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# Line 505 | Line 505 | system,$\frac{{dx}}{{dt}} = f(x) \label{introEquation:
505   \subsection{\label{introSection:exactFlow}Exact Propagator}
506  
507   Let $x(t)$ be the exact solution of the ODE
508 < system,$\frac{{dx}}{{dt}} = f(x) \label{introEquation:ODE}$, we can
509 < define its exact propagator(solution) $\varphi_\tau$
508 > system,
509 > \begin{equation}
510 > \frac{{dx}}{{dt}} = f(x), \label{introEquation:ODE}
511 > \end{equation} we can
512 > define its exact propagator $\varphi_\tau$:
513   \[ x(t+\tau)
514   =\varphi_\tau(x(t))
515   \]
# Line 578 | Line 581 | Using the chain rule, one may obtain,
581   \]
582   Using the chain rule, one may obtain,
583   \[
584 < \sum\limits_i {\frac{{dG}}{{dx_i }}} f_i (x) = f \dot \nabla G,
584 > \sum\limits_i {\frac{{dG}}{{dx_i }}} f_i (x) = f \cdot \nabla G,
585   \]
586   which is the condition for conserved quantities. For a canonical
587   Hamiltonian system, the time evolution of an arbitrary smooth
# Line 703 | Line 706 | symplectic(\ref{introEquation:SymplecticFlowCompositio
706   \end{align}
707   where $F(t)$ is the force at time $t$. This integration scheme is
708   known as \emph{velocity verlet} which is
709 < symplectic(\ref{introEquation:SymplecticFlowComposition}),
710 < time-reversible(\ref{introEquation:timeReversible}) and
711 < volume-preserving (\ref{introEquation:volumePreserving}). These
709 > symplectic(Eq.~\ref{introEquation:SymplecticFlowComposition}),
710 > time-reversible(Eq.~\ref{introEquation:timeReversible}) and
711 > volume-preserving (Eq.~\ref{introEquation:volumePreserving}). These
712   geometric properties attribute to its long-time stability and its
713   popularity in the community. However, the most commonly used
714   velocity verlet integration scheme is written as below,
# Line 747 | Line 750 | operators(\ref{introEquation:exponentialOperator}) ass
750  
751   The Baker-Campbell-Hausdorff formula can be used to determine the
752   local error of a splitting method in terms of the commutator of the
753 < operators(\ref{introEquation:exponentialOperator}) associated with
753 > operators(Eq.~\ref{introEquation:exponentialOperator}) associated with
754   the sub-propagator. For operators $hX$ and $hY$ which are associated
755   with $\varphi_1(t)$ and $\varphi_2(t)$ respectively , we have
756   \begin{equation}
# Line 831 | Line 834 | will discuss issues of production runs.
834   These three individual steps will be covered in the following
835   sections. Sec.~\ref{introSec:initialSystemSettings} deals with the
836   initialization of a simulation. Sec.~\ref{introSection:production}
837 < will discuss issues of production runs.
837 > discusses issues of production runs.
838   Sec.~\ref{introSection:Analysis} provides the theoretical tools for
839   analysis of trajectories.
840  
# Line 899 | Line 902 | as a means to arrive at an equilibrated structure in a
902   properties \textit{etc}, become independent of time. Strictly
903   speaking, minimization and heating are not necessary, provided the
904   equilibration process is long enough. However, these steps can serve
905 < as a means to arrive at an equilibrated structure in an effective
905 > as a mean to arrive at an equilibrated structure in an effective
906   way.
907  
908   \subsection{\label{introSection:production}Production}
# Line 969 | Line 972 | r_{ij})}{r_{ij}}\right\}. \label{introEquation:shifted
972   V(r_{ij})= \frac{q_i q_j \textrm{erfc}(\alpha
973   r_{ij})}{r_{ij}}-\lim_{r_{ij}\rightarrow
974   R_\textrm{c}}\left\{\frac{q_iq_j \textrm{erfc}(\alpha
975 < r_{ij})}{r_{ij}}\right\}. \label{introEquation:shiftedCoulomb}
975 > r_{ij})}{r_{ij}}\right\}, \label{introEquation:shiftedCoulomb}
976   \end{equation}
977   where $\alpha$ is the convergence parameter. Due to the lack of
978   inherent periodicity and rapid convergence,this method is extremely
# Line 986 | Line 989 | Recently, advanced visualization technique have become
989  
990   \subsection{\label{introSection:Analysis} Analysis}
991  
992 < Recently, advanced visualization technique have become applied to
992 > Recently, advanced visualization techniques have been applied to
993   monitor the motions of molecules. Although the dynamics of the
994   system can be described qualitatively from animation, quantitative
995   trajectory analysis is more useful. According to the principles of
# Line 1056 | Line 1059 | function is called an \emph{autocorrelation function}.
1059   \label{introEquation:timeCorrelationFunction}
1060   \end{equation}
1061   If $A$ and $B$ refer to same variable, this kind of correlation
1062 < function is called an \emph{autocorrelation function}. One example
1063 < of an auto correlation function is the velocity auto-correlation
1062 > functions are called \emph{autocorrelation functions}. One example
1063 > of auto correlation function is the velocity auto-correlation
1064   function which is directly related to transport properties of
1065   molecular liquids:
1066   \[
# Line 1108 | Line 1111 | Unfortunately, this approach uses a nonseparable Hamil
1111   computational penalty and the loss of angular momentum conservation
1112   still remain. A singularity-free representation utilizing
1113   quaternions was developed by Evans in 1977\cite{Evans1977}.
1114 < Unfortunately, this approach uses a nonseparable Hamiltonian
1115 < resulting from the quaternion representation, which prevents the
1114 > Unfortunately, this approach used a nonseparable Hamiltonian
1115 > resulting from the quaternion representation, which prevented the
1116   symplectic algorithm from being utilized. Another different approach
1117   is to apply holonomic constraints to the atoms belonging to the
1118   rigid body. Each atom moves independently under the normal forces
# Line 1152 | Line 1155 | Equation (\ref{introEquation:motionHamiltonianCoordina
1155   Q^T Q = 1, \label{introEquation:orthogonalConstraint}
1156   \end{equation}
1157   which is used to ensure the rotation matrix's unitarity. Using
1158 < Equation (\ref{introEquation:motionHamiltonianCoordinate},
1159 < \ref{introEquation:motionHamiltonianMomentum}), one can write down
1158 > Eq.~\ref{introEquation:motionHamiltonianCoordinate} and Eq.~
1159 > \ref{introEquation:motionHamiltonianMomentum}, one can write down
1160   the equations of motion,
1161   \begin{eqnarray}
1162   \frac{{dq}}{{dt}} & = & \frac{p}{m}, \label{introEquation:RBMotionPosition}\\
# Line 1185 | Line 1188 | the mechanical system subject to a holonomic constrain
1188   \[
1189   \tilde Q = Q,\tilde P = \frac{1}{2}\left( {P - QP^T Q} \right),
1190   \]
1191 < the mechanical system subject to a holonomic constraint manifold $M$
1191 > the mechanical system subjected to a holonomic constraint manifold $M$
1192   can be re-formulated as a Hamiltonian system on the cotangent space
1193   \[
1194   T^* SO(3) = \left\{ {(\tilde Q,\tilde P):\tilde Q^T \tilde Q =
# Line 1374 | Line 1377 | energy and potential energy,$H = T(p,\pi ) + V(q,Q)$.
1377   Splitting for Rigid Body}
1378  
1379   The Hamiltonian of rigid body can be separated in terms of kinetic
1380 < energy and potential energy,$H = T(p,\pi ) + V(q,Q)$. The equations
1380 > energy and potential energy, $H = T(p,\pi ) + V(q,Q)$. The equations
1381   of motion corresponding to potential energy and kinetic energy are
1382 < listed in the below table,
1382 > listed in Table~\ref{introTable:rbEquations}
1383   \begin{table}
1384   \caption{EQUATIONS OF MOTION DUE TO POTENTIAL AND KINETIC ENERGIES}
1385 + \label{introTable:rbEquations}
1386   \begin{center}
1387   \begin{tabular}{|l|l|}
1388    \hline

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