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# Line 315 | Line 315 | partition function like,
315   isolated and conserve energy, Microcanonical ensemble(NVE) has a
316   partition function like,
317   \begin{equation}
318 < \Omega (N,V,E) = e^{\beta TS}
319 < \label{introEqaution:NVEPartition}.
318 > \Omega (N,V,E) = e^{\beta TS} \label{introEquation:NVEPartition}.
319   \end{equation}
320   A canonical ensemble(NVT)is an ensemble of systems, each of which
321   can share its energy with a large heat reservoir. The distribution
# Line 571 | Line 570 | The most obvious change being that matrix $J$ now depe
570   \dot x = J(x)\nabla _x H \label{introEquation:poissonHamiltonian}
571   \end{equation}
572   The most obvious change being that matrix $J$ now depends on $x$.
574 The free rigid body is an example of Poisson system (actually a
575 Lie-Poisson system) with Hamiltonian function of angular kinetic
576 energy.
577 \begin{equation}
578 J(\pi ) = \left( {\begin{array}{*{20}c}
579   0 & {\pi _3 } & { - \pi _2 }  \\
580   { - \pi _3 } & 0 & {\pi _1 }  \\
581   {\pi _2 } & { - \pi _1 } & 0  \\
582 \end{array}} \right)
583 \end{equation}
573  
585 \begin{equation}
586 H = \frac{1}{2}\left( {\frac{{\pi _1^2 }}{{I_1 }} + \frac{{\pi _2^2
587 }}{{I_2 }} + \frac{{\pi _3^2 }}{{I_3 }}} \right)
588 \end{equation}
589
574   \subsection{\label{introSection:exactFlow}Exact Flow}
575  
576   Let $x(t)$ be the exact solution of the ODE system,
# Line 635 | Line 619 | a \emph{symplectic} flow if it satisfies,
619   Let $\varphi$ be the flow of Hamiltonian vector field, $\varphi$ is
620   a \emph{symplectic} flow if it satisfies,
621   \begin{equation}
622 < '\varphi^T J '\varphi = J.
622 > {\varphi '}^T J \varphi ' = J.
623   \end{equation}
624   According to Liouville's theorem, the symplectic volume is invariant
625   under a Hamiltonian flow, which is the basis for classical
# Line 643 | Line 627 | symplectomorphism. As to the Poisson system,
627   field on a symplectic manifold can be shown to be a
628   symplectomorphism. As to the Poisson system,
629   \begin{equation}
630 < '\varphi ^T J '\varphi  = J \circ \varphi
630 > {\varphi '}^T J \varphi ' = J \circ \varphi
631   \end{equation}
632   is the property must be preserved by the integrator.
633  
# Line 661 | Line 645 | only if $ h \circ \varphi ^{ - 1}  = \varphi  \circ h
645   In other words, the flow of this vector field is reversible if and
646   only if $ h \circ \varphi ^{ - 1}  = \varphi  \circ h $.
647  
648 < When designing any numerical methods, one should always try to
648 > A \emph{first integral}, or conserved quantity of a general
649 > differential function is a function $ G:R^{2d}  \to R^d $ which is
650 > constant for all solutions of the ODE $\frac{{dx}}{{dt}} = f(x)$ ,
651 > \[
652 > \frac{{dG(x(t))}}{{dt}} = 0.
653 > \]
654 > Using chain rule, one may obtain,
655 > \[
656 > \sum\limits_i {\frac{{dG}}{{dx_i }}} f_i (x) = f \bullet \nabla G,
657 > \]
658 > which is the condition for conserving \emph{first integral}. For a
659 > canonical Hamiltonian system, the time evolution of an arbitrary
660 > smooth function $G$ is given by,
661 > \begin{equation}
662 > \begin{array}{c}
663 > \frac{{dG(x(t))}}{{dt}} = [\nabla _x G(x(t))]^T \dot x(t) \\
664 >  = [\nabla _x G(x(t))]^T J\nabla _x H(x(t)). \\
665 > \end{array}
666 > \label{introEquation:firstIntegral1}
667 > \end{equation}
668 > Using poisson bracket notion, Equation
669 > \ref{introEquation:firstIntegral1} can be rewritten as
670 > \[
671 > \frac{d}{{dt}}G(x(t)) = \left\{ {G,H} \right\}(x(t)).
672 > \]
673 > Therefore, the sufficient condition for $G$ to be the \emph{first
674 > integral} of a Hamiltonian system is
675 > \[
676 > \left\{ {G,H} \right\} = 0.
677 > \]
678 > As well known, the Hamiltonian (or energy) H of a Hamiltonian system
679 > is a \emph{first integral}, which is due to the fact $\{ H,H\}  =
680 > 0$.
681 >
682 >
683 > When designing any numerical methods, one should always try to
684   preserve the structural properties of the original ODE and its flow.
685  
686   \subsection{\label{introSection:constructionSymplectic}Construction of Symplectic Methods}
# Line 685 | Line 704 | Runge--Kutta methods have been developed to overcome t
704   ordinary implicit Runge-Kutta methods are not suitable for
705   Hamiltonian system. Recently, various high-order explicit
706   Runge--Kutta methods have been developed to overcome this
707 < instability \cite{}. However, due to computational penalty involved
708 < in implementing the Runge-Kutta methods, they do not attract too
709 < much attention from Molecular Dynamics community. Instead, splitting
710 < have been widely accepted since they exploit natural decompositions
711 < of the system\cite{Tuckerman92}.
707 > instability. However, due to computational penalty involved in
708 > implementing the Runge-Kutta methods, they do not attract too much
709 > attention from Molecular Dynamics community. Instead, splitting have
710 > been widely accepted since they exploit natural decompositions of
711 > the system\cite{Tuckerman92}.
712  
713   \subsubsection{\label{introSection:splittingMethod}Splitting Method}
714  
# Line 736 | Line 755 | splitting gives a second-order decomposition,
755   splitting gives a second-order decomposition,
756   \begin{equation}
757   \varphi _h  = \varphi _{1,h/2}  \circ \varphi _{2,h}  \circ \varphi
758 < _{1,h/2} ,
740 < \label{introEqaution:secondOrderSplitting}
758 > _{1,h/2} , \label{introEquation:secondOrderSplitting}
759   \end{equation}
760   which has a local error proportional to $h^3$. Sprang splitting's
761   popularity in molecular simulation community attribute to its
762   symmetric property,
763   \begin{equation}
764   \varphi _h^{ - 1} = \varphi _{ - h}.
765 < \lable{introEquation:timeReversible}
765 > \label{introEquation:timeReversible}
766   \end{equation}
767  
768   \subsubsection{\label{introSection:exampleSplittingMethod}Example of Splitting Method}
# Line 802 | Line 820 | integrator, the \emph{position verlet} integrator, can
820   \frac{{\Delta t}}{{2m}}\dot q(0)} \right], %
821   \label{introEquation:positionVerlet1} \\%
822   %
823 < q(\Delta t) = q(0) + \frac{{\Delta t}}{2}\left[ {\dot q(0) + \dot
823 > q(\Delta t) &= q(0) + \frac{{\Delta t}}{2}\left[ {\dot q(0) + \dot
824   q(\Delta t)} \right]. %
825   \label{introEquation:positionVerlet1}
826   \end{align}
# Line 828 | Line 846 | can obtain
846   \]
847   Applying Baker-Campbell-Hausdorff formula to Sprang splitting, we
848   can obtain
849 < \begin{eqnarray}
849 > \begin{eqnarray*}
850   \exp (h X/2)\exp (h Y)\exp (h X/2) & = & \exp (h X + h Y + h^2
851 < [X,Y]/4 + h^2 [Y,X]/4 \\ & & \mbox{} + h^2 [X,X]/8 + h^2 [Y,Y]/8 +
852 < h^3 [Y,[Y,X]]/12 - h^3 [X,[X,Y]]/24 +  \ldots )
853 < \end{eqnarray}
851 > [X,Y]/4 + h^2 [Y,X]/4 \\ & & \mbox{} + h^2 [X,X]/8 + h^2 [Y,Y]/8 \\
852 > & & \mbox{} + h^3 [Y,[Y,X]]/12 - h^3 [X,[X,Y]]/24 & & \mbox{} +
853 > \ldots )
854 > \end{eqnarray*}
855   Since \[ [X,Y] + [Y,X] = 0\] and \[ [X,X] = 0\], the dominant local
856   error of Spring splitting is proportional to $h^3$. The same
857   procedure can be applied to general splitting,  of the form
# Line 871 | Line 890 | dynamical information.
890  
891   \subsection{\label{introSec:mdInit}Initialization}
892  
893 + \subsection{\label{introSec:forceEvaluation}Force Evaluation}
894 +
895   \subsection{\label{introSection:mdIntegration} Integration of the Equations of Motion}
896  
897   \section{\label{introSection:rigidBody}Dynamics of Rigid Bodies}
898  
899 < A rigid body is a body in which the distance between any two given
900 < points of a rigid body remains constant regardless of external
901 < forces exerted on it. A rigid body therefore conserves its shape
902 < during its motion.
899 > Rigid bodies are frequently involved in the modeling of different
900 > areas, from engineering, physics, to chemistry. For example,
901 > missiles and vehicle are usually modeled by rigid bodies.  The
902 > movement of the objects in 3D gaming engine or other physics
903 > simulator is governed by the rigid body dynamics. In molecular
904 > simulation, rigid body is used to simplify the model in
905 > protein-protein docking study{\cite{Gray03}}.
906  
907 < Applications of dynamics of rigid bodies.
908 <
909 < \subsection{\label{introSection:lieAlgebra}Lie Algebra}
910 <
911 < \subsection{\label{introSection:DLMMotionEquation}The Euler Equations of Rigid Body Motion}
912 <
913 < \subsection{\label{introSection:otherRBMotionEquation}Other Formulations for Rigid Body Motion}
907 > It is very important to develop stable and efficient methods to
908 > integrate the equations of motion of orientational degrees of
909 > freedom. Euler angles are the nature choice to describe the
910 > rotational degrees of freedom. However, due to its singularity, the
911 > numerical integration of corresponding equations of motion is very
912 > inefficient and inaccurate. Although an alternative integrator using
913 > different sets of Euler angles can overcome this difficulty\cite{},
914 > the computational penalty and the lost of angular momentum
915 > conservation still remain. A singularity free representation
916 > utilizing quaternions was developed by Evans in 1977. Unfortunately,
917 > this approach suffer from the nonseparable Hamiltonian resulted from
918 > quaternion representation, which prevents the symplectic algorithm
919 > to be utilized. Another different approach is to apply holonomic
920 > constraints to the atoms belonging to the rigid body. Each atom
921 > moves independently under the normal forces deriving from potential
922 > energy and constraint forces which are used to guarantee the
923 > rigidness. However, due to their iterative nature, SHAKE and Rattle
924 > algorithm converge very slowly when the number of constraint
925 > increases.
926  
927 < \section{\label{introSection:correlationFunctions}Correlation Functions}
927 > The break through in geometric literature suggests that, in order to
928 > develop a long-term integration scheme, one should preserve the
929 > symplectic structure of the flow. Introducing conjugate momentum to
930 > rotation matrix $A$ and re-formulating Hamiltonian's equation, a
931 > symplectic integrator, RSHAKE, was proposed to evolve the
932 > Hamiltonian system in a constraint manifold by iteratively
933 > satisfying the orthogonality constraint $A_t A = 1$. An alternative
934 > method using quaternion representation was developed by Omelyan.
935 > However, both of these methods are iterative and inefficient. In
936 > this section, we will present a symplectic Lie-Poisson integrator
937 > for rigid body developed by Dullweber and his
938 > coworkers\cite{Dullweber1997} in depth.
939 >
940 > \subsection{\label{introSection:constrainedHamiltonianRB}Constrained Hamiltonian for Rigid Body}
941 > The motion of the rigid body is Hamiltonian with the Hamiltonian
942 > function
943 > \begin{equation}
944 > H = \frac{1}{2}(p^T m^{ - 1} p) + \frac{1}{2}tr(PJ^{ - 1} P) +
945 > V(q,Q) + \frac{1}{2}tr[(QQ^T  - 1)\Lambda ].
946 > \label{introEquation:RBHamiltonian}
947 > \end{equation}
948 > Here, $q$ and $Q$  are the position and rotation matrix for the
949 > rigid-body, $p$ and $P$  are conjugate momenta to $q$  and $Q$ , and
950 > $J$, a diagonal matrix, is defined by
951 > \[
952 > I_{ii}^{ - 1}  = \frac{1}{2}\sum\limits_{i \ne j} {J_{jj}^{ - 1} }
953 > \]
954 > where $I_{ii}$ is the diagonal element of the inertia tensor. This
955 > constrained Hamiltonian equation subjects to a holonomic constraint,
956 > \begin{equation}
957 > Q^T Q = 1$, \label{introEquation:orthogonalConstraint}
958 > \end{equation}
959 > which is used to ensure rotation matrix's orthogonality.
960 > Differentiating \ref{introEquation:orthogonalConstraint} and using
961 > Equation \ref{introEquation:RBMotionMomentum}, one may obtain,
962 > \begin{equation}
963 > Q^T PJ^{ - 1}  + J^{ - 1} P^T Q = 0 . \\
964 > \label{introEquation:RBFirstOrderConstraint}
965 > \end{equation}
966 >
967 > Using Equation (\ref{introEquation:motionHamiltonianCoordinate},
968 > \ref{introEquation:motionHamiltonianMomentum}), one can write down
969 > the equations of motion,
970 > \[
971 > \begin{array}{c}
972 > \frac{{dq}}{{dt}} = \frac{p}{m} \label{introEquation:RBMotionPosition}\\
973 > \frac{{dp}}{{dt}} =  - \nabla _q V(q,Q) \label{introEquation:RBMotionMomentum}\\
974 > \frac{{dQ}}{{dt}} = PJ^{ - 1}  \label{introEquation:RBMotionRotation}\\
975 > \frac{{dP}}{{dt}} =  - \nabla _Q V(q,Q) - 2Q\Lambda . \label{introEquation:RBMotionP}\\
976 > \end{array}
977 > \]
978 >
979 > In general, there are two ways to satisfy the holonomic constraints.
980 > We can use constraint force provided by lagrange multiplier on the
981 > normal manifold to keep the motion on constraint space. Or we can
982 > simply evolve the system in constraint manifold. The two method are
983 > proved to be equivalent. The holonomic constraint and equations of
984 > motions define a constraint manifold for rigid body
985 > \[
986 > M = \left\{ {(Q,P):Q^T Q = 1,Q^T PJ^{ - 1}  + J^{ - 1} P^T Q = 0}
987 > \right\}.
988 > \]
989 >
990 > Unfortunately, this constraint manifold is not the cotangent bundle
991 > $T_{\star}SO(3)$. However, it turns out that under symplectic
992 > transformation, the cotangent space and the phase space are
993 > diffeomorphic. Introducing
994 > \[
995 > \tilde Q = Q,\tilde P = \frac{1}{2}\left( {P - QP^T Q} \right),
996 > \]
997 > the mechanical system subject to a holonomic constraint manifold $M$
998 > can be re-formulated as a Hamiltonian system on the cotangent space
999 > \[
1000 > T^* SO(3) = \left\{ {(\tilde Q,\tilde P):\tilde Q^T \tilde Q =
1001 > 1,\tilde Q^T \tilde PJ^{ - 1}  + J^{ - 1} P^T \tilde Q = 0} \right\}
1002 > \]
1003 >
1004 > For a body fixed vector $X_i$ with respect to the center of mass of
1005 > the rigid body, its corresponding lab fixed vector $X_0^{lab}$  is
1006 > given as
1007 > \begin{equation}
1008 > X_i^{lab} = Q X_i + q.
1009 > \end{equation}
1010 > Therefore, potential energy $V(q,Q)$ is defined by
1011 > \[
1012 > V(q,Q) = V(Q X_0 + q).
1013 > \]
1014 > Hence, the force and torque are given by
1015 > \[
1016 > \nabla _q V(q,Q) = F(q,Q) = \sum\limits_i {F_i (q,Q)},
1017 > \]
1018 > and
1019 > \[
1020 > \nabla _Q V(q,Q) = F(q,Q)X_i^t
1021 > \]
1022 > respectively.
1023 >
1024 > As a common choice to describe the rotation dynamics of the rigid
1025 > body, angular momentum on body frame $\Pi  = Q^t P$ is introduced to
1026 > rewrite the equations of motion,
1027 > \begin{equation}
1028 > \begin{array}{l}
1029 > \mathop \Pi \limits^ \bullet   = J^{ - 1} \Pi ^T \Pi  + Q^T \sum\limits_i {F_i (q,Q)X_i^T }  - \Lambda  \\
1030 > \mathop Q\limits^{{\rm{   }} \bullet }  = Q\Pi {\rm{ }}J^{ - 1}  \\
1031 > \end{array}
1032 > \label{introEqaution:RBMotionPI}
1033 > \end{equation}
1034 > , as well as holonomic constraints,
1035 > \[
1036 > \begin{array}{l}
1037 > \Pi J^{ - 1}  + J^{ - 1} \Pi ^t  = 0 \\
1038 > Q^T Q = 1 \\
1039 > \end{array}
1040 > \]
1041 >
1042 > For a vector $v(v_1 ,v_2 ,v_3 ) \in R^3$ and a matrix $\hat v \in
1043 > so(3)^ \star$, the hat-map isomorphism,
1044 > \begin{equation}
1045 > v(v_1 ,v_2 ,v_3 ) \Leftrightarrow \hat v = \left(
1046 > {\begin{array}{*{20}c}
1047 >   0 & { - v_3 } & {v_2 }  \\
1048 >   {v_3 } & 0 & { - v_1 }  \\
1049 >   { - v_2 } & {v_1 } & 0  \\
1050 > \end{array}} \right),
1051 > \label{introEquation:hatmapIsomorphism}
1052 > \end{equation}
1053 > will let us associate the matrix products with traditional vector
1054 > operations
1055 > \[
1056 > \hat vu = v \times u
1057 > \]
1058 >
1059 > Using \ref{introEqaution:RBMotionPI}, one can construct a skew
1060 > matrix,
1061 > \begin{equation}
1062 > (\mathop \Pi \limits^ \bullet   - \mathop \Pi \limits^ \bullet  ^T
1063 > ){\rm{ }} = {\rm{ }}(\Pi  - \Pi ^T ){\rm{ }}(J^{ - 1} \Pi  + \Pi J^{
1064 > - 1} ) + \sum\limits_i {[Q^T F_i (r,Q)X_i^T  - X_i F_i (r,Q)^T Q]} -
1065 > (\Lambda  - \Lambda ^T ) . \label{introEquation:skewMatrixPI}
1066 > \end{equation}
1067 > Since $\Lambda$ is symmetric, the last term of Equation
1068 > \ref{introEquation:skewMatrixPI} is zero, which implies the Lagrange
1069 > multiplier $\Lambda$ is absent from the equations of motion. This
1070 > unique property eliminate the requirement of iterations which can
1071 > not be avoided in other methods\cite{}.
1072 >
1073 > Applying hat-map isomorphism, we obtain the equation of motion for
1074 > angular momentum on body frame
1075 > \begin{equation}
1076 > \dot \pi  = \pi  \times I^{ - 1} \pi  + \sum\limits_i {\left( {Q^T
1077 > F_i (r,Q)} \right) \times X_i }.
1078 > \label{introEquation:bodyAngularMotion}
1079 > \end{equation}
1080 > In the same manner, the equation of motion for rotation matrix is
1081 > given by
1082 > \[
1083 > \dot Q = Qskew(I^{ - 1} \pi )
1084 > \]
1085 >
1086 > \subsection{\label{introSection:SymplecticFreeRB}Symplectic
1087 > Lie-Poisson Integrator for Free Rigid Body}
1088 >
1089 > If there is not external forces exerted on the rigid body, the only
1090 > contribution to the rotational is from the kinetic potential (the
1091 > first term of \ref{ introEquation:bodyAngularMotion}). The free
1092 > rigid body is an example of Lie-Poisson system with Hamiltonian
1093 > function
1094 > \begin{equation}
1095 > T^r (\pi ) = T_1 ^r (\pi _1 ) + T_2^r (\pi _2 ) + T_3^r (\pi _3 )
1096 > \label{introEquation:rotationalKineticRB}
1097 > \end{equation}
1098 > where $T_i^r (\pi _i ) = \frac{{\pi _i ^2 }}{{2I_i }}$ and
1099 > Lie-Poisson structure matrix,
1100 > \begin{equation}
1101 > J(\pi ) = \left( {\begin{array}{*{20}c}
1102 >   0 & {\pi _3 } & { - \pi _2 }  \\
1103 >   { - \pi _3 } & 0 & {\pi _1 }  \\
1104 >   {\pi _2 } & { - \pi _1 } & 0  \\
1105 > \end{array}} \right)
1106 > \end{equation}
1107 > Thus, the dynamics of free rigid body is governed by
1108 > \begin{equation}
1109 > \frac{d}{{dt}}\pi  = J(\pi )\nabla _\pi  T^r (\pi )
1110 > \end{equation}
1111 >
1112 > One may notice that each $T_i^r$ in Equation
1113 > \ref{introEquation:rotationalKineticRB} can be solved exactly. For
1114 > instance, the equations of motion due to $T_1^r$ are given by
1115 > \begin{equation}
1116 > \frac{d}{{dt}}\pi  = R_1 \pi ,\frac{d}{{dt}}Q = QR_1
1117 > \label{introEqaution:RBMotionSingleTerm}
1118 > \end{equation}
1119 > where
1120 > \[ R_1  = \left( {\begin{array}{*{20}c}
1121 >   0 & 0 & 0  \\
1122 >   0 & 0 & {\pi _1 }  \\
1123 >   0 & { - \pi _1 } & 0  \\
1124 > \end{array}} \right).
1125 > \]
1126 > The solutions of Equation \ref{introEqaution:RBMotionSingleTerm} is
1127 > \[
1128 > \pi (\Delta t) = e^{\Delta tR_1 } \pi (0),Q(\Delta t) =
1129 > Q(0)e^{\Delta tR_1 }
1130 > \]
1131 > with
1132 > \[
1133 > e^{\Delta tR_1 }  = \left( {\begin{array}{*{20}c}
1134 >   0 & 0 & 0  \\
1135 >   0 & {\cos \theta _1 } & {\sin \theta _1 }  \\
1136 >   0 & { - \sin \theta _1 } & {\cos \theta _1 }  \\
1137 > \end{array}} \right),\theta _1  = \frac{{\pi _1 }}{{I_1 }}\Delta t.
1138 > \]
1139 > To reduce the cost of computing expensive functions in e^{\Delta
1140 > tR_1 }, we can use Cayley transformation,
1141 > \[
1142 > e^{\Delta tR_1 }  \approx (1 - \Delta tR_1 )^{ - 1} (1 + \Delta tR_1
1143 > )
1144 > \]
1145  
1146 + The flow maps for $T_2^r$ and $T_2^r$ can be found in the same
1147 + manner.
1148 +
1149 + In order to construct a second-order symplectic method, we split the
1150 + angular kinetic Hamiltonian function can into five terms
1151 + \[
1152 + T^r (\pi ) = \frac{1}{2}T_1 ^r (\pi _1 ) + \frac{1}{2}T_2^r (\pi _2
1153 + ) + T_3^r (\pi _3 ) + \frac{1}{2}T_2^r (\pi _2 ) + \frac{1}{2}T_1 ^r
1154 + (\pi _1 )
1155 + \].
1156 + Concatenating flows corresponding to these five terms, we can obtain
1157 + an symplectic integrator,
1158 + \[
1159 + \varphi _{\Delta t,T^r }  = \varphi _{\Delta t/2,\pi _1 }  \circ
1160 + \varphi _{\Delta t/2,\pi _2 }  \circ \varphi _{\Delta t,\pi _3 }
1161 + \circ \varphi _{\Delta t/2,\pi _2 }  \circ \varphi _{\Delta t/2,\pi
1162 + _1 }.
1163 + \]
1164 +
1165 + The non-canonical Lie-Poisson bracket ${F, G}$ of two function
1166 + $F(\pi )$ and $G(\pi )$ is defined by
1167 + \[
1168 + \{ F,G\} (\pi ) = [\nabla _\pi  F(\pi )]^T J(\pi )\nabla _\pi  G(\pi
1169 + )
1170 + \]
1171 + If the Poisson bracket of a function $F$ with an arbitrary smooth
1172 + function $G$ is zero, $F$ is a \emph{Casimir}, which is the
1173 + conserved quantity in Poisson system. We can easily verify that the
1174 + norm of the angular momentum, $\parallel \pi
1175 + \parallel$, is a \emph{Casimir}. Let$ F(\pi ) = S(\frac{{\parallel
1176 + \pi \parallel ^2 }}{2})$ for an arbitrary function $ S:R \to R$ ,
1177 + then by the chain rule
1178 + \[
1179 + \nabla _\pi  F(\pi ) = S'(\frac{{\parallel \pi \parallel ^2
1180 + }}{2})\pi
1181 + \]
1182 + Thus $ [\nabla _\pi  F(\pi )]^T J(\pi ) =  - S'(\frac{{\parallel \pi
1183 + \parallel ^2 }}{2})\pi  \times \pi  = 0 $. This explicit
1184 + Lie-Poisson integrator is found to be extremely efficient and stable
1185 + which can be explained by the fact the small angle approximation is
1186 + used and the norm of the angular momentum is conserved.
1187 +
1188 + \subsection{\label{introSection:RBHamiltonianSplitting} Hamiltonian
1189 + Splitting for Rigid Body}
1190 +
1191 + The Hamiltonian of rigid body can be separated in terms of kinetic
1192 + energy and potential energy,
1193 + \[
1194 + H = T(p,\pi ) + V(q,Q)
1195 + \]
1196 + The equations of motion corresponding to potential energy and
1197 + kinetic energy are listed in the below table,
1198 + \begin{center}
1199 + \begin{tabular}{|l|l|}
1200 +  \hline
1201 +  % after \\: \hline or \cline{col1-col2} \cline{col3-col4} ...
1202 +  Potential & Kinetic \\
1203 +  $\frac{{dq}}{{dt}} = \frac{p}{m}$ & $\frac{d}{{dt}}q = p$ \\
1204 +  $\frac{d}{{dt}}p =  - \frac{{\partial V}}{{\partial q}}$ & $ \frac{d}{{dt}}p = 0$ \\
1205 +  $\frac{d}{{dt}}Q = 0$ & $ \frac{d}{{dt}}Q = Qskew(I^{ - 1} j)$ \\
1206 +  $ \frac{d}{{dt}}\pi  = \sum\limits_i {\left( {Q^T F_i (r,Q)} \right) \times X_i }$ & $\frac{d}{{dt}}\pi  = \pi  \times I^{ - 1} \pi$\\
1207 +  \hline
1208 + \end{tabular}
1209 + \end{center}
1210 + A second-order symplectic method is now obtained by the composition
1211 + of the flow maps,
1212 + \[
1213 + \varphi _{\Delta t}  = \varphi _{\Delta t/2,V}  \circ \varphi
1214 + _{\Delta t,T}  \circ \varphi _{\Delta t/2,V}.
1215 + \]
1216 + Moreover, \varphi _{\Delta t/2,V} can be divided into two sub-flows
1217 + which corresponding to force and torque respectively,
1218 + \[
1219 + \varphi _{\Delta t/2,V}  = \varphi _{\Delta t/2,F}  \circ \varphi
1220 + _{\Delta t/2,\tau }.
1221 + \]
1222 + Since the associated operators of $\varphi _{\Delta t/2,F} $ and
1223 + $\circ \varphi _{\Delta t/2,\tau }$ are commuted, the composition
1224 + order inside \varphi _{\Delta t/2,V} does not matter.
1225 +
1226 + Furthermore, kinetic potential can be separated to translational
1227 + kinetic term, $T^t (p)$, and rotational kinetic term, $T^r (\pi )$,
1228 + \begin{equation}
1229 + T(p,\pi ) =T^t (p) + T^r (\pi ).
1230 + \end{equation}
1231 + where $ T^t (p) = \frac{1}{2}p^T m^{ - 1} p $ and $T^r (\pi )$ is
1232 + defined by \ref{introEquation:rotationalKineticRB}. Therefore, the
1233 + corresponding flow maps are given by
1234 + \[
1235 + \varphi _{\Delta t,T}  = \varphi _{\Delta t,T^t }  \circ \varphi
1236 + _{\Delta t,T^r }.
1237 + \]
1238 + Finally, we obtain the overall symplectic flow maps for free moving
1239 + rigid body
1240 + \begin{equation}
1241 + \begin{array}{c}
1242 + \varphi _{\Delta t}  = \varphi _{\Delta t/2,F}  \circ \varphi _{\Delta t/2,\tau }  \\
1243 +  \circ \varphi _{\Delta t,T^t }  \circ \varphi _{\Delta t/2,\pi _1 }  \circ \varphi _{\Delta t/2,\pi _2 }  \circ \varphi _{\Delta t,\pi _3 }  \circ \varphi _{\Delta t/2,\pi _2 }  \circ \varphi _{\Delta t/2,\pi _1 }  \\
1244 +  \circ \varphi _{\Delta t/2,\tau }  \circ \varphi _{\Delta t/2,F}  .\\
1245 + \end{array}
1246 + \label{introEquation:overallRBFlowMaps}
1247 + \end{equation}
1248 +
1249   \section{\label{introSection:langevinDynamics}Langevin Dynamics}
1250  
1251   \subsection{\label{introSection:LDIntroduction}Introduction and application of Langevin Dynamics}
# Line 1097 | Line 1453 | Body}
1453  
1454   \subsection{\label{introSection:centersRigidBody}Centers of Rigid
1455   Body}
1456 +
1457 + \section{\label{introSection:correlationFunctions}Correlation Functions}

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