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# Line 73 | Line 73 | can only be described in cartesian coordinate systems.
73   \subsection{\label{introSection:lagrangian}Lagrangian Mechanics}
74  
75   Newtonian Mechanics suffers from two important limitations: motions
76 < can only be described in cartesian coordinate systems. Moreover, It
77 < become impossible to predict analytically the properties of the
76 > can only be described in cartesian coordinate systems. Moreover, it
77 > becomes impossible to predict analytically the properties of the
78   system even if we know all of the details of the interaction. In
79   order to overcome some of the practical difficulties which arise in
80   attempts to apply Newton's equation to complex system, approximate
# Line 227 | Line 227 | this system is a $6f$ dimensional space. A point, $x =
227   momentum variables. Consider a dynamic system of $f$ particles in a
228   cartesian space, where each of the $6f$ coordinates and momenta is
229   assigned to one of $6f$ mutually orthogonal axes, the phase space of
230 < this system is a $6f$ dimensional space. A point, $x = (q_1 , \ldots
231 < ,q_f ,p_1 , \ldots ,p_f )$, with a unique set of values of $6f$
232 < coordinates and momenta is a phase space vector.
233 <
230 > this system is a $6f$ dimensional space. A point, $x = (\rightarrow
231 > q_1 , \ldots ,\rightarrow q_f ,\rightarrow p_1 , \ldots ,\rightarrow
232 > p_f )$, with a unique set of values of $6f$ coordinates and momenta
233 > is a phase space vector.
234   %%%fix me
235 < A microscopic state or microstate of a classical system is
236 < specification of the complete phase space vector of a system at any
237 < instant in time. An ensemble is defined as a collection of systems
238 < sharing one or more macroscopic characteristics but each being in a
239 < unique microstate. The complete ensemble is specified by giving all
240 < systems or microstates consistent with the common macroscopic
241 < characteristics of the ensemble. Although the state of each
242 < individual system in the ensemble could be precisely described at
243 < any instance in time by a suitable phase space vector, when using
244 < ensembles for statistical purposes, there is no need to maintain
245 < distinctions between individual systems, since the numbers of
246 < systems at any time in the different states which correspond to
247 < different regions of the phase space are more interesting. Moreover,
248 < in the point of view of statistical mechanics, one would prefer to
249 < use ensembles containing a large enough population of separate
250 < members so that the numbers of systems in such different states can
251 < be regarded as changing continuously as we traverse different
252 < regions of the phase space. The condition of an ensemble at any time
235 >
236 > In statistical mechanics, the condition of an ensemble at any time
237   can be regarded as appropriately specified by the density $\rho$
238   with which representative points are distributed over the phase
239   space. The density distribution for an ensemble with $f$ degrees of
# Line 752 | Line 736 | to its symmetric property,
736   \begin{equation}
737   \varphi _h^{ - 1} = \varphi _{ - h}.
738   \label{introEquation:timeReversible}
739 < \end{equation},appendixFig:architecture
739 > \end{equation}
740  
741   \subsubsection{\label{introSection:exampleSplittingMethod}\textbf{Examples of the Splitting Method}}
742   The classical equation for a system consisting of interacting
# Line 1114 | Line 1098 | computer simulation. Figure
1098   (r)}{\rho}.
1099   \]
1100   Note that the delta function can be replaced by a histogram in
1101 < computer simulation. Figure
1102 < \ref{introFigure:pairDistributionFunction} shows a typical pair
1103 < distribution function for the liquid argon system. The occurrence of
1120 < several peaks in the plot of $g(r)$ suggests that it is more likely
1121 < to find particles at certain radial values than at others. This is a
1122 < result of the attractive interaction at such distances. Because of
1123 < the strong repulsive forces at short distance, the probability of
1124 < locating particles at distances less than about 3.7{\AA} from each
1125 < other is essentially zero.
1101 > computer simulation. Peaks in $g(r)$ represent solvent shells, and
1102 > the height of these peaks gradually decreases to 1 as the liquid of
1103 > large distance approaches the bulk density.
1104  
1127 %\begin{figure}
1128 %\centering
1129 %\includegraphics[width=\linewidth]{pdf.eps}
1130 %\caption[Pair distribution function for the liquid argon
1131 %]{Pair distribution function for the liquid argon}
1132 %\label{introFigure:pairDistributionFunction}
1133 %\end{figure}
1105  
1106   \subsubsection{\label{introSection:timeDependentProperties}\textbf{Time-dependent
1107   Properties}}
# Line 1270 | Line 1241 | $T_{\star}SO(3)$. However, it turns out that under sym
1241   \]
1242  
1243   Unfortunately, this constraint manifold is not the cotangent bundle
1244 < $T_{\star}SO(3)$. However, it turns out that under symplectic
1244 > $T^* SO(3)$ which can be consider as a symplectic manifold on Lie
1245 > rotation group $SO(3)$. However, it turns out that under symplectic
1246   transformation, the cotangent space and the phase space are
1247   diffeomorphic. By introducing
1248   \[
# Line 1308 | Line 1280 | introduced to rewrite the equations of motion,
1280   introduced to rewrite the equations of motion,
1281   \begin{equation}
1282   \begin{array}{l}
1283 < \mathop \Pi \limits^ \bullet   = J^{ - 1} \Pi ^T \Pi  + Q^T \sum\limits_i {F_i (q,Q)X_i^T }  - \Lambda  \\
1284 < \mathop Q\limits^{{\rm{   }} \bullet }  = Q\Pi {\rm{ }}J^{ - 1}  \\
1283 > \dot \Pi  = J^{ - 1} \Pi ^T \Pi  + Q^T \sum\limits_i {F_i (q,Q)X_i^T }  - \Lambda  \\
1284 > \dot Q  = Q\Pi {\rm{ }}J^{ - 1}  \\
1285   \end{array}
1286   \label{introEqaution:RBMotionPI}
1287   \end{equation}
# Line 1339 | Line 1311 | matrix,
1311   \]
1312   Using \ref{introEqaution:RBMotionPI}, one can construct a skew
1313   matrix,
1314 < \begin{equation}
1315 < (\mathop \Pi \limits^ \bullet   - \mathop \Pi \limits^ {\bullet  ^T}
1316 < ){\rm{ }} = {\rm{ }}(\Pi  - \Pi ^T ){\rm{ }}(J^{ - 1} \Pi  + \Pi J^{
1317 < - 1} ) + \sum\limits_i {[Q^T F_i (r,Q)X_i^T  - X_i F_i (r,Q)^T Q]} -
1318 < (\Lambda  - \Lambda ^T ) . \label{introEquation:skewMatrixPI}
1319 < \end{equation}
1314 >
1315 > \begin{eqnarray*}
1316 > (\dot \Pi  - \dot \Pi ^T ){\rm{ }} = {\rm{ }}(\Pi  - \Pi ^T ){\rm{
1317 > }}(J^{ - 1} \Pi  + \Pi J^{ - 1} ) + \sum\limits_i {[Q^T F_i
1318 > (r,Q)X_i^T  - X_i F_i (r,Q)^T Q]}  - (\Lambda  - \Lambda ^T ).
1319 > \label{introEquation:skewMatrixPI}
1320 > \end{eqnarray*}
1321 >
1322   Since $\Lambda$ is symmetric, the last term of Equation
1323   \ref{introEquation:skewMatrixPI} is zero, which implies the Lagrange
1324   multiplier $\Lambda$ is absent from the equations of motion. This
# Line 1476 | Line 1450 | kinetic energy are listed in the below table,
1450   The equations of motion corresponding to potential energy and
1451   kinetic energy are listed in the below table,
1452   \begin{table}
1453 < \caption{Equations of motion due to Potential and Kinetic Energies}
1453 > \caption{EQUATIONS OF MOTION DUE TO POTENTIAL AND KINETIC ENERGIES}
1454   \begin{center}
1455   \begin{tabular}{|l|l|}
1456    \hline

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