208 |
|
The thermodynamic behaviors and properties of Molecular Dynamics |
209 |
|
simulation are governed by the principle of Statistical Mechanics. |
210 |
|
The following section will give a brief introduction to some of the |
211 |
< |
Statistical Mechanics concepts and theorem presented in this |
211 |
> |
Statistical Mechanics concepts and theorems presented in this |
212 |
|
dissertation. |
213 |
|
|
214 |
|
\subsection{\label{introSection:ensemble}Phase Space and Ensemble} |
372 |
|
Liouville's theorem can be expressed in a variety of different forms |
373 |
|
which are convenient within different contexts. For any two function |
374 |
|
$F$ and $G$ of the coordinates and momenta of a system, the Poisson |
375 |
< |
bracket ${F, G}$ is defined as |
375 |
> |
bracket $\{F,G\}$ is defined as |
376 |
|
\begin{equation} |
377 |
|
\left\{ {F,G} \right\} = \sum\limits_i {\left( {\frac{{\partial |
378 |
|
F}}{{\partial q_i }}\frac{{\partial G}}{{\partial p_i }} - |
439 |
|
\section{\label{introSection:geometricIntegratos}Geometric Integrators} |
440 |
|
A variety of numerical integrators have been proposed to simulate |
441 |
|
the motions of atoms in MD simulation. They usually begin with |
442 |
< |
initial conditionals and move the objects in the direction governed |
442 |
> |
initial conditions and move the objects in the direction governed |
443 |
|
by the differential equations. However, most of them ignore the |
444 |
|
hidden physical laws contained within the equations. Since 1990, |
445 |
|
geometric integrators, which preserve various phase-flow invariants |
459 |
|
\emph{smooth manifold}) is a manifold on which it is possible to |
460 |
|
apply calculus\cite{Hirsch1997}. A \emph{symplectic manifold} is |
461 |
|
defined as a pair $(M, \omega)$ which consists of a |
462 |
< |
\emph{differentiable manifold} $M$ and a close, non-degenerated, |
462 |
> |
\emph{differentiable manifold} $M$ and a close, non-degenerate, |
463 |
|
bilinear symplectic form, $\omega$. A symplectic form on a vector |
464 |
|
space $V$ is a function $\omega(x, y)$ which satisfies |
465 |
|
$\omega(\lambda_1x_1+\lambda_2x_2, y) = \lambda_1\omega(x_1, y)+ |
479 |
|
\begin{equation} |
480 |
|
\dot x = f(x) |
481 |
|
\end{equation} |
482 |
< |
where $x = x(q,p)^T$, this system is a canonical Hamiltonian, if |
482 |
> |
where $x = x(q,p)$, this system is a canonical Hamiltonian, if |
483 |
|
$f(x) = J\nabla _x H(x)$. Here, $H = H (q, p)$ is Hamiltonian |
484 |
|
function and $J$ is the skew-symmetric matrix |
485 |
|
\begin{equation} |
527 |
|
\begin{equation} |
528 |
|
\varphi _\tau = \varphi _{ - \tau }^{ - 1}. |
529 |
|
\end{equation} |
530 |
< |
The exact propagator can also be written in terms of operator, |
530 |
> |
The exact propagator can also be written as an operator, |
531 |
|
\begin{equation} |
532 |
|
\varphi _\tau (x) = e^{\tau \sum\limits_i {f_i (x)\frac{\partial |
533 |
|
}{{\partial x_i }}} } (x) \equiv \exp (\tau f)(x). |
729 |
|
|
730 |
|
\item Use the half step velocities to move positions one whole step, $\Delta t$. |
731 |
|
|
732 |
< |
\item Evaluate the forces at the new positions, $\mathbf{q}(\Delta t)$, and use the new forces to complete the velocity move. |
732 |
> |
\item Evaluate the forces at the new positions, $q(\Delta t)$, and use the new forces to complete the velocity move. |
733 |
|
|
734 |
|
\item Repeat from step 1 with the new position, velocities, and forces assuming the roles of the initial values. |
735 |
|
\end{enumerate} |
868 |
|
minimization to find a more reasonable conformation. Several energy |
869 |
|
minimization methods have been developed to exploit the energy |
870 |
|
surface and to locate the local minimum. While converging slowly |
871 |
< |
near the minimum, steepest descent method is extremely robust when |
871 |
> |
near the minimum, the steepest descent method is extremely robust when |
872 |
|
systems are strongly anharmonic. Thus, it is often used to refine |
873 |
|
structures from crystallographic data. Relying on the Hessian, |
874 |
|
advanced methods like Newton-Raphson converge rapidly to a local |
887 |
|
temperature. Beginning at a lower temperature and gradually |
888 |
|
increasing the temperature by assigning larger random velocities, we |
889 |
|
end up setting the temperature of the system to a final temperature |
890 |
< |
at which the simulation will be conducted. In heating phase, we |
890 |
> |
at which the simulation will be conducted. In the heating phase, we |
891 |
|
should also keep the system from drifting or rotating as a whole. To |
892 |
|
do this, the net linear momentum and angular momentum of the system |
893 |
|
is shifted to zero after each resampling from the Maxwell -Boltzman |
954 |
|
in simulations. The Ewald summation, in which the slowly decaying |
955 |
|
Coulomb potential is transformed into direct and reciprocal sums |
956 |
|
with rapid and absolute convergence, has proved to minimize the |
957 |
< |
periodicity artifacts in liquid simulations. Taking the advantages |
958 |
< |
of the fast Fourier transform (FFT) for calculating discrete Fourier |
957 |
> |
periodicity artifacts in liquid simulations. Taking advantage |
958 |
> |
of fast Fourier transform (FFT) techniques for calculating discrete Fourier |
959 |
|
transforms, the particle mesh-based |
960 |
|
methods\cite{Hockney1981,Shimada1993, Luty1994} are accelerated from |
961 |
|
$O(N^{3/2})$ to $O(N logN)$. An alternative approach is the |
1059 |
|
\label{introEquation:timeCorrelationFunction} |
1060 |
|
\end{equation} |
1061 |
|
If $A$ and $B$ refer to same variable, this kind of correlation |
1062 |
< |
functions are called \emph{autocorrelation functions}. One example |
1063 |
< |
of auto correlation function is the velocity auto-correlation |
1062 |
> |
functions are called \emph{autocorrelation functions}. One typical example is the velocity autocorrelation |
1063 |
|
function which is directly related to transport properties of |
1064 |
|
molecular liquids: |
1065 |
< |
\[ |
1065 |
> |
\begin{equation} |
1066 |
|
D = \frac{1}{3}\int\limits_0^\infty {\left\langle {v(t) \cdot v(0)} |
1067 |
|
\right\rangle } dt |
1068 |
< |
\] |
1068 |
> |
\end{equation} |
1069 |
|
where $D$ is diffusion constant. Unlike the velocity autocorrelation |
1070 |
|
function, which is averaged over time origins and over all the |
1071 |
|
atoms, the dipole autocorrelation functions is calculated for the |
1072 |
|
entire system. The dipole autocorrelation function is given by: |
1073 |
< |
\[ |
1073 |
> |
\begin{equation} |
1074 |
|
c_{dipole} = \left\langle {u_{tot} (t) \cdot u_{tot} (t)} |
1075 |
|
\right\rangle |
1076 |
< |
\] |
1076 |
> |
\end{equation} |
1077 |
|
Here $u_{tot}$ is the net dipole of the entire system and is given |
1078 |
|
by |
1079 |
< |
\[ |
1079 |
> |
\begin{equation} |
1080 |
|
u_{tot} (t) = \sum\limits_i {u_i (t)}. |
1081 |
< |
\] |
1081 |
> |
\end{equation} |
1082 |
|
In principle, many time correlation functions can be related to |
1083 |
|
Fourier transforms of the infrared, Raman, and inelastic neutron |
1084 |
|
scattering spectra of molecular liquids. In practice, one can |
1085 |
|
extract the IR spectrum from the intensity of the molecular dipole |
1086 |
|
fluctuation at each frequency using the following relationship: |
1087 |
< |
\[ |
1087 |
> |
\begin{equation} |
1088 |
|
\hat c_{dipole} (v) = \int_{ - \infty }^\infty {c_{dipole} (t)e^{ - |
1089 |
|
i2\pi vt} dt}. |
1090 |
< |
\] |
1090 |
> |
\end{equation} |
1091 |
|
|
1092 |
|
\section{\label{introSection:rigidBody}Dynamics of Rigid Bodies} |
1093 |
|
|
1094 |
|
Rigid bodies are frequently involved in the modeling of different |
1095 |
< |
areas, from engineering, physics, to chemistry. For example, |
1095 |
> |
areas, including engineering, physics and chemistry. For example, |
1096 |
|
missiles and vehicles are usually modeled by rigid bodies. The |
1097 |
|
movement of the objects in 3D gaming engines or other physics |
1098 |
|
simulators is governed by rigid body dynamics. In molecular |
1134 |
|
Dullweber and his coworkers\cite{Dullweber1997} in depth. |
1135 |
|
|
1136 |
|
\subsection{\label{introSection:constrainedHamiltonianRB}Constrained Hamiltonian for Rigid Bodies} |
1137 |
< |
The motion of a rigid body is Hamiltonian with the Hamiltonian |
1139 |
< |
function |
1137 |
> |
The Hamiltonian of a rigid body is given by |
1138 |
|
\begin{equation} |
1139 |
|
H = \frac{1}{2}(p^T m^{ - 1} p) + \frac{1}{2}tr(PJ^{ - 1} P) + |
1140 |
|
V(q,Q) + \frac{1}{2}tr[(QQ^T - 1)\Lambda ]. |
1346 |
|
\circ \varphi _{\Delta t/2,\pi _2 } \circ \varphi _{\Delta t/2,\pi |
1347 |
|
_1 }. |
1348 |
|
\] |
1349 |
< |
The non-canonical Lie-Poisson bracket ${F, G}$ of two function |
1352 |
< |
$F(\pi )$ and $G(\pi )$ is defined by |
1349 |
> |
The non-canonical Lie-Poisson bracket $\{F, G\}$ of two functions $F(\pi )$ and $G(\pi )$ is defined by |
1350 |
|
\[ |
1351 |
|
\{ F,G\} (\pi ) = [\nabla _\pi F(\pi )]^T J(\pi )\nabla _\pi G(\pi |
1352 |
|
). |
1355 |
|
function $G$ is zero, $F$ is a \emph{Casimir}, which is the |
1356 |
|
conserved quantity in Poisson system. We can easily verify that the |
1357 |
|
norm of the angular momentum, $\parallel \pi |
1358 |
< |
\parallel$, is a \emph{Casimir}\cite{McLachlan1993}. Let$ F(\pi ) = S(\frac{{\parallel |
1358 |
> |
\parallel$, is a \emph{Casimir}\cite{McLachlan1993}. Let $F(\pi ) = S(\frac{{\parallel |
1359 |
|
\pi \parallel ^2 }}{2})$ for an arbitrary function $ S:R \to R$ , |
1360 |
|
then by the chain rule |
1361 |
|
\[ |
1376 |
|
The Hamiltonian of rigid body can be separated in terms of kinetic |
1377 |
|
energy and potential energy, $H = T(p,\pi ) + V(q,Q)$. The equations |
1378 |
|
of motion corresponding to potential energy and kinetic energy are |
1379 |
< |
listed in Table~\ref{introTable:rbEquations} |
1379 |
> |
listed in Table~\ref{introTable:rbEquations}. |
1380 |
|
\begin{table} |
1381 |
|
\caption{EQUATIONS OF MOTION DUE TO POTENTIAL AND KINETIC ENERGIES} |
1382 |
|
\label{introTable:rbEquations} |
1434 |
|
As an alternative to newtonian dynamics, Langevin dynamics, which |
1435 |
|
mimics a simple heat bath with stochastic and dissipative forces, |
1436 |
|
has been applied in a variety of studies. This section will review |
1437 |
< |
the theory of Langevin dynamics. A brief derivation of generalized |
1437 |
> |
the theory of Langevin dynamics. A brief derivation of the generalized |
1438 |
|
Langevin equation will be given first. Following that, we will |
1439 |
< |
discuss the physical meaning of the terms appearing in the equation |
1443 |
< |
as well as the calculation of friction tensor from hydrodynamics |
1444 |
< |
theory. |
1439 |
> |
discuss the physical meaning of the terms appearing in the equation. |
1440 |
|
|
1441 |
|
\subsection{\label{introSection:generalizedLangevinDynamics}Derivation of Generalized Langevin Equation} |
1442 |
|
|
1445 |
|
environment, has been widely used in quantum chemistry and |
1446 |
|
statistical mechanics. One of the successful applications of |
1447 |
|
Harmonic bath model is the derivation of the Generalized Langevin |
1448 |
< |
Dynamics (GLE). Lets consider a system, in which the degree of |
1448 |
> |
Dynamics (GLE). Consider a system, in which the degree of |
1449 |
|
freedom $x$ is assumed to couple to the bath linearly, giving a |
1450 |
|
Hamiltonian of the form |
1451 |
|
\begin{equation} |
1456 |
|
with this degree of freedom, $H_B$ is a harmonic bath Hamiltonian, |
1457 |
|
\[ |
1458 |
|
H_B = \sum\limits_{\alpha = 1}^N {\left\{ {\frac{{p_\alpha ^2 |
1459 |
< |
}}{{2m_\alpha }} + \frac{1}{2}m_\alpha \omega _\alpha ^2 } |
1459 |
> |
}}{{2m_\alpha }} + \frac{1}{2}m_\alpha x_\alpha ^2 } |
1460 |
|
\right\}} |
1461 |
|
\] |
1462 |
|
where the index $\alpha$ runs over all the bath degrees of freedom, |
1509 |
|
L(f(t)) \equiv F(p) = \int_0^\infty {f(t)e^{ - pt} dt} |
1510 |
|
\] |
1511 |
|
where $p$ is real and $L$ is called the Laplace Transform |
1512 |
< |
Operator. Below are some important properties of Laplace transform |
1512 |
> |
Operator. Below are some important properties of the Laplace transform |
1513 |
|
\begin{eqnarray*} |
1514 |
|
L(x + y) & = & L(x) + L(y) \\ |
1515 |
|
L(ax) & = & aL(x) \\ |
1578 |
|
(t)\dot x(t - \tau )d\tau } + R(t) |
1579 |
|
\label{introEuqation:GeneralizedLangevinDynamics} |
1580 |
|
\end{equation} |
1581 |
< |
which is known as the \emph{generalized Langevin equation}. |
1581 |
> |
which is known as the \emph{generalized Langevin equation} (GLE). |
1582 |
|
|
1583 |
|
\subsubsection{\label{introSection:randomForceDynamicFrictionKernel}\textbf{Random Force and Dynamic Friction Kernel}} |
1584 |
|
|
1585 |
|
One may notice that $R(t)$ depends only on initial conditions, which |
1586 |
|
implies it is completely deterministic within the context of a |
1587 |
|
harmonic bath. However, it is easy to verify that $R(t)$ is totally |
1588 |
< |
uncorrelated to $x$ and $\dot x$,$\left\langle {x(t)R(t)} |
1588 |
> |
uncorrelated to $x$ and $\dot x$, $\left\langle {x(t)R(t)} |
1589 |
|
\right\rangle = 0, \left\langle {\dot x(t)R(t)} \right\rangle = |
1590 |
|
0.$ This property is what we expect from a truly random process. As |
1591 |
|
long as the model chosen for $R(t)$ was a gaussian distribution in |
1614 |
|
infinitely quickly to motions in the system. Thus, $\xi (t)$ can be |
1615 |
|
taken as a $delta$ function in time: |
1616 |
|
\[ |
1617 |
< |
\xi (t) = 2\xi _0 \delta (t) |
1617 |
> |
\xi (t) = 2\xi _0 \delta (t). |
1618 |
|
\] |
1619 |
|
Hence, the convolution integral becomes |
1620 |
|
\[ |
1639 |
|
q_\alpha (t) = x_\alpha (t) - \frac{1}{{m_\alpha \omega _\alpha |
1640 |
|
^2 }}x(0), |
1641 |
|
\] |
1642 |
< |
we can rewrite $R(T)$ as |
1642 |
> |
we can rewrite $R(t)$ as |
1643 |
|
\[ |
1644 |
|
R(t) = \sum\limits_{\alpha = 1}^N {g_\alpha q_\alpha (t)}. |
1645 |
|
\] |