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# Line 27 | Line 27 | $F_ij$ be the force that particle $i$ exerts on partic
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  
# Line 315 | Line 315 | partition function like,
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
# Line 394 | Line 393 | 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
# Line 431 | Line 458 | expressed as
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
# Line 544 | Line 570 | The free rigid body is an example of Poisson system (a
570   \dot x = J(x)\nabla _x H \label{introEquation:poissonHamiltonian}
571   \end{equation}
572   The most obvious change being that matrix $J$ now depends on $x$.
547 The free rigid body is an example of Poisson system (actually a
548 Lie-Poisson system) with Hamiltonian function of angular kinetic
549 energy.
550 \begin{equation}
551 J(\pi ) = \left( {\begin{array}{*{20}c}
552   0 & {\pi _3 } & { - \pi _2 }  \\
553   { - \pi _3 } & 0 & {\pi _1 }  \\
554   {\pi _2 } & { - \pi _1 } & 0  \\
555 \end{array}} \right)
556 \end{equation}
573  
574 < \begin{equation}
559 < H = \frac{1}{2}\left( {\frac{{\pi _1^2 }}{{I_1 }} + \frac{{\pi _2^2
560 < }}{{I_2 }} + \frac{{\pi _3^2 }}{{I_3 }}} \right)
561 < \end{equation}
574 > \subsection{\label{introSection:exactFlow}Exact Flow}
575  
563 \subsection{\label{introSection:geometricProperties}Geometric Properties}
576   Let $x(t)$ be the exact solution of the ODE system,
577   \begin{equation}
578   \frac{{dx}}{{dt}} = f(x) \label{introEquation:ODE}
# Line 570 | Line 582 | space to itself. In most cases, it is not easy to find
582   x(t+\tau) =\varphi_\tau(x(t))
583   \]
584   where $\tau$ is a fixed time step and $\varphi$ is a map from phase
585 < 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 $p$,
585 > space to itself. The flow has the continuous group property,
586   \begin{equation}
587 + \varphi _{\tau _1 }  \circ \varphi _{\tau _2 }  = \varphi _{\tau _1
588 + + \tau _2 } .
589 + \end{equation}
590 + In particular,
591 + \begin{equation}
592 + \varphi _\tau   \circ \varphi _{ - \tau }  = I
593 + \end{equation}
594 + Therefore, the exact flow is self-adjoint,
595 + \begin{equation}
596 + \varphi _\tau   = \varphi _{ - \tau }^{ - 1}.
597 + \end{equation}
598 + The exact flow can also be written in terms of the of an operator,
599 + \begin{equation}
600 + \varphi _\tau  (x) = e^{\tau \sum\limits_i {f_i (x)\frac{\partial
601 + }{{\partial x_i }}} } (x) \equiv \exp (\tau f)(x).
602 + \label{introEquation:exponentialOperator}
603 + \end{equation}
604 +
605 + In most cases, it is not easy to find the exact flow $\varphi_\tau$.
606 + Instead, we use a approximate map, $\psi_\tau$, which is usually
607 + called integrator. The order of an integrator $\psi_\tau$ is $p$, if
608 + the Taylor series of $\psi_\tau$ agree to order $p$,
609 + \begin{equation}
610   \psi_tau(x) = x + \tau f(x) + O(\tau^{p+1})
611   \end{equation}
612  
613 + \subsection{\label{introSection:geometricProperties}Geometric Properties}
614 +
615   The hidden geometric properties of ODE and its flow play important
616 < roles in numerical studies. Let $\varphi$ be the flow of Hamiltonian
617 < vector field, $\varphi$ is a \emph{symplectic} flow if it satisfies,
616 > roles in numerical studies. Many of them can be found in systems
617 > which occur naturally in applications.
618 >
619 > Let $\varphi$ be the flow of Hamiltonian vector field, $\varphi$ is
620 > a \emph{symplectic} flow if it satisfies,
621   \begin{equation}
622 < '\varphi^T J '\varphi = J.
622 > {\varphi '}^T J \varphi ' = J.
623   \end{equation}
624   According to Liouville's theorem, the symplectic volume is invariant
625   under a Hamiltonian flow, which is the basis for classical
# Line 591 | Line 627 | symplectomorphism. As to the Poisson system,
627   field on a symplectic manifold can be shown to be a
628   symplectomorphism. As to the Poisson system,
629   \begin{equation}
630 < '\varphi ^T J '\varphi  = J \circ \varphi
630 > {\varphi '}^T J \varphi ' = J \circ \varphi
631   \end{equation}
632 < is the property must be preserved by the integrator. It is possible
633 < to construct a \emph{volume-preserving} flow for a source free($
634 < \nabla \cdot f = 0 $) ODE, if the flow satisfies $ \det d\varphi  =
635 < 1$. Changing the variables $y = h(x)$ in a
636 < ODE\ref{introEquation:ODE} will result in a new system,
632 > is the property must be preserved by the integrator.
633 >
634 > It is possible to construct a \emph{volume-preserving} flow for a
635 > source free($ \nabla \cdot f = 0 $) ODE, if the flow satisfies $
636 > \det d\varphi  = 1$. One can show easily that a symplectic flow will
637 > be volume-preserving.
638 >
639 > Changing the variables $y = h(x)$ in a ODE\ref{introEquation:ODE}
640 > will result in a new system,
641   \[
642   \dot y = \tilde f(y) = ((dh \cdot f)h^{ - 1} )(y).
643   \]
644   The vector filed $f$ has reversing symmetry $h$ if $f = - \tilde f$.
645   In other words, the flow of this vector field is reversible if and
646 < only if $ h \circ \varphi ^{ - 1}  = \varphi  \circ h $. When
607 < designing any numerical methods, one should always try to preserve
608 < the structural properties of the original ODE and its flow.
646 > only if $ h \circ \varphi ^{ - 1}  = \varphi  \circ h $.
647  
648 + A \emph{first integral}, or conserved quantity of a general
649 + differential function is a function $ G:R^{2d}  \to R^d $ which is
650 + constant for all solutions of the ODE $\frac{{dx}}{{dt}} = f(x)$ ,
651 + \[
652 + \frac{{dG(x(t))}}{{dt}} = 0.
653 + \]
654 + Using chain rule, one may obtain,
655 + \[
656 + \sum\limits_i {\frac{{dG}}{{dx_i }}} f_i (x) = f \bullet \nabla G,
657 + \]
658 + which is the condition for conserving \emph{first integral}. For a
659 + canonical Hamiltonian system, the time evolution of an arbitrary
660 + smooth function $G$ is given by,
661 + \begin{equation}
662 + \begin{array}{c}
663 + \frac{{dG(x(t))}}{{dt}} = [\nabla _x G(x(t))]^T \dot x(t) \\
664 +  = [\nabla _x G(x(t))]^T J\nabla _x H(x(t)). \\
665 + \end{array}
666 + \label{introEquation:firstIntegral1}
667 + \end{equation}
668 + Using poisson bracket notion, Equation
669 + \ref{introEquation:firstIntegral1} can be rewritten as
670 + \[
671 + \frac{d}{{dt}}G(x(t)) = \left\{ {G,H} \right\}(x(t)).
672 + \]
673 + Therefore, the sufficient condition for $G$ to be the \emph{first
674 + integral} of a Hamiltonian system is
675 + \[
676 + \left\{ {G,H} \right\} = 0.
677 + \]
678 + As well known, the Hamiltonian (or energy) H of a Hamiltonian system
679 + is a \emph{first integral}, which is due to the fact $\{ H,H\}  =
680 + 0$.
681 +
682 +
683 + When designing any numerical methods, one should always try to
684 + preserve the structural properties of the original ODE and its flow.
685 +
686   \subsection{\label{introSection:constructionSymplectic}Construction of Symplectic Methods}
687   A lot of well established and very effective numerical methods have
688   been successful precisely because of their symplecticities even
# Line 622 | Line 698 | and difficult to use\cite{}. In dissipative systems, v
698   \end{enumerate}
699  
700   Generating function tends to lead to methods which are cumbersome
701 < and difficult to use\cite{}. In dissipative systems, variational
702 < methods can capture the decay of energy accurately\cite{}. Since
703 < their geometrically unstable nature against non-Hamiltonian
704 < perturbations, ordinary implicit Runge-Kutta methods are not
705 < suitable for Hamiltonian system. Recently, various high-order
706 < explicit Runge--Kutta methods have been developed to overcome this
707 < instability \cite{}. However, due to computational penalty involved
708 < in implementing the Runge-Kutta methods, they do not attract too
709 < much attention from Molecular Dynamics community. Instead, splitting
710 < have been widely accepted since they exploit natural decompositions
711 < of the system\cite{Tuckerman92}. The main idea behind splitting
712 < methods is to decompose the discrete $\varphi_h$ as a composition of
713 < simpler flows,
701 > and difficult to use. In dissipative systems, variational methods
702 > can capture the decay of energy accurately. Since their
703 > geometrically unstable nature against non-Hamiltonian perturbations,
704 > ordinary implicit Runge-Kutta methods are not suitable for
705 > Hamiltonian system. Recently, various high-order explicit
706 > Runge--Kutta methods have been developed to overcome this
707 > instability. However, due to computational penalty involved in
708 > implementing the Runge-Kutta methods, they do not attract too much
709 > attention from Molecular Dynamics community. Instead, splitting have
710 > been widely accepted since they exploit natural decompositions of
711 > the system\cite{Tuckerman92}.
712 >
713 > \subsubsection{\label{introSection:splittingMethod}Splitting Method}
714 >
715 > The main idea behind splitting methods is to decompose the discrete
716 > $\varphi_h$ as a composition of simpler flows,
717   \begin{equation}
718   \varphi _h  = \varphi _{h_1 }  \circ \varphi _{h_2 }  \ldots  \circ
719   \varphi _{h_n }
720   \label{introEquation:FlowDecomposition}
721   \end{equation}
722   where each of the sub-flow is chosen such that each represent a
723 < simpler integration of the system. Let $\phi$ and $\psi$ both be
724 < symplectic maps, it is easy to show that any composition of
725 < symplectic flows yields a symplectic map,
723 > simpler integration of the system.
724 >
725 > Suppose that a Hamiltonian system takes the form,
726 > \[
727 > H = H_1 + H_2.
728 > \]
729 > Here, $H_1$ and $H_2$ may represent different physical processes of
730 > the system. For instance, they may relate to kinetic and potential
731 > energy respectively, which is a natural decomposition of the
732 > problem. If $H_1$ and $H_2$ can be integrated using exact flows
733 > $\varphi_1(t)$ and $\varphi_2(t)$, respectively, a simple first
734 > order is then given by the Lie-Trotter formula
735   \begin{equation}
736 + \varphi _h  = \varphi _{1,h}  \circ \varphi _{2,h},
737 + \label{introEquation:firstOrderSplitting}
738 + \end{equation}
739 + where $\varphi _h$ is the result of applying the corresponding
740 + continuous $\varphi _i$ over a time $h$. By definition, as
741 + $\varphi_i(t)$ is the exact solution of a Hamiltonian system, it
742 + must follow that each operator $\varphi_i(t)$ is a symplectic map.
743 + It is easy to show that any composition of symplectic flows yields a
744 + symplectic map,
745 + \begin{equation}
746   (\varphi '\phi ')^T J\varphi '\phi ' = \phi '^T \varphi '^T J\varphi
747 < '\phi ' = \phi '^T J\phi ' = J.
747 > '\phi ' = \phi '^T J\phi ' = J,
748   \label{introEquation:SymplecticFlowComposition}
749   \end{equation}
750 < Suppose that a Hamiltonian system has a form with $H = T + V$
750 > where $\phi$ and $\psi$ both are symplectic maps. Thus operator
751 > splitting in this context automatically generates a symplectic map.
752  
753 + The Lie-Trotter splitting(\ref{introEquation:firstOrderSplitting})
754 + introduces local errors proportional to $h^2$, while Strang
755 + splitting gives a second-order decomposition,
756 + \begin{equation}
757 + \varphi _h  = \varphi _{1,h/2}  \circ \varphi _{2,h}  \circ \varphi
758 + _{1,h/2} , \label{introEquation:secondOrderSplitting}
759 + \end{equation}
760 + which has a local error proportional to $h^3$. Sprang splitting's
761 + popularity in molecular simulation community attribute to its
762 + symmetric property,
763 + \begin{equation}
764 + \varphi _h^{ - 1} = \varphi _{ - h}.
765 + \label{introEquation:timeReversible}
766 + \end{equation}
767 +
768 + \subsubsection{\label{introSection:exampleSplittingMethod}Example of Splitting Method}
769 + The classical equation for a system consisting of interacting
770 + particles can be written in Hamiltonian form,
771 + \[
772 + H = T + V
773 + \]
774 + where $T$ is the kinetic energy and $V$ is the potential energy.
775 + Setting $H_1 = T, H_2 = V$ and applying Strang splitting, one
776 + obtains the following:
777 + \begin{align}
778 + q(\Delta t) &= q(0) + \dot{q}(0)\Delta t +
779 +    \frac{F[q(0)]}{m}\frac{\Delta t^2}{2}, %
780 + \label{introEquation:Lp10a} \\%
781 + %
782 + \dot{q}(\Delta t) &= \dot{q}(0) + \frac{\Delta t}{2m}
783 +    \biggl [F[q(0)] + F[q(\Delta t)] \biggr]. %
784 + \label{introEquation:Lp10b}
785 + \end{align}
786 + where $F(t)$ is the force at time $t$. This integration scheme is
787 + known as \emph{velocity verlet} which is
788 + symplectic(\ref{introEquation:SymplecticFlowComposition}),
789 + time-reversible(\ref{introEquation:timeReversible}) and
790 + volume-preserving (\ref{introEquation:volumePreserving}). These
791 + geometric properties attribute to its long-time stability and its
792 + popularity in the community. However, the most commonly used
793 + velocity verlet integration scheme is written as below,
794 + \begin{align}
795 + \dot{q}\biggl (\frac{\Delta t}{2}\biggr ) &=
796 +    \dot{q}(0) + \frac{\Delta t}{2m}\, F[q(0)], \label{introEquation:Lp9a}\\%
797 + %
798 + q(\Delta t) &= q(0) + \Delta t\, \dot{q}\biggl (\frac{\Delta t}{2}\biggr ),%
799 +    \label{introEquation:Lp9b}\\%
800 + %
801 + \dot{q}(\Delta t) &= \dot{q}\biggl (\frac{\Delta t}{2}\biggr ) +
802 +    \frac{\Delta t}{2m}\, F[q(0)]. \label{introEquation:Lp9c}
803 + \end{align}
804 + From the preceding splitting, one can see that the integration of
805 + the equations of motion would follow:
806 + \begin{enumerate}
807 + \item calculate the velocities at the half step, $\frac{\Delta t}{2}$, from the forces calculated at the initial position.
808 +
809 + \item Use the half step velocities to move positions one whole step, $\Delta t$.
810 +
811 + \item Evaluate the forces at the new positions, $\mathbf{r}(\Delta t)$, and use the new forces to complete the velocity move.
812 +
813 + \item Repeat from step 1 with the new position, velocities, and forces assuming the roles of the initial values.
814 + \end{enumerate}
815 +
816 + Simply switching the order of splitting and composing, a new
817 + integrator, the \emph{position verlet} integrator, can be generated,
818 + \begin{align}
819 + \dot q(\Delta t) &= \dot q(0) + \Delta tF(q(0))\left[ {q(0) +
820 + \frac{{\Delta t}}{{2m}}\dot q(0)} \right], %
821 + \label{introEquation:positionVerlet1} \\%
822 + %
823 + q(\Delta t) &= q(0) + \frac{{\Delta t}}{2}\left[ {\dot q(0) + \dot
824 + q(\Delta t)} \right]. %
825 + \label{introEquation:positionVerlet1}
826 + \end{align}
827 +
828 + \subsubsection{\label{introSection:errorAnalysis}Error Analysis and Higher Order Methods}
829 +
830 + Baker-Campbell-Hausdorff formula can be used to determine the local
831 + error of splitting method in terms of commutator of the
832 + operators(\ref{introEquation:exponentialOperator}) associated with
833 + the sub-flow. For operators $hX$ and $hY$ which are associate to
834 + $\varphi_1(t)$ and $\varphi_2(t$ respectively , we have
835 + \begin{equation}
836 + \exp (hX + hY) = \exp (hZ)
837 + \end{equation}
838 + where
839 + \begin{equation}
840 + hZ = hX + hY + \frac{{h^2 }}{2}[X,Y] + \frac{{h^3 }}{2}\left(
841 + {[X,[X,Y]] + [Y,[Y,X]]} \right) +  \ldots .
842 + \end{equation}
843 + Here, $[X,Y]$ is the commutators of operator $X$ and $Y$ given by
844 + \[
845 + [X,Y] = XY - YX .
846 + \]
847 + Applying Baker-Campbell-Hausdorff formula to Sprang splitting, we
848 + can obtain
849 + \begin{eqnarray*}
850 + \exp (h X/2)\exp (h Y)\exp (h X/2) & = & \exp (h X + h Y + h^2
851 + [X,Y]/4 + h^2 [Y,X]/4 \\ & & \mbox{} + h^2 [X,X]/8 + h^2 [Y,Y]/8 \\
852 + & & \mbox{} + h^3 [Y,[Y,X]]/12 - h^3 [X,[X,Y]]/24 & & \mbox{} +
853 + \ldots )
854 + \end{eqnarray*}
855 + Since \[ [X,Y] + [Y,X] = 0\] and \[ [X,X] = 0\], the dominant local
856 + error of Spring splitting is proportional to $h^3$. The same
857 + procedure can be applied to general splitting,  of the form
858 + \begin{equation}
859 + \varphi _{b_m h}^2  \circ \varphi _{a_m h}^1  \circ \varphi _{b_{m -
860 + 1} h}^2  \circ  \ldots  \circ \varphi _{a_1 h}^1 .
861 + \end{equation}
862 + Careful choice of coefficient $a_1 ,\ldot , b_m$ will lead to higher
863 + order method. Yoshida proposed an elegant way to compose higher
864 + order methods based on symmetric splitting. Given a symmetric second
865 + order base method $ \varphi _h^{(2)} $, a fourth-order symmetric
866 + method can be constructed by composing,
867 + \[
868 + \varphi _h^{(4)}  = \varphi _{\alpha h}^{(2)}  \circ \varphi _{\beta
869 + h}^{(2)}  \circ \varphi _{\alpha h}^{(2)}
870 + \]
871 + where $ \alpha  =  - \frac{{2^{1/3} }}{{2 - 2^{1/3} }}$ and $ \beta
872 + = \frac{{2^{1/3} }}{{2 - 2^{1/3} }}$. Moreover, a symmetric
873 + integrator $ \varphi _h^{(2n + 2)}$ can be composed by
874 + \begin{equation}
875 + \varphi _h^{(2n + 2)}  = \varphi _{\alpha h}^{(2n)}  \circ \varphi
876 + _{\beta h}^{(2n)}  \circ \varphi _{\alpha h}^{(2n)}
877 + \end{equation}
878 + , if the weights are chosen as
879 + \[
880 + \alpha  =  - \frac{{2^{1/(2n + 1)} }}{{2 - 2^{1/(2n + 1)} }},\beta =
881 + \frac{{2^{1/(2n + 1)} }}{{2 - 2^{1/(2n + 1)} }} .
882 + \]
883 +
884   \section{\label{introSection:molecularDynamics}Molecular Dynamics}
885  
886   As a special discipline of molecular modeling, Molecular dynamics
# Line 660 | Line 890 | dynamical information.
890  
891   \subsection{\label{introSec:mdInit}Initialization}
892  
893 + \subsection{\label{introSec:forceEvaluation}Force Evaluation}
894 +
895   \subsection{\label{introSection:mdIntegration} Integration of the Equations of Motion}
896  
897   \section{\label{introSection:rigidBody}Dynamics of Rigid Bodies}
898  
899 < A rigid body is a body in which the distance between any two given
900 < points of a rigid body remains constant regardless of external
901 < forces exerted on it. A rigid body therefore conserves its shape
902 < during its motion.
903 <
904 < Applications of dynamics of rigid bodies.
905 <
674 < \subsection{\label{introSection:lieAlgebra}Lie Algebra}
675 <
676 < \subsection{\label{introSection:DLMMotionEquation}The Euler Equations of Rigid Body Motion}
677 <
678 < \subsection{\label{introSection:otherRBMotionEquation}Other Formulations for Rigid Body Motion}
899 > Rigid bodies are frequently involved in the modeling of different
900 > areas, from engineering, physics, to chemistry. For example,
901 > missiles and vehicle are usually modeled by rigid bodies.  The
902 > movement of the objects in 3D gaming engine or other physics
903 > simulator is governed by the rigid body dynamics. In molecular
904 > simulation, rigid body is used to simplify the model in
905 > protein-protein docking study{\cite{Gray03}}.
906  
907 < %\subsection{\label{introSection:poissonBrackets}Poisson Brackets}
907 > It is very important to develop stable and efficient methods to
908 > integrate the equations of motion of orientational degrees of
909 > freedom. Euler angles are the nature choice to describe the
910 > rotational degrees of freedom. However, due to its singularity, the
911 > numerical integration of corresponding equations of motion is very
912 > inefficient and inaccurate. Although an alternative integrator using
913 > different sets of Euler angles can overcome this difficulty\cite{},
914 > the computational penalty and the lost of angular momentum
915 > conservation still remain. A singularity free representation
916 > utilizing quaternions was developed by Evans in 1977. Unfortunately,
917 > this approach suffer from the nonseparable Hamiltonian resulted from
918 > quaternion representation, which prevents the symplectic algorithm
919 > to be utilized. Another different approach is to apply holonomic
920 > constraints to the atoms belonging to the rigid body. Each atom
921 > moves independently under the normal forces deriving from potential
922 > energy and constraint forces which are used to guarantee the
923 > rigidness. However, due to their iterative nature, SHAKE and Rattle
924 > algorithm converge very slowly when the number of constraint
925 > increases.
926  
927 < \section{\label{introSection:correlationFunctions}Correlation Functions}
927 > The break through in geometric literature suggests that, in order to
928 > develop a long-term integration scheme, one should preserve the
929 > symplectic structure of the flow. Introducing conjugate momentum to
930 > rotation matrix $A$ and re-formulating Hamiltonian's equation, a
931 > symplectic integrator, RSHAKE, was proposed to evolve the
932 > Hamiltonian system in a constraint manifold by iteratively
933 > satisfying the orthogonality constraint $A_t A = 1$. An alternative
934 > method using quaternion representation was developed by Omelyan.
935 > However, both of these methods are iterative and inefficient. In
936 > this section, we will present a symplectic Lie-Poisson integrator
937 > for rigid body developed by Dullweber and his
938 > coworkers\cite{Dullweber1997} in depth.
939  
940 + \subsection{\label{introSection:constrainedHamiltonianRB}Constrained Hamiltonian for Rigid Body}
941 + The motion of the rigid body is Hamiltonian with the Hamiltonian
942 + function
943 + \begin{equation}
944 + H = \frac{1}{2}(p^T m^{ - 1} p) + \frac{1}{2}tr(PJ^{ - 1} P) +
945 + V(q,Q) + \frac{1}{2}tr[(QQ^T  - 1)\Lambda ].
946 + \label{introEquation:RBHamiltonian}
947 + \end{equation}
948 + Here, $q$ and $Q$  are the position and rotation matrix for the
949 + rigid-body, $p$ and $P$  are conjugate momenta to $q$  and $Q$ , and
950 + $J$, a diagonal matrix, is defined by
951 + \[
952 + I_{ii}^{ - 1}  = \frac{1}{2}\sum\limits_{i \ne j} {J_{jj}^{ - 1} }
953 + \]
954 + where $I_{ii}$ is the diagonal element of the inertia tensor. This
955 + constrained Hamiltonian equation subjects to a holonomic constraint,
956 + \begin{equation}
957 + Q^T Q = 1$, \label{introEquation:orthogonalConstraint}
958 + \end{equation}
959 + which is used to ensure rotation matrix's orthogonality.
960 + Differentiating \ref{introEquation:orthogonalConstraint} and using
961 + Equation \ref{introEquation:RBMotionMomentum}, one may obtain,
962 + \begin{equation}
963 + Q^T PJ^{ - 1}  + J^{ - 1} P^T Q = 0 . \\
964 + \label{introEquation:RBFirstOrderConstraint}
965 + \end{equation}
966 +
967 + Using Equation (\ref{introEquation:motionHamiltonianCoordinate},
968 + \ref{introEquation:motionHamiltonianMomentum}), one can write down
969 + the equations of motion,
970 + \[
971 + \begin{array}{c}
972 + \frac{{dq}}{{dt}} = \frac{p}{m} \label{introEquation:RBMotionPosition}\\
973 + \frac{{dp}}{{dt}} =  - \nabla _q V(q,Q) \label{introEquation:RBMotionMomentum}\\
974 + \frac{{dQ}}{{dt}} = PJ^{ - 1}  \label{introEquation:RBMotionRotation}\\
975 + \frac{{dP}}{{dt}} =  - \nabla _Q V(q,Q) - 2Q\Lambda . \label{introEquation:RBMotionP}\\
976 + \end{array}
977 + \]
978 +
979 + In general, there are two ways to satisfy the holonomic constraints.
980 + We can use constraint force provided by lagrange multiplier on the
981 + normal manifold to keep the motion on constraint space. Or we can
982 + simply evolve the system in constraint manifold. The two method are
983 + proved to be equivalent. The holonomic constraint and equations of
984 + motions define a constraint manifold for rigid body
985 + \[
986 + M = \left\{ {(Q,P):Q^T Q = 1,Q^T PJ^{ - 1}  + J^{ - 1} P^T Q = 0}
987 + \right\}.
988 + \]
989 +
990 + Unfortunately, this constraint manifold is not the cotangent bundle
991 + $T_{\star}SO(3)$. However, it turns out that under symplectic
992 + transformation, the cotangent space and the phase space are
993 + diffeomorphic. Introducing
994 + \[
995 + \tilde Q = Q,\tilde P = \frac{1}{2}\left( {P - QP^T Q} \right),
996 + \]
997 + the mechanical system subject to a holonomic constraint manifold $M$
998 + can be re-formulated as a Hamiltonian system on the cotangent space
999 + \[
1000 + T^* SO(3) = \left\{ {(\tilde Q,\tilde P):\tilde Q^T \tilde Q =
1001 + 1,\tilde Q^T \tilde PJ^{ - 1}  + J^{ - 1} P^T \tilde Q = 0} \right\}
1002 + \]
1003 +
1004 + For a body fixed vector $X_i$ with respect to the center of mass of
1005 + the rigid body, its corresponding lab fixed vector $X_0^{lab}$  is
1006 + given as
1007 + \begin{equation}
1008 + X_i^{lab} = Q X_i + q.
1009 + \end{equation}
1010 + Therefore, potential energy $V(q,Q)$ is defined by
1011 + \[
1012 + V(q,Q) = V(Q X_0 + q).
1013 + \]
1014 + Hence, the force and torque are given by
1015 + \[
1016 + \nabla _q V(q,Q) = F(q,Q) = \sum\limits_i {F_i (q,Q)},
1017 + \]
1018 + and
1019 + \[
1020 + \nabla _Q V(q,Q) = F(q,Q)X_i^t
1021 + \]
1022 + respectively.
1023 +
1024 + As a common choice to describe the rotation dynamics of the rigid
1025 + body, angular momentum on body frame $\Pi  = Q^t P$ is introduced to
1026 + rewrite the equations of motion,
1027 + \begin{equation}
1028 + \begin{array}{l}
1029 + \mathop \Pi \limits^ \bullet   = J^{ - 1} \Pi ^T \Pi  + Q^T \sum\limits_i {F_i (q,Q)X_i^T }  - \Lambda  \\
1030 + \mathop Q\limits^{{\rm{   }} \bullet }  = Q\Pi {\rm{ }}J^{ - 1}  \\
1031 + \end{array}
1032 + \label{introEqaution:RBMotionPI}
1033 + \end{equation}
1034 + , as well as holonomic constraints,
1035 + \[
1036 + \begin{array}{l}
1037 + \Pi J^{ - 1}  + J^{ - 1} \Pi ^t  = 0 \\
1038 + Q^T Q = 1 \\
1039 + \end{array}
1040 + \]
1041 +
1042 + For a vector $v(v_1 ,v_2 ,v_3 ) \in R^3$ and a matrix $\hat v \in
1043 + so(3)^ \star$, the hat-map isomorphism,
1044 + \begin{equation}
1045 + v(v_1 ,v_2 ,v_3 ) \Leftrightarrow \hat v = \left(
1046 + {\begin{array}{*{20}c}
1047 +   0 & { - v_3 } & {v_2 }  \\
1048 +   {v_3 } & 0 & { - v_1 }  \\
1049 +   { - v_2 } & {v_1 } & 0  \\
1050 + \end{array}} \right),
1051 + \label{introEquation:hatmapIsomorphism}
1052 + \end{equation}
1053 + will let us associate the matrix products with traditional vector
1054 + operations
1055 + \[
1056 + \hat vu = v \times u
1057 + \]
1058 +
1059 + Using \ref{introEqaution:RBMotionPI}, one can construct a skew
1060 + matrix,
1061 + \begin{equation}
1062 + (\mathop \Pi \limits^ \bullet   - \mathop \Pi \limits^ \bullet  ^T
1063 + ){\rm{ }} = {\rm{ }}(\Pi  - \Pi ^T ){\rm{ }}(J^{ - 1} \Pi  + \Pi J^{
1064 + - 1} ) + \sum\limits_i {[Q^T F_i (r,Q)X_i^T  - X_i F_i (r,Q)^T Q]} -
1065 + (\Lambda  - \Lambda ^T ) . \label{introEquation:skewMatrixPI}
1066 + \end{equation}
1067 + Since $\Lambda$ is symmetric, the last term of Equation
1068 + \ref{introEquation:skewMatrixPI} is zero, which implies the Lagrange
1069 + multiplier $\Lambda$ is absent from the equations of motion. This
1070 + unique property eliminate the requirement of iterations which can
1071 + not be avoided in other methods\cite{}.
1072 +
1073 + Applying hat-map isomorphism, we obtain the equation of motion for
1074 + angular momentum on body frame
1075 + \begin{equation}
1076 + \dot \pi  = \pi  \times I^{ - 1} \pi  + \sum\limits_i {\left( {Q^T
1077 + F_i (r,Q)} \right) \times X_i }.
1078 + \label{introEquation:bodyAngularMotion}
1079 + \end{equation}
1080 + In the same manner, the equation of motion for rotation matrix is
1081 + given by
1082 + \[
1083 + \dot Q = Qskew(I^{ - 1} \pi )
1084 + \]
1085 +
1086 + \subsection{\label{introSection:SymplecticFreeRB}Symplectic
1087 + Lie-Poisson Integrator for Free Rigid Body}
1088 +
1089 + If there is not external forces exerted on the rigid body, the only
1090 + contribution to the rotational is from the kinetic potential (the
1091 + first term of \ref{ introEquation:bodyAngularMotion}). The free
1092 + rigid body is an example of Lie-Poisson system with Hamiltonian
1093 + function
1094 + \begin{equation}
1095 + T^r (\pi ) = T_1 ^r (\pi _1 ) + T_2^r (\pi _2 ) + T_3^r (\pi _3 )
1096 + \label{introEquation:rotationalKineticRB}
1097 + \end{equation}
1098 + where $T_i^r (\pi _i ) = \frac{{\pi _i ^2 }}{{2I_i }}$ and
1099 + Lie-Poisson structure matrix,
1100 + \begin{equation}
1101 + J(\pi ) = \left( {\begin{array}{*{20}c}
1102 +   0 & {\pi _3 } & { - \pi _2 }  \\
1103 +   { - \pi _3 } & 0 & {\pi _1 }  \\
1104 +   {\pi _2 } & { - \pi _1 } & 0  \\
1105 + \end{array}} \right)
1106 + \end{equation}
1107 + Thus, the dynamics of free rigid body is governed by
1108 + \begin{equation}
1109 + \frac{d}{{dt}}\pi  = J(\pi )\nabla _\pi  T^r (\pi )
1110 + \end{equation}
1111 +
1112 + One may notice that each $T_i^r$ in Equation
1113 + \ref{introEquation:rotationalKineticRB} can be solved exactly. For
1114 + instance, the equations of motion due to $T_1^r$ are given by
1115 + \begin{equation}
1116 + \frac{d}{{dt}}\pi  = R_1 \pi ,\frac{d}{{dt}}Q = QR_1
1117 + \label{introEqaution:RBMotionSingleTerm}
1118 + \end{equation}
1119 + where
1120 + \[ R_1  = \left( {\begin{array}{*{20}c}
1121 +   0 & 0 & 0  \\
1122 +   0 & 0 & {\pi _1 }  \\
1123 +   0 & { - \pi _1 } & 0  \\
1124 + \end{array}} \right).
1125 + \]
1126 + The solutions of Equation \ref{introEqaution:RBMotionSingleTerm} is
1127 + \[
1128 + \pi (\Delta t) = e^{\Delta tR_1 } \pi (0),Q(\Delta t) =
1129 + Q(0)e^{\Delta tR_1 }
1130 + \]
1131 + with
1132 + \[
1133 + e^{\Delta tR_1 }  = \left( {\begin{array}{*{20}c}
1134 +   0 & 0 & 0  \\
1135 +   0 & {\cos \theta _1 } & {\sin \theta _1 }  \\
1136 +   0 & { - \sin \theta _1 } & {\cos \theta _1 }  \\
1137 + \end{array}} \right),\theta _1  = \frac{{\pi _1 }}{{I_1 }}\Delta t.
1138 + \]
1139 + To reduce the cost of computing expensive functions in e^{\Delta
1140 + tR_1 }, we can use Cayley transformation,
1141 + \[
1142 + e^{\Delta tR_1 }  \approx (1 - \Delta tR_1 )^{ - 1} (1 + \Delta tR_1
1143 + )
1144 + \]
1145 +
1146 + The flow maps for $T_2^r$ and $T_2^r$ can be found in the same
1147 + manner.
1148 +
1149 + In order to construct a second-order symplectic method, we split the
1150 + angular kinetic Hamiltonian function can into five terms
1151 + \[
1152 + T^r (\pi ) = \frac{1}{2}T_1 ^r (\pi _1 ) + \frac{1}{2}T_2^r (\pi _2
1153 + ) + T_3^r (\pi _3 ) + \frac{1}{2}T_2^r (\pi _2 ) + \frac{1}{2}T_1 ^r
1154 + (\pi _1 )
1155 + \].
1156 + Concatenating flows corresponding to these five terms, we can obtain
1157 + an symplectic integrator,
1158 + \[
1159 + \varphi _{\Delta t,T^r }  = \varphi _{\Delta t/2,\pi _1 }  \circ
1160 + \varphi _{\Delta t/2,\pi _2 }  \circ \varphi _{\Delta t,\pi _3 }
1161 + \circ \varphi _{\Delta t/2,\pi _2 }  \circ \varphi _{\Delta t/2,\pi
1162 + _1 }.
1163 + \]
1164 +
1165 + The non-canonical Lie-Poisson bracket ${F, G}$ of two function
1166 + $F(\pi )$ and $G(\pi )$ is defined by
1167 + \[
1168 + \{ F,G\} (\pi ) = [\nabla _\pi  F(\pi )]^T J(\pi )\nabla _\pi  G(\pi
1169 + )
1170 + \]
1171 + If the Poisson bracket of a function $F$ with an arbitrary smooth
1172 + function $G$ is zero, $F$ is a \emph{Casimir}, which is the
1173 + conserved quantity in Poisson system. We can easily verify that the
1174 + norm of the angular momentum, $\parallel \pi
1175 + \parallel$, is a \emph{Casimir}. Let$ F(\pi ) = S(\frac{{\parallel
1176 + \pi \parallel ^2 }}{2})$ for an arbitrary function $ S:R \to R$ ,
1177 + then by the chain rule
1178 + \[
1179 + \nabla _\pi  F(\pi ) = S'(\frac{{\parallel \pi \parallel ^2
1180 + }}{2})\pi
1181 + \]
1182 + Thus $ [\nabla _\pi  F(\pi )]^T J(\pi ) =  - S'(\frac{{\parallel \pi
1183 + \parallel ^2 }}{2})\pi  \times \pi  = 0 $. This explicit
1184 + Lie-Poisson integrator is found to be extremely efficient and stable
1185 + which can be explained by the fact the small angle approximation is
1186 + used and the norm of the angular momentum is conserved.
1187 +
1188 + \subsection{\label{introSection:RBHamiltonianSplitting} Hamiltonian
1189 + Splitting for Rigid Body}
1190 +
1191 + The Hamiltonian of rigid body can be separated in terms of kinetic
1192 + energy and potential energy,
1193 + \[
1194 + H = T(p,\pi ) + V(q,Q)
1195 + \]
1196 + The equations of motion corresponding to potential energy and
1197 + kinetic energy are listed in the below table,
1198 + \begin{center}
1199 + \begin{tabular}{|l|l|}
1200 +  \hline
1201 +  % after \\: \hline or \cline{col1-col2} \cline{col3-col4} ...
1202 +  Potential & Kinetic \\
1203 +  $\frac{{dq}}{{dt}} = \frac{p}{m}$ & $\frac{d}{{dt}}q = p$ \\
1204 +  $\frac{d}{{dt}}p =  - \frac{{\partial V}}{{\partial q}}$ & $ \frac{d}{{dt}}p = 0$ \\
1205 +  $\frac{d}{{dt}}Q = 0$ & $ \frac{d}{{dt}}Q = Qskew(I^{ - 1} j)$ \\
1206 +  $ \frac{d}{{dt}}\pi  = \sum\limits_i {\left( {Q^T F_i (r,Q)} \right) \times X_i }$ & $\frac{d}{{dt}}\pi  = \pi  \times I^{ - 1} \pi$\\
1207 +  \hline
1208 + \end{tabular}
1209 + \end{center}
1210 + A second-order symplectic method is now obtained by the composition
1211 + of the flow maps,
1212 + \[
1213 + \varphi _{\Delta t}  = \varphi _{\Delta t/2,V}  \circ \varphi
1214 + _{\Delta t,T}  \circ \varphi _{\Delta t/2,V}.
1215 + \]
1216 + Moreover, \varphi _{\Delta t/2,V} can be divided into two sub-flows
1217 + which corresponding to force and torque respectively,
1218 + \[
1219 + \varphi _{\Delta t/2,V}  = \varphi _{\Delta t/2,F}  \circ \varphi
1220 + _{\Delta t/2,\tau }.
1221 + \]
1222 + Since the associated operators of $\varphi _{\Delta t/2,F} $ and
1223 + $\circ \varphi _{\Delta t/2,\tau }$ are commuted, the composition
1224 + order inside \varphi _{\Delta t/2,V} does not matter.
1225 +
1226 + Furthermore, kinetic potential can be separated to translational
1227 + kinetic term, $T^t (p)$, and rotational kinetic term, $T^r (\pi )$,
1228 + \begin{equation}
1229 + T(p,\pi ) =T^t (p) + T^r (\pi ).
1230 + \end{equation}
1231 + where $ T^t (p) = \frac{1}{2}p^T m^{ - 1} p $ and $T^r (\pi )$ is
1232 + defined by \ref{introEquation:rotationalKineticRB}. Therefore, the
1233 + corresponding flow maps are given by
1234 + \[
1235 + \varphi _{\Delta t,T}  = \varphi _{\Delta t,T^t }  \circ \varphi
1236 + _{\Delta t,T^r }.
1237 + \]
1238 + Finally, we obtain the overall symplectic flow maps for free moving
1239 + rigid body
1240 + \begin{equation}
1241 + \begin{array}{c}
1242 + \varphi _{\Delta t}  = \varphi _{\Delta t/2,F}  \circ \varphi _{\Delta t/2,\tau }  \\
1243 +  \circ \varphi _{\Delta t,T^t }  \circ \varphi _{\Delta t/2,\pi _1 }  \circ \varphi _{\Delta t/2,\pi _2 }  \circ \varphi _{\Delta t,\pi _3 }  \circ \varphi _{\Delta t/2,\pi _2 }  \circ \varphi _{\Delta t/2,\pi _1 }  \\
1244 +  \circ \varphi _{\Delta t/2,\tau }  \circ \varphi _{\Delta t/2,F}  .\\
1245 + \end{array}
1246 + \label{introEquation:overallRBFlowMaps}
1247 + \end{equation}
1248 +
1249   \section{\label{introSection:langevinDynamics}Langevin Dynamics}
1250  
1251   \subsection{\label{introSection:LDIntroduction}Introduction and application of Langevin Dynamics}
# Line 729 | Line 1294 | introEquation:motionHamiltonianMomentum},
1294   \dot p &=  - \frac{{\partial H}}{{\partial x}}
1295         &= m\ddot x
1296         &= - \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)}
1297 < \label{introEq:Lp5}
1297 > \label{introEquation:Lp5}
1298   \end{align}
1299   , and
1300   \begin{align}
# Line 888 | Line 1453 | Body}
1453  
1454   \subsection{\label{introSection:centersRigidBody}Centers of Rigid
1455   Body}
1456 +
1457 + \section{\label{introSection:correlationFunctions}Correlation Functions}

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