| 27 |
|
\end{equation} |
| 28 |
|
A point mass interacting with other bodies moves with the |
| 29 |
|
acceleration along the direction of the force acting on it. Let |
| 30 |
< |
$F_ij$ be the force that particle $i$ exerts on particle $j$, and |
| 31 |
< |
$F_ji$ be the force that particle $j$ exerts on particle $i$. |
| 30 |
> |
$F_{ij}$ be the force that particle $i$ exerts on particle $j$, and |
| 31 |
> |
$F_{ji}$ be the force that particle $j$ exerts on particle $i$. |
| 32 |
|
Newton¡¯s third law states that |
| 33 |
|
\begin{equation} |
| 34 |
< |
F_ij = -F_ji |
| 34 |
> |
F_{ij} = -F_{ji} |
| 35 |
|
\label{introEquation:newtonThirdLaw} |
| 36 |
|
\end{equation} |
| 37 |
|
|
| 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 |
| 393 |
|
\begin{equation} |
| 394 |
|
\rho \propto e^{ - \beta H} |
| 395 |
|
\label{introEquation:densityAndHamiltonian} |
| 396 |
+ |
\end{equation} |
| 397 |
+ |
|
| 398 |
+ |
\subsubsection{\label{introSection:phaseSpaceConservation}Conservation of Phase Space} |
| 399 |
+ |
Lets consider a region in the phase space, |
| 400 |
+ |
\begin{equation} |
| 401 |
+ |
\delta v = \int { \ldots \int {dq_1 } ...dq_f dp_1 } ..dp_f . |
| 402 |
+ |
\end{equation} |
| 403 |
+ |
If this region is small enough, the density $\rho$ can be regarded |
| 404 |
+ |
as uniform over the whole phase space. Thus, the number of phase |
| 405 |
+ |
points inside this region is given by, |
| 406 |
+ |
\begin{equation} |
| 407 |
+ |
\delta N = \rho \delta v = \rho \int { \ldots \int {dq_1 } ...dq_f |
| 408 |
+ |
dp_1 } ..dp_f. |
| 409 |
+ |
\end{equation} |
| 410 |
+ |
|
| 411 |
+ |
\begin{equation} |
| 412 |
+ |
\frac{{d(\delta N)}}{{dt}} = \frac{{d\rho }}{{dt}}\delta v + \rho |
| 413 |
+ |
\frac{d}{{dt}}(\delta v) = 0. |
| 414 |
+ |
\end{equation} |
| 415 |
+ |
With the help of stationary assumption |
| 416 |
+ |
(\ref{introEquation:stationary}), we obtain the principle of the |
| 417 |
+ |
\emph{conservation of extension in phase space}, |
| 418 |
+ |
\begin{equation} |
| 419 |
+ |
\frac{d}{{dt}}(\delta v) = \frac{d}{{dt}}\int { \ldots \int {dq_1 } |
| 420 |
+ |
...dq_f dp_1 } ..dp_f = 0. |
| 421 |
+ |
\label{introEquation:volumePreserving} |
| 422 |
|
\end{equation} |
| 423 |
|
|
| 424 |
+ |
\subsubsection{\label{introSection:liouvilleInOtherForms}Liouville's Theorem in Other Forms} |
| 425 |
+ |
|
| 426 |
|
Liouville's theorem can be expresses in a variety of different forms |
| 427 |
|
which are convenient within different contexts. For any two function |
| 428 |
|
$F$ and $G$ of the coordinates and momenta of a system, the Poisson |
| 458 |
|
\label{introEquation:liouvilleTheoremInOperator} |
| 459 |
|
\end{equation} |
| 460 |
|
|
| 434 |
– |
|
| 461 |
|
\subsection{\label{introSection:ergodic}The Ergodic Hypothesis} |
| 462 |
|
|
| 463 |
|
Various thermodynamic properties can be calculated from Molecular |
| 586 |
|
}}{{I_2 }} + \frac{{\pi _3^2 }}{{I_3 }}} \right) |
| 587 |
|
\end{equation} |
| 588 |
|
|
| 589 |
< |
\subsection{\label{introSection:geometricProperties}Geometric Properties} |
| 589 |
> |
\subsection{\label{introSection:exactFlow}Exact Flow} |
| 590 |
> |
|
| 591 |
|
Let $x(t)$ be the exact solution of the ODE system, |
| 592 |
|
\begin{equation} |
| 593 |
|
\frac{{dx}}{{dt}} = f(x) \label{introEquation:ODE} |
| 597 |
|
x(t+\tau) =\varphi_\tau(x(t)) |
| 598 |
|
\] |
| 599 |
|
where $\tau$ is a fixed time step and $\varphi$ is a map from phase |
| 600 |
< |
space to itself. In most cases, it is not easy to find the exact |
| 574 |
< |
flow $\varphi_\tau$. Instead, we use a approximate map, $\psi_\tau$, |
| 575 |
< |
which is usually called integrator. The order of an integrator |
| 576 |
< |
$\psi_\tau$ is $p$, if the Taylor series of $\psi_\tau$ agree to |
| 577 |
< |
order $p$, |
| 600 |
> |
space to itself. The flow has the continuous group property, |
| 601 |
|
\begin{equation} |
| 602 |
+ |
\varphi _{\tau _1 } \circ \varphi _{\tau _2 } = \varphi _{\tau _1 |
| 603 |
+ |
+ \tau _2 } . |
| 604 |
+ |
\end{equation} |
| 605 |
+ |
In particular, |
| 606 |
+ |
\begin{equation} |
| 607 |
+ |
\varphi _\tau \circ \varphi _{ - \tau } = I |
| 608 |
+ |
\end{equation} |
| 609 |
+ |
Therefore, the exact flow is self-adjoint, |
| 610 |
+ |
\begin{equation} |
| 611 |
+ |
\varphi _\tau = \varphi _{ - \tau }^{ - 1}. |
| 612 |
+ |
\end{equation} |
| 613 |
+ |
The exact flow can also be written in terms of the of an operator, |
| 614 |
+ |
\begin{equation} |
| 615 |
+ |
\varphi _\tau (x) = e^{\tau \sum\limits_i {f_i (x)\frac{\partial |
| 616 |
+ |
}{{\partial x_i }}} } (x) \equiv \exp (\tau f)(x). |
| 617 |
+ |
\label{introEquation:exponentialOperator} |
| 618 |
+ |
\end{equation} |
| 619 |
+ |
|
| 620 |
+ |
In most cases, it is not easy to find the exact flow $\varphi_\tau$. |
| 621 |
+ |
Instead, we use a approximate map, $\psi_\tau$, which is usually |
| 622 |
+ |
called integrator. The order of an integrator $\psi_\tau$ is $p$, if |
| 623 |
+ |
the Taylor series of $\psi_\tau$ agree to order $p$, |
| 624 |
+ |
\begin{equation} |
| 625 |
|
\psi_tau(x) = x + \tau f(x) + O(\tau^{p+1}) |
| 626 |
|
\end{equation} |
| 627 |
|
|
| 628 |
+ |
\subsection{\label{introSection:geometricProperties}Geometric Properties} |
| 629 |
+ |
|
| 630 |
|
The hidden geometric properties of ODE and its flow play important |
| 631 |
< |
roles in numerical studies. Let $\varphi$ be the flow of Hamiltonian |
| 632 |
< |
vector field, $\varphi$ is a \emph{symplectic} flow if it satisfies, |
| 631 |
> |
roles in numerical studies. Many of them can be found in systems |
| 632 |
> |
which occur naturally in applications. |
| 633 |
> |
|
| 634 |
> |
Let $\varphi$ be the flow of Hamiltonian vector field, $\varphi$ is |
| 635 |
> |
a \emph{symplectic} flow if it satisfies, |
| 636 |
|
\begin{equation} |
| 637 |
< |
'\varphi^T J '\varphi = J. |
| 637 |
> |
{\varphi '}^T J \varphi ' = J. |
| 638 |
|
\end{equation} |
| 639 |
|
According to Liouville's theorem, the symplectic volume is invariant |
| 640 |
|
under a Hamiltonian flow, which is the basis for classical |
| 642 |
|
field on a symplectic manifold can be shown to be a |
| 643 |
|
symplectomorphism. As to the Poisson system, |
| 644 |
|
\begin{equation} |
| 645 |
< |
'\varphi ^T J '\varphi = J \circ \varphi |
| 645 |
> |
{\varphi '}^T J \varphi ' = J \circ \varphi |
| 646 |
|
\end{equation} |
| 647 |
< |
is the property must be preserved by the integrator. It is possible |
| 648 |
< |
to construct a \emph{volume-preserving} flow for a source free($ |
| 649 |
< |
\nabla \cdot f = 0 $) ODE, if the flow satisfies $ \det d\varphi = |
| 650 |
< |
1$. Changing the variables $y = h(x)$ in a |
| 651 |
< |
ODE\ref{introEquation:ODE} will result in a new system, |
| 647 |
> |
is the property must be preserved by the integrator. |
| 648 |
> |
|
| 649 |
> |
It is possible to construct a \emph{volume-preserving} flow for a |
| 650 |
> |
source free($ \nabla \cdot f = 0 $) ODE, if the flow satisfies $ |
| 651 |
> |
\det d\varphi = 1$. One can show easily that a symplectic flow will |
| 652 |
> |
be volume-preserving. |
| 653 |
> |
|
| 654 |
> |
Changing the variables $y = h(x)$ in a ODE\ref{introEquation:ODE} |
| 655 |
> |
will result in a new system, |
| 656 |
|
\[ |
| 657 |
|
\dot y = \tilde f(y) = ((dh \cdot f)h^{ - 1} )(y). |
| 658 |
|
\] |
| 659 |
|
The vector filed $f$ has reversing symmetry $h$ if $f = - \tilde f$. |
| 660 |
|
In other words, the flow of this vector field is reversible if and |
| 661 |
< |
only if $ h \circ \varphi ^{ - 1} = \varphi \circ h $. When |
| 662 |
< |
designing any numerical methods, one should always try to preserve |
| 663 |
< |
the structural properties of the original ODE and its flow. |
| 661 |
> |
only if $ h \circ \varphi ^{ - 1} = \varphi \circ h $. |
| 662 |
> |
|
| 663 |
> |
A \emph{first integral}, or conserved quantity of a general |
| 664 |
> |
differential function is a function $ G:R^{2d} \to R^d $ which is |
| 665 |
> |
constant for all solutions of the ODE $\frac{{dx}}{{dt}} = f(x)$ , |
| 666 |
> |
\[ |
| 667 |
> |
\frac{{dG(x(t))}}{{dt}} = 0. |
| 668 |
> |
\] |
| 669 |
> |
Using chain rule, one may obtain, |
| 670 |
> |
\[ |
| 671 |
> |
\sum\limits_i {\frac{{dG}}{{dx_i }}} f_i (x) = f \bullet \nabla G, |
| 672 |
> |
\] |
| 673 |
> |
which is the condition for conserving \emph{first integral}. For a |
| 674 |
> |
canonical Hamiltonian system, the time evolution of an arbitrary |
| 675 |
> |
smooth function $G$ is given by, |
| 676 |
> |
\begin{equation} |
| 677 |
> |
\begin{array}{c} |
| 678 |
> |
\frac{{dG(x(t))}}{{dt}} = [\nabla _x G(x(t))]^T \dot x(t) \\ |
| 679 |
> |
= [\nabla _x G(x(t))]^T J\nabla _x H(x(t)). \\ |
| 680 |
> |
\end{array} |
| 681 |
> |
\label{introEquation:firstIntegral1} |
| 682 |
> |
\end{equation} |
| 683 |
> |
Using poisson bracket notion, Equation |
| 684 |
> |
\ref{introEquation:firstIntegral1} can be rewritten as |
| 685 |
> |
\[ |
| 686 |
> |
\frac{d}{{dt}}G(x(t)) = \left\{ {G,H} \right\}(x(t)). |
| 687 |
> |
\] |
| 688 |
> |
Therefore, the sufficient condition for $G$ to be the \emph{first |
| 689 |
> |
integral} of a Hamiltonian system is |
| 690 |
> |
\[ |
| 691 |
> |
\left\{ {G,H} \right\} = 0. |
| 692 |
> |
\] |
| 693 |
> |
As well known, the Hamiltonian (or energy) H of a Hamiltonian system |
| 694 |
> |
is a \emph{first integral}, which is due to the fact $\{ H,H\} = |
| 695 |
> |
0$. |
| 696 |
|
|
| 697 |
+ |
|
| 698 |
+ |
When designing any numerical methods, one should always try to |
| 699 |
+ |
preserve the structural properties of the original ODE and its flow. |
| 700 |
+ |
|
| 701 |
|
\subsection{\label{introSection:constructionSymplectic}Construction of Symplectic Methods} |
| 702 |
|
A lot of well established and very effective numerical methods have |
| 703 |
|
been successful precisely because of their symplecticities even |
| 713 |
|
\end{enumerate} |
| 714 |
|
|
| 715 |
|
Generating function tends to lead to methods which are cumbersome |
| 716 |
< |
and difficult to use\cite{}. In dissipative systems, variational |
| 717 |
< |
methods can capture the decay of energy accurately\cite{}. Since |
| 718 |
< |
their geometrically unstable nature against non-Hamiltonian |
| 719 |
< |
perturbations, ordinary implicit Runge-Kutta methods are not |
| 720 |
< |
suitable for Hamiltonian system. Recently, various high-order |
| 721 |
< |
explicit Runge--Kutta methods have been developed to overcome this |
| 722 |
< |
instability \cite{}. However, due to computational penalty involved |
| 723 |
< |
in implementing the Runge-Kutta methods, they do not attract too |
| 724 |
< |
much attention from Molecular Dynamics community. Instead, splitting |
| 725 |
< |
have been widely accepted since they exploit natural decompositions |
| 726 |
< |
of the system\cite{Tuckerman92}. The main idea behind splitting |
| 727 |
< |
methods is to decompose the discrete $\varphi_h$ as a composition of |
| 728 |
< |
simpler flows, |
| 716 |
> |
and difficult to use. In dissipative systems, variational methods |
| 717 |
> |
can capture the decay of energy accurately. Since their |
| 718 |
> |
geometrically unstable nature against non-Hamiltonian perturbations, |
| 719 |
> |
ordinary implicit Runge-Kutta methods are not suitable for |
| 720 |
> |
Hamiltonian system. Recently, various high-order explicit |
| 721 |
> |
Runge--Kutta methods have been developed to overcome this |
| 722 |
> |
instability. However, due to computational penalty involved in |
| 723 |
> |
implementing the Runge-Kutta methods, they do not attract too much |
| 724 |
> |
attention from Molecular Dynamics community. Instead, splitting have |
| 725 |
> |
been widely accepted since they exploit natural decompositions of |
| 726 |
> |
the system\cite{Tuckerman92}. |
| 727 |
> |
|
| 728 |
> |
\subsubsection{\label{introSection:splittingMethod}Splitting Method} |
| 729 |
> |
|
| 730 |
> |
The main idea behind splitting methods is to decompose the discrete |
| 731 |
> |
$\varphi_h$ as a composition of simpler flows, |
| 732 |
|
\begin{equation} |
| 733 |
|
\varphi _h = \varphi _{h_1 } \circ \varphi _{h_2 } \ldots \circ |
| 734 |
|
\varphi _{h_n } |
| 735 |
|
\label{introEquation:FlowDecomposition} |
| 736 |
|
\end{equation} |
| 737 |
|
where each of the sub-flow is chosen such that each represent a |
| 738 |
< |
simpler integration of the system. Let $\phi$ and $\psi$ both be |
| 739 |
< |
symplectic maps, it is easy to show that any composition of |
| 740 |
< |
symplectic flows yields a symplectic map, |
| 738 |
> |
simpler integration of the system. |
| 739 |
> |
|
| 740 |
> |
Suppose that a Hamiltonian system takes the form, |
| 741 |
> |
\[ |
| 742 |
> |
H = H_1 + H_2. |
| 743 |
> |
\] |
| 744 |
> |
Here, $H_1$ and $H_2$ may represent different physical processes of |
| 745 |
> |
the system. For instance, they may relate to kinetic and potential |
| 746 |
> |
energy respectively, which is a natural decomposition of the |
| 747 |
> |
problem. If $H_1$ and $H_2$ can be integrated using exact flows |
| 748 |
> |
$\varphi_1(t)$ and $\varphi_2(t)$, respectively, a simple first |
| 749 |
> |
order is then given by the Lie-Trotter formula |
| 750 |
|
\begin{equation} |
| 751 |
+ |
\varphi _h = \varphi _{1,h} \circ \varphi _{2,h}, |
| 752 |
+ |
\label{introEquation:firstOrderSplitting} |
| 753 |
+ |
\end{equation} |
| 754 |
+ |
where $\varphi _h$ is the result of applying the corresponding |
| 755 |
+ |
continuous $\varphi _i$ over a time $h$. By definition, as |
| 756 |
+ |
$\varphi_i(t)$ is the exact solution of a Hamiltonian system, it |
| 757 |
+ |
must follow that each operator $\varphi_i(t)$ is a symplectic map. |
| 758 |
+ |
It is easy to show that any composition of symplectic flows yields a |
| 759 |
+ |
symplectic map, |
| 760 |
+ |
\begin{equation} |
| 761 |
|
(\varphi '\phi ')^T J\varphi '\phi ' = \phi '^T \varphi '^T J\varphi |
| 762 |
< |
'\phi ' = \phi '^T J\phi ' = J. |
| 762 |
> |
'\phi ' = \phi '^T J\phi ' = J, |
| 763 |
|
\label{introEquation:SymplecticFlowComposition} |
| 764 |
|
\end{equation} |
| 765 |
< |
Suppose that a Hamiltonian system has a form with $H = T + V$ |
| 765 |
> |
where $\phi$ and $\psi$ both are symplectic maps. Thus operator |
| 766 |
> |
splitting in this context automatically generates a symplectic map. |
| 767 |
|
|
| 768 |
+ |
The Lie-Trotter splitting(\ref{introEquation:firstOrderSplitting}) |
| 769 |
+ |
introduces local errors proportional to $h^2$, while Strang |
| 770 |
+ |
splitting gives a second-order decomposition, |
| 771 |
+ |
\begin{equation} |
| 772 |
+ |
\varphi _h = \varphi _{1,h/2} \circ \varphi _{2,h} \circ \varphi |
| 773 |
+ |
_{1,h/2} , \label{introEquation:secondOrderSplitting} |
| 774 |
+ |
\end{equation} |
| 775 |
+ |
which has a local error proportional to $h^3$. Sprang splitting's |
| 776 |
+ |
popularity in molecular simulation community attribute to its |
| 777 |
+ |
symmetric property, |
| 778 |
+ |
\begin{equation} |
| 779 |
+ |
\varphi _h^{ - 1} = \varphi _{ - h}. |
| 780 |
+ |
\label{introEquation:timeReversible} |
| 781 |
+ |
\end{equation} |
| 782 |
+ |
|
| 783 |
+ |
\subsubsection{\label{introSection:exampleSplittingMethod}Example of Splitting Method} |
| 784 |
+ |
The classical equation for a system consisting of interacting |
| 785 |
+ |
particles can be written in Hamiltonian form, |
| 786 |
+ |
\[ |
| 787 |
+ |
H = T + V |
| 788 |
+ |
\] |
| 789 |
+ |
where $T$ is the kinetic energy and $V$ is the potential energy. |
| 790 |
+ |
Setting $H_1 = T, H_2 = V$ and applying Strang splitting, one |
| 791 |
+ |
obtains the following: |
| 792 |
+ |
\begin{align} |
| 793 |
+ |
q(\Delta t) &= q(0) + \dot{q}(0)\Delta t + |
| 794 |
+ |
\frac{F[q(0)]}{m}\frac{\Delta t^2}{2}, % |
| 795 |
+ |
\label{introEquation:Lp10a} \\% |
| 796 |
+ |
% |
| 797 |
+ |
\dot{q}(\Delta t) &= \dot{q}(0) + \frac{\Delta t}{2m} |
| 798 |
+ |
\biggl [F[q(0)] + F[q(\Delta t)] \biggr]. % |
| 799 |
+ |
\label{introEquation:Lp10b} |
| 800 |
+ |
\end{align} |
| 801 |
+ |
where $F(t)$ is the force at time $t$. This integration scheme is |
| 802 |
+ |
known as \emph{velocity verlet} which is |
| 803 |
+ |
symplectic(\ref{introEquation:SymplecticFlowComposition}), |
| 804 |
+ |
time-reversible(\ref{introEquation:timeReversible}) and |
| 805 |
+ |
volume-preserving (\ref{introEquation:volumePreserving}). These |
| 806 |
+ |
geometric properties attribute to its long-time stability and its |
| 807 |
+ |
popularity in the community. However, the most commonly used |
| 808 |
+ |
velocity verlet integration scheme is written as below, |
| 809 |
+ |
\begin{align} |
| 810 |
+ |
\dot{q}\biggl (\frac{\Delta t}{2}\biggr ) &= |
| 811 |
+ |
\dot{q}(0) + \frac{\Delta t}{2m}\, F[q(0)], \label{introEquation:Lp9a}\\% |
| 812 |
+ |
% |
| 813 |
+ |
q(\Delta t) &= q(0) + \Delta t\, \dot{q}\biggl (\frac{\Delta t}{2}\biggr ),% |
| 814 |
+ |
\label{introEquation:Lp9b}\\% |
| 815 |
+ |
% |
| 816 |
+ |
\dot{q}(\Delta t) &= \dot{q}\biggl (\frac{\Delta t}{2}\biggr ) + |
| 817 |
+ |
\frac{\Delta t}{2m}\, F[q(0)]. \label{introEquation:Lp9c} |
| 818 |
+ |
\end{align} |
| 819 |
+ |
From the preceding splitting, one can see that the integration of |
| 820 |
+ |
the equations of motion would follow: |
| 821 |
+ |
\begin{enumerate} |
| 822 |
+ |
\item calculate the velocities at the half step, $\frac{\Delta t}{2}$, from the forces calculated at the initial position. |
| 823 |
+ |
|
| 824 |
+ |
\item Use the half step velocities to move positions one whole step, $\Delta t$. |
| 825 |
+ |
|
| 826 |
+ |
\item Evaluate the forces at the new positions, $\mathbf{r}(\Delta t)$, and use the new forces to complete the velocity move. |
| 827 |
+ |
|
| 828 |
+ |
\item Repeat from step 1 with the new position, velocities, and forces assuming the roles of the initial values. |
| 829 |
+ |
\end{enumerate} |
| 830 |
+ |
|
| 831 |
+ |
Simply switching the order of splitting and composing, a new |
| 832 |
+ |
integrator, the \emph{position verlet} integrator, can be generated, |
| 833 |
+ |
\begin{align} |
| 834 |
+ |
\dot q(\Delta t) &= \dot q(0) + \Delta tF(q(0))\left[ {q(0) + |
| 835 |
+ |
\frac{{\Delta t}}{{2m}}\dot q(0)} \right], % |
| 836 |
+ |
\label{introEquation:positionVerlet1} \\% |
| 837 |
+ |
% |
| 838 |
+ |
q(\Delta t) &= q(0) + \frac{{\Delta t}}{2}\left[ {\dot q(0) + \dot |
| 839 |
+ |
q(\Delta t)} \right]. % |
| 840 |
+ |
\label{introEquation:positionVerlet1} |
| 841 |
+ |
\end{align} |
| 842 |
+ |
|
| 843 |
+ |
\subsubsection{\label{introSection:errorAnalysis}Error Analysis and Higher Order Methods} |
| 844 |
+ |
|
| 845 |
+ |
Baker-Campbell-Hausdorff formula can be used to determine the local |
| 846 |
+ |
error of splitting method in terms of commutator of the |
| 847 |
+ |
operators(\ref{introEquation:exponentialOperator}) associated with |
| 848 |
+ |
the sub-flow. For operators $hX$ and $hY$ which are associate to |
| 849 |
+ |
$\varphi_1(t)$ and $\varphi_2(t$ respectively , we have |
| 850 |
+ |
\begin{equation} |
| 851 |
+ |
\exp (hX + hY) = \exp (hZ) |
| 852 |
+ |
\end{equation} |
| 853 |
+ |
where |
| 854 |
+ |
\begin{equation} |
| 855 |
+ |
hZ = hX + hY + \frac{{h^2 }}{2}[X,Y] + \frac{{h^3 }}{2}\left( |
| 856 |
+ |
{[X,[X,Y]] + [Y,[Y,X]]} \right) + \ldots . |
| 857 |
+ |
\end{equation} |
| 858 |
+ |
Here, $[X,Y]$ is the commutators of operator $X$ and $Y$ given by |
| 859 |
+ |
\[ |
| 860 |
+ |
[X,Y] = XY - YX . |
| 861 |
+ |
\] |
| 862 |
+ |
Applying Baker-Campbell-Hausdorff formula to Sprang splitting, we |
| 863 |
+ |
can obtain |
| 864 |
+ |
\begin{eqnarray*} |
| 865 |
+ |
\exp (h X/2)\exp (h Y)\exp (h X/2) & = & \exp (h X + h Y + h^2 |
| 866 |
+ |
[X,Y]/4 + h^2 [Y,X]/4 \\ & & \mbox{} + h^2 [X,X]/8 + h^2 [Y,Y]/8 \\ |
| 867 |
+ |
& & \mbox{} + h^3 [Y,[Y,X]]/12 - h^3 [X,[X,Y]]/24 & & \mbox{} + |
| 868 |
+ |
\ldots ) |
| 869 |
+ |
\end{eqnarray*} |
| 870 |
+ |
Since \[ [X,Y] + [Y,X] = 0\] and \[ [X,X] = 0\], the dominant local |
| 871 |
+ |
error of Spring splitting is proportional to $h^3$. The same |
| 872 |
+ |
procedure can be applied to general splitting, of the form |
| 873 |
+ |
\begin{equation} |
| 874 |
+ |
\varphi _{b_m h}^2 \circ \varphi _{a_m h}^1 \circ \varphi _{b_{m - |
| 875 |
+ |
1} h}^2 \circ \ldots \circ \varphi _{a_1 h}^1 . |
| 876 |
+ |
\end{equation} |
| 877 |
+ |
Careful choice of coefficient $a_1 ,\ldot , b_m$ will lead to higher |
| 878 |
+ |
order method. Yoshida proposed an elegant way to compose higher |
| 879 |
+ |
order methods based on symmetric splitting. Given a symmetric second |
| 880 |
+ |
order base method $ \varphi _h^{(2)} $, a fourth-order symmetric |
| 881 |
+ |
method can be constructed by composing, |
| 882 |
+ |
\[ |
| 883 |
+ |
\varphi _h^{(4)} = \varphi _{\alpha h}^{(2)} \circ \varphi _{\beta |
| 884 |
+ |
h}^{(2)} \circ \varphi _{\alpha h}^{(2)} |
| 885 |
+ |
\] |
| 886 |
+ |
where $ \alpha = - \frac{{2^{1/3} }}{{2 - 2^{1/3} }}$ and $ \beta |
| 887 |
+ |
= \frac{{2^{1/3} }}{{2 - 2^{1/3} }}$. Moreover, a symmetric |
| 888 |
+ |
integrator $ \varphi _h^{(2n + 2)}$ can be composed by |
| 889 |
+ |
\begin{equation} |
| 890 |
+ |
\varphi _h^{(2n + 2)} = \varphi _{\alpha h}^{(2n)} \circ \varphi |
| 891 |
+ |
_{\beta h}^{(2n)} \circ \varphi _{\alpha h}^{(2n)} |
| 892 |
+ |
\end{equation} |
| 893 |
+ |
, if the weights are chosen as |
| 894 |
+ |
\[ |
| 895 |
+ |
\alpha = - \frac{{2^{1/(2n + 1)} }}{{2 - 2^{1/(2n + 1)} }},\beta = |
| 896 |
+ |
\frac{{2^{1/(2n + 1)} }}{{2 - 2^{1/(2n + 1)} }} . |
| 897 |
+ |
\] |
| 898 |
+ |
|
| 899 |
|
\section{\label{introSection:molecularDynamics}Molecular Dynamics} |
| 900 |
|
|
| 901 |
|
As a special discipline of molecular modeling, Molecular dynamics |
| 905 |
|
|
| 906 |
|
\subsection{\label{introSec:mdInit}Initialization} |
| 907 |
|
|
| 908 |
+ |
\subsection{\label{introSec:forceEvaluation}Force Evaluation} |
| 909 |
+ |
|
| 910 |
|
\subsection{\label{introSection:mdIntegration} Integration of the Equations of Motion} |
| 911 |
|
|
| 912 |
|
\section{\label{introSection:rigidBody}Dynamics of Rigid Bodies} |
| 913 |
|
|
| 914 |
< |
A rigid body is a body in which the distance between any two given |
| 915 |
< |
points of a rigid body remains constant regardless of external |
| 916 |
< |
forces exerted on it. A rigid body therefore conserves its shape |
| 917 |
< |
during its motion. |
| 914 |
> |
Rigid bodies are frequently involved in the modeling of different |
| 915 |
> |
areas, from engineering, physics, to chemistry. For example, |
| 916 |
> |
missiles and vehicle are usually modeled by rigid bodies. The |
| 917 |
> |
movement of the objects in 3D gaming engine or other physics |
| 918 |
> |
simulator is governed by the rigid body dynamics. In molecular |
| 919 |
> |
simulation, rigid body is used to simplify the model in |
| 920 |
> |
protein-protein docking study{\cite{Gray03}}. |
| 921 |
|
|
| 922 |
< |
Applications of dynamics of rigid bodies. |
| 922 |
> |
It is very important to develop stable and efficient methods to |
| 923 |
> |
integrate the equations of motion of orientational degrees of |
| 924 |
> |
freedom. Euler angles are the nature choice to describe the |
| 925 |
> |
rotational degrees of freedom. However, due to its singularity, the |
| 926 |
> |
numerical integration of corresponding equations of motion is very |
| 927 |
> |
inefficient and inaccurate. Although an alternative integrator using |
| 928 |
> |
different sets of Euler angles can overcome this difficulty\cite{}, |
| 929 |
> |
the computational penalty and the lost of angular momentum |
| 930 |
> |
conservation still remain. A singularity free representation |
| 931 |
> |
utilizing quaternions was developed by Evans in 1977. Unfortunately, |
| 932 |
> |
this approach suffer from the nonseparable Hamiltonian resulted from |
| 933 |
> |
quaternion representation, which prevents the symplectic algorithm |
| 934 |
> |
to be utilized. Another different approach is to apply holonomic |
| 935 |
> |
constraints to the atoms belonging to the rigid body. Each atom |
| 936 |
> |
moves independently under the normal forces deriving from potential |
| 937 |
> |
energy and constraint forces which are used to guarantee the |
| 938 |
> |
rigidness. However, due to their iterative nature, SHAKE and Rattle |
| 939 |
> |
algorithm converge very slowly when the number of constraint |
| 940 |
> |
increases. |
| 941 |
|
|
| 942 |
+ |
The break through in geometric literature suggests that, in order to |
| 943 |
+ |
develop a long-term integration scheme, one should preserve the |
| 944 |
+ |
symplectic structure of the flow. Introducing conjugate momentum to |
| 945 |
+ |
rotation matrix $A$ and re-formulating Hamiltonian's equation, a |
| 946 |
+ |
symplectic integrator, RSHAKE, was proposed to evolve the |
| 947 |
+ |
Hamiltonian system in a constraint manifold by iteratively |
| 948 |
+ |
satisfying the orthogonality constraint $A_t A = 1$. An alternative |
| 949 |
+ |
method using quaternion representation was developed by Omelyan. |
| 950 |
+ |
However, both of these methods are iterative and inefficient. In |
| 951 |
+ |
this section, we will present a symplectic Lie-Poisson integrator |
| 952 |
+ |
for rigid body developed by Dullweber and his coworkers\cite{}. |
| 953 |
+ |
|
| 954 |
|
\subsection{\label{introSection:lieAlgebra}Lie Algebra} |
| 955 |
|
|
| 956 |
< |
\subsection{\label{introSection:DLMMotionEquation}The Euler Equations of Rigid Body Motion} |
| 956 |
> |
\subsection{\label{introSection:constrainedHamiltonianRB}Constrained Hamiltonian for Rigid Body} |
| 957 |
|
|
| 958 |
< |
\subsection{\label{introSection:otherRBMotionEquation}Other Formulations for Rigid Body Motion} |
| 958 |
> |
\begin{equation} |
| 959 |
> |
H = \frac{1}{2}(p^T m^{ - 1} p) + \frac{1}{2}tr(PJ^{ - 1} P) + |
| 960 |
> |
V(q,Q) + \frac{1}{2}tr[(QQ^T - 1)\Lambda ]. |
| 961 |
> |
\label{introEquation:RBHamiltonian} |
| 962 |
> |
\end{equation} |
| 963 |
> |
Here, $q$ and $Q$ are the position and rotation matrix for the |
| 964 |
> |
rigid-body, $p$ and $P$ are conjugate momenta to $q$ and $Q$ , and |
| 965 |
> |
$J$, a diagonal matrix, is defined by |
| 966 |
> |
\[ |
| 967 |
> |
I_{ii}^{ - 1} = \frac{1}{2}\sum\limits_{i \ne j} {J_{jj}^{ - 1} } |
| 968 |
> |
\] |
| 969 |
> |
where $I_{ii}$ is the diagonal element of the inertia tensor. This |
| 970 |
> |
constrained Hamiltonian equation subjects to a holonomic constraint, |
| 971 |
> |
\begin{equation} |
| 972 |
> |
Q^T Q = 1$, \label{introEquation:orthogonalConstraint} |
| 973 |
> |
\end{equation} |
| 974 |
> |
which is used to ensure rotation matrix's orthogonality. |
| 975 |
> |
Differentiating \ref{introEquation:orthogonalConstraint} and using |
| 976 |
> |
Equation \ref{introEquation:RBMotionMomentum}, one may obtain, |
| 977 |
> |
\begin{equation} |
| 978 |
> |
Q^t PJ^{ - 1} + J^{ - 1} P^t Q = 0 . \\ |
| 979 |
> |
\label{introEquation:RBFirstOrderConstraint} |
| 980 |
> |
\end{equation} |
| 981 |
|
|
| 982 |
< |
%\subsection{\label{introSection:poissonBrackets}Poisson Brackets} |
| 982 |
> |
Using Equation (\ref{introEquation:motionHamiltonianCoordinate}, |
| 983 |
> |
\ref{introEquation:motionHamiltonianMomentum}), one can write down |
| 984 |
> |
the equations of motion, |
| 985 |
> |
\[ |
| 986 |
> |
\begin{array}{c} |
| 987 |
> |
\frac{{dq}}{{dt}} = \frac{p}{m} \label{introEquation:RBMotionPosition}\\ |
| 988 |
> |
\frac{{dp}}{{dt}} = - \nabla _q V(q,Q) \label{introEquation:RBMotionMomentum}\\ |
| 989 |
> |
\frac{{dQ}}{{dt}} = PJ^{ - 1} \label{introEquation:RBMotionRotation}\\ |
| 990 |
> |
\frac{{dP}}{{dt}} = - \nabla _q V(q,Q) - 2Q\Lambda . \label{introEquation:RBMotionP}\\ |
| 991 |
> |
\end{array} |
| 992 |
> |
\] |
| 993 |
|
|
| 682 |
– |
\section{\label{introSection:correlationFunctions}Correlation Functions} |
| 994 |
|
|
| 995 |
+ |
\[ |
| 996 |
+ |
M = \left\{ {(Q,P):Q^T Q = 1,Q^t PJ^{ - 1} + J^{ - 1} P^t Q = 0} |
| 997 |
+ |
\right\} . |
| 998 |
+ |
\] |
| 999 |
+ |
|
| 1000 |
+ |
\subsection{\label{introSection:DLMMotionEquation}The Euler Equations of Rigid Body Motion} |
| 1001 |
+ |
|
| 1002 |
+ |
\subsection{\label{introSection:symplecticDiscretizationRB}Symplectic Discretization of Euler Equations} |
| 1003 |
+ |
|
| 1004 |
+ |
|
| 1005 |
|
\section{\label{introSection:langevinDynamics}Langevin Dynamics} |
| 1006 |
|
|
| 1007 |
|
\subsection{\label{introSection:LDIntroduction}Introduction and application of Langevin Dynamics} |
| 1050 |
|
\dot p &= - \frac{{\partial H}}{{\partial x}} |
| 1051 |
|
&= m\ddot x |
| 1052 |
|
&= - \frac{{\partial W(x)}}{{\partial x}} - \sum\limits_{\alpha = 1}^N {g_\alpha \left( {x_\alpha - \frac{{g_\alpha }}{{m_\alpha w_\alpha ^2 }}x} \right)} |
| 1053 |
< |
\label{introEq:Lp5} |
| 1053 |
> |
\label{introEquation:Lp5} |
| 1054 |
|
\end{align} |
| 1055 |
|
, and |
| 1056 |
|
\begin{align} |
| 1209 |
|
|
| 1210 |
|
\subsection{\label{introSection:centersRigidBody}Centers of Rigid |
| 1211 |
|
Body} |
| 1212 |
+ |
|
| 1213 |
+ |
\section{\label{introSection:correlationFunctions}Correlation Functions} |
