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Revision 903 by tim, Wed Jan 7 03:53:53 2004 UTC vs.
Revision 904 by tim, Wed Jan 7 15:21:00 2004 UTC

# Line 8 | Line 8
8   %TCIDATA{Version=5.00.0.2552}
9   %TCIDATA{CSTFile=40 LaTeX article.cst}
10   %TCIDATA{Created=Friday, September 19, 2003 08:29:53}
11 < %TCIDATA{LastRevised=Tuesday, January 06, 2004 17:35:24}
11 > %TCIDATA{LastRevised=Wednesday, January 07, 2004 10:20:42}
12   %TCIDATA{<META NAME="GraphicsSave" CONTENT="32">}
13   %TCIDATA{<META NAME="SaveForMode" CONTENT="1">}
14   %TCIDATA{<META NAME="DocumentShell" CONTENT="Standard LaTeX\Standard LaTeX Article">}
# Line 40 | Line 40
40   \begin{document}
41   \section{\label{Sec:pbc}Periodic Boundary Conditions}
42  
43 < \textit{Periodic boundary conditions} are widely used  to simulate
44 < truly macroscopic systems with a relatively small number of
45 < particles. Simulation box is replicated throughout space to form
46 < an infinite lattice. During the simulation, when a particle moves
47 < in the primary cell, its periodic image particles in other boxes
48 < move in exactly the same direction with exactly the same
49 < orientation.Thus, as a particle leaves the primary cell, one of
50 < its images will enter through the opposite face.If the simulation
51 < box is large enough to avoid "feeling" the symmetric of the
52 < periodic lattice,the surface effect could be ignored. For the time
53 < being, Cubic and parallelepiped are the available periodic cells
54 < used in OOPSE.
55 < \bigskip In OOPSE, we use the matrix instead of vector to describe the property
56 < of the simulation box. Therefore, not only the size of the
57 < simulation box could be changed during the simulation, but also
58 < the shape of it.
59 < The transformation from box space vector
60 < $\overrightarrow{s}$to its corresponding real space vector
61 < $\overrightarrow{r}$ is defined by
43 > \textit{Periodic boundary conditions} are widely used to simulate truly
44 > macroscopic systems with a relatively small number of particles. Simulation
45 > box is replicated throughout space to form an infinite lattice. During the
46 > simulation, when a particle moves in the primary cell, its periodic image
47 > particles in other boxes move in exactly the same direction with exactly the
48 > same orientation.Thus, as a particle leaves the primary cell, one of its
49 > images will enter through the opposite face.If the simulation box is large
50 > enough to avoid "feeling" the symmetric of the periodic lattice,the surface
51 > effect could be ignored. Cubic and parallelepiped are the available periodic
52 > cells. \bigskip In OOPSE, we use the matrix instead of the vector to describe
53 > the property of the simulation box. Therefore, not only the size of the
54 > simulation box could be changed during the simulation, but also the shape of
55 > it. The transformation from box space vector $\overrightarrow{s}$ to its
56 > corresponding real space vector $\overrightarrow{r}$ is defined by
57   \begin{equation}
58   \overrightarrow{r}=H\overrightarrow{s}%
59   \end{equation}
60  
66 where $H=(h_{x},h_{y},h_{z})$ is a transformation matrix made up
67 of the three box axis vector. h_{x},h_{y} and h_{z} represent the
68 sides of the simulation box respectively. Thus H matrix becomes
61  
62 + where $H=(h_{x},h_{y},h_{z})$ is a transformation matrix made up of the three
63 + box axis vectors. $h_{x},h_{y}$ and $h_{z}$ represent the sides of the
64 + simulation box respectively.
65  
66 < To find the minimum image, we need to convert the real vector to
67 < its corresponding vector in box space first,
73 < \bigskip
66 > To find the minimum image, we need to convert the real vector to its
67 > corresponding vector in box space first, \bigskip%
68   \begin{equation}
69   \overrightarrow{s}=H^{-1}\overrightarrow{r}%
70   \end{equation}
71 < And then, each element of \overrightarrow{s} is casted to lie
72 < between -0.5 to 0.5
71 > And then, each element of $\overrightarrow{s}$ is casted to lie between -0.5
72 > to 0.5,
73   \begin{equation}
74 < \s_{i}=s_{i}-round(s_{i})%
74 > s_{i}^{\prime}=s_{i}-round(s_{i})
75   \end{equation}
76 < where
76 > where%
77 >
78   \begin{equation}
79 < \round(x)=(x+0.5)(x-0.5)%
79 > round(x)=\lfloor{x+0.5}\rfloor\text{ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ }if\text{
80 > }x\geqslant0
81   \end{equation}
82 + %
83  
84 < For example, round(3.6)=4, round(3.1) = 3, round(-3.6) = -4,
85 < round(-3.1)=-3.
84 > \begin{equation}
85 > round(x)=\lceil{x-0.5}\rceil\text{ \ \ \ \ \ \ \ \ \ \ \ \ \ \ }if\text{ }x<0
86 > \end{equation}
87  
88 +
89 + For example, $round(3.6)=4$,$round(3.1)=3$, $round(-3.6)=-4$, $round(-3.1)=-3$.
90 +
91 + Finally, we could get the minimum image by transforming back to real space,%
92 +
93   \begin{equation}
94 < \overrightarrow{s}=H^{-1}\overrightarrow{r}%
94 > \overrightarrow{r^{\prime}}=H^{-1}\overrightarrow{s^{\prime}}%
95   \end{equation}
96  
97  
98  
99 < \end{document}
99 > \end{document}

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