)
1358 + \end{equation}
1359 + The kinetic contribution to the pressure tensor utilizes the {\it
1360 + outer} product of the velocities denoted by the $\otimes$ symbol.  The
1361 + stress tensor is calculated from another outer product of the
1362 + inter-atomic separation vectors (${\bf r}_{ij} = {\bf r}_j - {\bf
1363 + r}_i$) with the forces between the same two atoms,
1364 + \begin{equation}
1365 + \overleftrightarrow{\mathsf{W}}(t) = \sum_{i} \sum_{j>i} {\bf r}_{ij}(t)
1366 + \otimes {\bf f}_{ij}(t)
1367 + \end{equation}
1368 + The instantaneous pressure is then simply obtained from the trace of
1369 + the Pressure tensor,
1370 + \begin{equation}
1371 + P(t) = \frac{1}{3} \mathrm{Tr} \left( \overleftrightarrow{\mathsf{P}}(t)
1372 + \right)
1373 + \end{equation}
1374 +
1375 + In eq.(\ref{eq:melchionna1}), $\tau_B$ is the time constant for
1376 + relaxation of the pressure to the target value.  To set values for
1377 + $\tau_B$ or $P_{\mathrm{target}}$ in a simulation, one would use the
1378 + {\tt tauBarostat} and {\tt targetPressure} keywords in the {\tt .bass}
1379 + file.  The units for {\tt tauBarostat} are fs, and the units for the
1380 + {\tt targetPressure} are atmospheres.  Like in the NVT integrator, the
1381 + integration of the equations of motion is carried out in a
1382 + velocity-Verlet style 2 part algorithm:
1383 +
1384 + {\tt moveA:}
1385 + \begin{eqnarray}
1386 + T(t) & \leftarrow & \left\{{\bf v}(t)\right\}, \left\{{\bf j}(t)\right\} \\
1387 + P(t) & \leftarrow & \left\{{\bf r}(t)\right\}, \left\{{\bf v}(t)\right\}, \left\{{\bf f}(t)\right\} \\
1388 + {\bf v}\left(t + \delta t / 2\right)  & \leftarrow & {\bf
1389 + v}(t) + \frac{\delta t}{2} \left( \frac{{\bf f}(t)}{m} - {\bf v}(t)
1390 + \left(\chi(t) + \eta(t) \right) \right) \\
1391 + {\bf j}\left(t + \delta t / 2 \right)  & \leftarrow & {\bf
1392 + j}(t) + \frac{\delta t}{2} \left( {\bf \tau}^b(t) - {\bf j}(t)
1393 + \chi(t) \right) \\
1394 + \mathsf{A}(t + \delta t) & \leftarrow & \mathrm{rot}\left(\delta t *
1395 + {\bf j}(t + \delta t / 2) \overleftrightarrow{\mathsf{I}}^{-1} \right) \\
1396 + \chi\left(t + \delta t / 2 \right) & \leftarrow & \chi(t) +
1397 + \frac{\delta t}{2 \tau_T^2} \left( \frac{T(t)}{T_{\mathrm{target}}} - 1
1398 + \right) \\
1399 + \eta(t + \delta t / 2) & \leftarrow & \eta(t) + \frac{\delta t \mathcal{V}(t)}{2 N k_B
1400 + T(t) \tau_B^2} \left( P(t) - P_{\mathrm{target}} \right) \\
1401 + {\bf r}(t + \delta t) & \leftarrow & {\bf r}(t) + \delta t \left\{ {\bf
1402 + v}\left(t + \delta t / 2 \right) + \eta(t + \delta t / 2)\left[ {\bf
1403 + r}(t + \delta t) - {\bf R}_0 \right] \right\} \\
1404 + \mathsf{H}(t + \delta t) & \leftarrow & e^{-\delta t \eta(t + \delta t
1405 + / 2)} \mathsf{H}(t)
1406 + \end{eqnarray}
1407 +
1408 + Most of these equations are identical to their counterparts in the NVT
1409 + integrator, but the propagation of positions to time $t + \delta t$
1410 + depends on the positions at the same time.  {\sc oopse} carries out
1411 + this step iteratively (with a limit of 5 passes through the iterative
1412 + loop).  Also, the simulation box $\mathsf{H}$ is scaled uniformly for
1413 + one full time step by an exponential factor that depends on the value
1414 + of $\eta$ at time $t +
1415 + \delta t / 2$.  Reshaping the box uniformly also scales the volume of
1416 + the box by
1417 + \begin{equation}
1418 + \mathcal{V}(t + \delta t) \leftarrow e^{ - 3 \delta t \eta(t + \delta t /2)}
1419 + \mathcal{V}(t)
1420 + \end{equation}
1421 +
1422 + The {\tt doForces} step for the NPTi integrator is exactly the same as
1423 + in both the DLM and NVT integrators.  Once the forces and torques have
1424 + been obtained at the new time step, the velocities can be advanced to
1425 + the same time value.
1426 +
1427 + {\tt moveB:}
1428 + \begin{eqnarray}
1429 + T(t + \delta t) & \leftarrow & \left\{{\bf v}(t + \delta t)\right\},
1430 + \left\{{\bf j}(t + \delta t)\right\} \\
1431 + P(t + \delta t) & \leftarrow & \left\{{\bf r}(t + \delta t)\right\},
1432 + \left\{{\bf v}(t + \delta t)\right\}, \left\{{\bf f}(t + \delta t)\right\} \\
1433 + \chi\left(t + \delta t \right) & \leftarrow & \chi\left(t + \delta t /
1434 + 2 \right) + \frac{\delta t}{2 \tau_T^2} \left( \frac{T(t+\delta
1435 + t)}{T_{\mathrm{target}}} - 1 \right) \\
1436 + \eta(t + \delta t) & \leftarrow & \eta(t + \delta t / 2) +
1437 + \frac{\delta t \mathcal{V}(t + \delta t)}{2 N k_B T(t + \delta t) \tau_B^2}
1438 + \left( P(t + \delta t) - P_{\mathrm{target}}
1439 + \right) \\
1440 + {\bf v}\left(t + \delta t \right)  & \leftarrow & {\bf
1441 + v}\left(t + \delta t / 2 \right) + \frac{\delta t}{2} \left(
1442 + \frac{{\bf f}(t + \delta t)}{m} - {\bf v}(t + \delta t)
1443 + (\chi(t + \delta t) + \eta(t + \delta t)) \right) \\
1444 + {\bf j}\left(t + \delta t \right)  & \leftarrow & {\bf
1445 + j}\left(t + \delta t / 2 \right) + \frac{\delta t}{2} \left( {\bf
1446 + \tau}^b(t + \delta t) - {\bf j}(t + \delta t)
1447 + \chi(t + \delta t) \right)
1448 + \end{eqnarray}
1449 +
1450 + Once again, since ${\bf v}(t + \delta t)$ and ${\bf j}(t + \delta t)$
1451 + are required to caclculate $T(t + \delta t)$, $P(t + \delta t)$, $\chi(t +
1452 + \delta t)$, and $\eta(t + \delta t)$, they indirectly depend on their
1453 + own values at time $t + \delta t$.  {\tt moveB} is therefore done in
1454 + an iterative fashion until $\chi(t + \delta t)$ and $\eta(t + \delta
1455 + t)$ become self-consistent.  The relative tolerance for the
1456 + 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
1458 + consistency check has not been satisfied.
1459 +
1460 + The Melchionna modification of the Nos\'e-Hoover-Andersen algorithm is
1461 + known to conserve a Hamiltonian for the extended system that is, to
1462 + within a constant, identical to the Gibbs free energy,
1463 + \begin{equation}
1464 + H_{\mathrm{NPTi}} = V + K + f k_B T_{\mathrm{target}} \left(
1465 + \frac{\tau_{T}^2 \chi^2(t)}{2} + \int_{0}^{t} \chi(t^\prime) dt^\prime
1466 + \right) + P_{\mathrm{target}} \mathcal{V}(t).
1467 + \end{equation}
1468 + Poor choices of $\delta t$, $\tau_T$, or $\tau_B$ can result in
1469 + non-conservation of $H_{\mathrm{NPTi}}$, so the conserved quantity is
1470 + maintained in the last column of the {\tt .stat} file to allow checks
1471 + on the quality of the integration.  It is also known that this
1472 + algorithm samples the equilibrium distribution for the enthalpy
1473 + (including contributions for the thermostat and barostat),
1474 + \begin{equation}
1475 + H_{\mathrm{NPTi}} = V + K + \frac{f k_B T_{\mathrm{target}}}{2} \left(
1476 + \chi^2 \tau_T^2 + \eta^2 \tau_B^2 \right) +  P_{\mathrm{target}}
1477 + \mathcal{V}(t).
1478 + \end{equation}
1479 +
1480 + Bond constraints are applied at the end of both the {\tt moveA} and
1481 + {\tt moveB} portions of the algorithm.  Details on the constraint
1482 + algorithms are given in section \ref{oopseSec:rattle}.
1483 +
1484 + \subsubsection{\label{sec:NPTf}Constant-pressure integration with a
1485 + flexible box (NPTf)}
1486 +
1487 + There is a relatively simple generalization of the
1488 + Nos\'e-Hoover-Andersen method to include changes in the simulation box
1489 + {\it shape} as well as in the volume of the box.  This method utilizes
1490 + the full $3 \times 3$ pressure tensor and introduces a tensor of
1491 + extended variables ($\overleftrightarrow{\eta}$) to control changes to
1492 + the box shape.  The equations of motion for this method are
1493 + \begin{eqnarray}
1494 + \dot{{\bf r}} & = & {\bf v} + \overleftrightarrow{\eta} \cdot \left( {\bf r} - {\bf R}_0 \right) \\
1495 + \dot{{\bf v}} & = & \frac{{\bf f}}{m} - (\overleftrightarrow{\eta} +
1496 + \chi \mathsf{1}) {\bf v} \\
1497 + \dot{\mathsf{A}} & = & \mathsf{A} \cdot
1498 + \mbox{ skew}\left(\overleftrightarrow{I}^{-1} \cdot {\bf j}\right) \\
1499 + \dot{{\bf j}} & = & {\bf j} \times \left( \overleftrightarrow{I}^{-1}
1500 + \cdot {\bf j} \right) - \mbox{ rot}\left(\mathsf{A}^{T} \cdot \frac{\partial
1501 + V}{\partial \mathsf{A}} \right) - \chi {\bf j} \\
1502 + \dot{\chi} & = & \frac{1}{\tau_{T}^2} \left(
1503 + \frac{T}{T_{\mathrm{target}}} - 1 \right) \\
1504 + \dot{\overleftrightarrow{eta}} & = & \frac{1}{\tau_{B}^2 f k_B
1505 + T_{\mathrm{target}}} V \left( \overleftrightarrow{\mathsf{P}} - P_{\mathrm{target}}\mathsf{1} \right) \\
1506 + \dot{\mathsf{H}} & = &  \overleftrightarrow{\eta} \cdot \mathsf{H}
1507 + \label{eq:melchionna2}
1508 + \end{eqnarray}
1509 +
1510 + Here, $\mathsf{1}$ is the unit matrix and $\overleftrightarrow{\mathsf{P}}$
1511 + is the pressure tensor.  Again, the volume, $\mathcal{V} = \det
1512 + \mathsf{H}$.
1513 +
1514 + The propagation of the equations of motion is nearly identical to the
1515 + NPTi integration:
1516 +
1517 + {\tt moveA:}
1518 + \begin{eqnarray}
1519 + T(t) & \leftarrow & \left\{{\bf v}(t)\right\}, \left\{{\bf j}(t)\right\} \\
1520 + \overleftrightarrow{\mathsf{P}}(t) & \leftarrow & \left\{{\bf r}(t)\right\}, \left\{{\bf v}(t)\right\}, \left\{{\bf f}(t)\right\} \\
1521 + {\bf v}\left(t + \delta t / 2\right)  & \leftarrow & {\bf
1522 + v}(t) + \frac{\delta t}{2} \left( \frac{{\bf f}(t)}{m} -
1523 + \left(\chi(t)\mathsf{1} + \overleftrightarrow{\eta}(t) \right) \cdot
1524 + {\bf v}(t) \right) \\
1525 + {\bf j}\left(t + \delta t / 2 \right)  & \leftarrow & {\bf
1526 + j}(t) + \frac{\delta t}{2} \left( {\bf \tau}^b(t) - {\bf j}(t)
1527 + \chi(t) \right) \\
1528 + \mathsf{A}(t + \delta t) & \leftarrow & \mathrm{rot}\left(\delta t *
1529 + {\bf j}(t + \delta t / 2) \overleftrightarrow{\mathsf{I}}^{-1} \right) \\
1530 + \chi\left(t + \delta t / 2 \right) & \leftarrow & \chi(t) +
1531 + \frac{\delta t}{2 \tau_T^2} \left( \frac{T(t)}{T_{\mathrm{target}}} - 1
1532 + \right) \\
1533 + \overleftrightarrow{\eta}(t + \delta t / 2) & \leftarrow & \overleftrightarrow{\eta}(t) + \frac{\delta t \mathcal{V}(t)}{2 N k_B
1534 + T(t) \tau_B^2} \left( \overleftrightarrow{\mathsf{P}}(t) - P_{\mathrm{target}}\mathsf{1} \right) \\
1535 + {\bf r}(t + \delta t) & \leftarrow & {\bf r}(t) + \delta t \left\{ {\bf
1536 + v}\left(t + \delta t / 2 \right) + \overleftrightarrow{\eta}(t +
1537 + \delta t / 2) \cdot \left[ {\bf
1538 + r}(t + \delta t) - {\bf R}_0 \right] \right\} \\
1539 + \mathsf{H}(t + \delta t) & \leftarrow & \mathsf{H}(t) \cdot e^{-\delta t
1540 + \overleftrightarrow{\eta}(t + \delta t / 2)}
1541 + \end{eqnarray}
1542 + {\sc oopse} uses a power series expansion truncated at second order
1543 + for the exponential operation which scales the simulation box.
1544 +
1545 + The {\tt moveB} portion of the algorithm is largely unchanged from the
1546 + NPTi integrator:
1547 +
1548 + {\tt moveB:}
1549 + \begin{eqnarray}
1550 + T(t + \delta t) & \leftarrow & \left\{{\bf v}(t + \delta t)\right\},
1551 + \left\{{\bf j}(t + \delta t)\right\} \\
1552 + \overleftrightarrow{\mathsf{P}}(t + \delta t) & \leftarrow & \left\{{\bf r}(t + \delta t)\right\},
1553 + \left\{{\bf v}(t + \delta t)\right\}, \left\{{\bf f}(t + \delta t)\right\} \\
1554 + \chi\left(t + \delta t \right) & \leftarrow & \chi\left(t + \delta t /
1555 + 2 \right) + \frac{\delta t}{2 \tau_T^2} \left( \frac{T(t+\delta
1556 + t)}{T_{\mathrm{target}}} - 1 \right) \\
1557 + \overleftrightarrow{\eta}(t + \delta t) & \leftarrow & \overleftrightarrow{\eta}(t + \delta t / 2) +
1558 + \frac{\delta t \mathcal{V}(t + \delta t)}{2 N k_B T(t + \delta t) \tau_B^2}
1559 + \left( \overleftrightarrow{P}(t + \delta t) - P_{\mathrm{target}}\mathsf{1}
1560 + \right) \\
1561 + {\bf v}\left(t + \delta t \right)  & \leftarrow & {\bf
1562 + v}\left(t + \delta t / 2 \right) + \frac{\delta t}{2} \left(
1563 + \frac{{\bf f}(t + \delta t)}{m} -
1564 + (\chi(t + \delta t)\mathsf{1} + \overleftrightarrow{\eta}(t + \delta
1565 + t)) \right) \cdot {\bf v}(t + \delta t) \\
1566 + {\bf j}\left(t + \delta t \right)  & \leftarrow & {\bf
1567 + j}\left(t + \delta t / 2 \right) + \frac{\delta t}{2} \left( {\bf
1568 + \tau}^b(t + \delta t) - {\bf j}(t + \delta t)
1569 + \chi(t + \delta t) \right)
1570 + \end{eqnarray}
1571 +
1572 + The iterative schemes for both {\tt moveA} and {\tt moveB} are
1573 + identical to those described for the NPTi integrator.
1574 +
1575 + The NPTf integrator is known to conserve the following Hamiltonian:
1576 + \begin{equation}
1577 + H_{\mathrm{NPTf}} = V + K + f k_B T_{\mathrm{target}} \left(
1578 + \frac{\tau_{T}^2 \chi^2(t)}{2} + \int_{0}^{t} \chi(t^\prime) dt^\prime
1579 + \right) + P_{\mathrm{target}} \mathcal{V}(t) + \frac{f k_B
1580 + T_{\mathrm{target}}}{2}
1581 + \mathrm{Tr}\left[\overleftrightarrow{\eta}(t)\right]^2 \tau_B^2.
1582 + \end{equation}
1583 +
1584 + This integrator must be used with care, particularly in liquid
1585 + simulations.  Liquids have very small restoring forces in the
1586 + off-diagonal directions, and the simulation box can very quickly form
1587 + elongated and sheared geometries which become smaller than the
1588 + electrostatic or Lennard-Jones cutoff radii.  It finds most use in
1589 + simulating crystals or liquid crystals which assume non-orthorhombic
1590 + geometries.
1591 +
1592 + \subsubsection{\label{nptxyz}Constant pressure in 3 axes (NPTxyz)}
1593 +
1594 + There is one additional extended system integrator which is somewhat
1595 + simpler than the NPTf method described above.  In this case, the three
1596 + axes have independent barostats which each attempt to preserve the
1597 + target pressure along the box walls perpendicular to that particular
1598 + axis.  The lengths of the box axes are allowed to fluctuate
1599 + independently, but the angle between the box axes does not change.
1600 + The equations of motion are identical to those described above, but
1601 + only the {\it diagonal} elements of $\overleftrightarrow{\eta}$ are
1602 + computed.  The off-diagonal elements are set to zero (even when the
1603 + pressure tensor has non-zero off-diagonal elements).
1604 +
1605 + It should be noted that the NPTxyz integrator is {\it not} known to
1606 + preserve any Hamiltonian of interest to the chemical physics
1607 + community.  The integrator is extremely useful, however, in generating
1608 + initial conditions for other integration methods.  It {\it is} suitable
1609 + for use with liquid simulations, or in cases where there is
1610 + orientational anisotropy in the system (i.e. in lipid bilayer
1611 + simulations).
1612 +
1613   \subsection{\label{oopseSec:rattle}The {\sc rattle} Method for Bond
1614          Constraints}
1615  
# Line 1222 | Line 1865 | coefficient can be approximated by
1865   If the time-dependent friction decays rapidly, the static friction
1866   coefficient can be approximated by
1867   \begin{equation}
1868 < \xi^{static}(z)=\int_{0}^{\infty}\langle\delta F(z,t)\delta F(z,0)\rangle dt
1868 > \xi_{\text{static}}(z)=\int_{0}^{\infty}\langle\delta F(z,t)\delta F(z,0)\rangle dt
1869   \end{equation}
1870 < Therefore, the diffusion constant can then be estimated by
1870 > Allowing diffusion constant to then be calculated through the
1871 > Einstein relation:\cite{Marrink94}
1872   \begin{equation}
1873 < D(z)=\frac{k_{B}T}{\xi^{static}(z)}=\frac{(k_{B}T)^{2}}{\int_{0}^{\infty
1873 > D(z)=\frac{k_{B}T}{\xi_{\text{static}}(z)}=\frac{(k_{B}T)^{2}}{\int_{0}^{\infty
1874   }\langle\delta F(z,t)\delta F(z,0)\rangle dt}%
1875   \end{equation}
1876  
# Line 1236 | Line 1880 | resetting the coordinate, we reset the forces of z-con
1880   auto-correlation calculation.\cite{Marrink94} However, simply resetting the
1881   coordinate will move the center of the mass of the whole system. To
1882   avoid this problem, a new method was used in {\sc oopse}. Instead of
1883 < resetting the coordinate, we reset the forces of z-constraint
1883 > resetting the coordinate, we reset the forces of z-constrained
1884   molecules as well as subtract the total constraint forces from the
1885 < rest of the system after force calculation at each time step.
1242 < \begin{align}
1243 < F_{\alpha i}&=0\\
1244 < V_{\alpha i}&=V_{\alpha i}-\frac{\sum\limits_{i}M_{_{\alpha i}}V_{\alpha i}}{\sum\limits_{i}M_{_{\alpha i}}}\\
1245 < F_{\alpha i}&=F_{\alpha i}-\frac{M_{_{\alpha i}}}{\sum\limits_{\alpha}\sum\limits_{i}M_{_{\alpha i}}}\sum\limits_{\beta}F_{\beta}\\
1246 < V_{\alpha i}&=V_{\alpha i}-\frac{\sum\limits_{\alpha}\sum\limits_{i}M_{_{\alpha i}}V_{\alpha i}}{\sum\limits_{\alpha}\sum\limits_{i}M_{_{\alpha i}}}
1247 < \end{align}
1885 > rest of the system after the force calculation at each time step.
1886  
1887 + After the force calculation, define $G_\alpha$ as
1888 + \begin{equation}
1889 + G_{\alpha} = \sum_i F_{\alpha i}
1890 + \label{oopseEq:zc1}
1891 + \end{equation}
1892 + Where $F_{\alpha i}$ is the force in the z direction of atom $i$ in
1893 + z-constrained molecule $\alpha$. The forces of the z constrained
1894 + molecule are then set to:
1895 + \begin{equation}
1896 + F_{\alpha i} = F_{\alpha i} -
1897 +        \frac{m_{\alpha i} G_{\alpha}}{\sum_i m_{\alpha i}}
1898 + \end{equation}
1899 + Here, $m_{\alpha i}$ is the mass of atom $i$ in the z-constrained
1900 + molecule. Having rescaled the forces, the velocities must also be
1901 + rescaled to subtract out any center of mass velocity in the z
1902 + direction.
1903 + \begin{equation}
1904 + v_{\alpha i} = v_{\alpha i} -
1905 +        \frac{\sum_i m_{\alpha i} v_{\alpha i}}{\sum_i m_{\alpha i}}
1906 + \end{equation}
1907 + Where $v_{\alpha i}$ is the velocity of atom $i$ in the z direction.
1908 + Lastly, all of the accumulated z constrained forces must be subtracted
1909 + from the system to keep the system center of mass from drifting.
1910 + \begin{equation}
1911 + F_{\beta i} = F_{\beta i} - \frac{m_{\beta i} \sum_{\alpha} G_{\alpha}}
1912 +        {\sum_{\beta}\sum_i m_{\beta i}}
1913 + \end{equation}
1914 + Where $\beta$ are all of the unconstrained molecules in the system.
1915 +
1916   At the very beginning of the simulation, the molecules may not be at their
1917   constrained positions. To move a z-constrained molecule to its specified
1918   position, a simple harmonic potential is used

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