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# Line 63 | Line 63 | that if all forces are conservative, Energy $E = T + V
63   \end{equation}
64   If there are no external torques acting on a body, the angular
65   momentum of it is conserved. The last conservation theorem state
66 < that if all forces are conservative, Energy $E = T + V$ is
67 < conserved. All of these conserved quantities are important factors
68 < to determine the quality of numerical integration scheme for rigid
69 < body \cite{Dullweber1997}.
66 > that if all forces are conservative, Energy
67 > \begin{equation}E = T + V \label{introEquation:energyConservation}
68 > \end{equation}
69 > is conserved. All of these conserved quantities are
70 > important factors to determine the quality of numerical integration
71 > scheme for rigid body \cite{Dullweber1997}.
72  
73   \subsection{\label{introSection:lagrangian}Lagrangian Mechanics}
74  
# Line 200 | Line 202 | When studying Hamiltonian system, it is more convenien
202   independent variables and it only works with 1st-order differential
203   equations\cite{Marion90}.
204  
205 < When studying Hamiltonian system, it is more convenient to use
206 < notation
207 < \begin{equation}
208 < r = r(q,p)^T
207 < \end{equation}
208 < and to introduce a $2n \times 2n$ canonical structure matrix $J$,
209 < \begin{equation}
210 < J = \left( {\begin{array}{*{20}c}
211 <   0 & I  \\
212 <   { - I} & 0  \\
213 < \end{array}} \right)
214 < \label{introEquation:canonicalMatrix}
215 < \end{equation}
216 < where $I$ is a $n \times n$ identity matrix and $J$ is a
217 < skew-symmetric matrix ($ J^T  =  - J $). Thus, Hamiltonian system
218 < can be rewritten as,
205 > In Newtonian Mechanics, a system described by conservative forces
206 > conserves the total energy \ref{introEquation:energyConservation}.
207 > It follows that Hamilton's equations of motion conserve the total
208 > Hamiltonian.
209   \begin{equation}
210 < \frac{d}{{dt}}r = J\nabla _r H(r)
211 < \label{introEquation:compactHamiltonian}
210 > \frac{{dH}}{{dt}} = \sum\limits_i {\left( {\frac{{\partial
211 > H}}{{\partial q_i }}\dot q_i  + \frac{{\partial H}}{{\partial p_i
212 > }}\dot p_i } \right)}  = \sum\limits_i {\left( {\frac{{\partial
213 > H}}{{\partial q_i }}\frac{{\partial H}}{{\partial p_i }} -
214 > \frac{{\partial H}}{{\partial p_i }}\frac{{\partial H}}{{\partial
215 > q_i }}} \right) = 0} \label{introEquation:conserveHalmitonian}
216   \end{equation}
217  
224 %\subsection{\label{introSection:canonicalTransformation}Canonical
225 %Transformation}
226
227 \section{\label{introSection:geometricIntegratos}Geometric Integrators}
228
229 \subsection{\label{introSection:symplecticMaps}Symplectic Maps and Methods}
230
231 \subsection{\label{Construction of Symplectic Methods}}
232
218   \section{\label{introSection:statisticalMechanics}Statistical
219   Mechanics}
220  
# Line 238 | Line 223 | Statistical Mechanics concepts presented in this disse
223   The following section will give a brief introduction to some of the
224   Statistical Mechanics concepts presented in this dissertation.
225  
226 < \subsection{\label{introSection::ensemble}Ensemble and Phase Space}
226 > \subsection{\label{introSection:ensemble}Ensemble and Phase Space}
227  
228   \subsection{\label{introSection:ergodic}The Ergodic Hypothesis}
229  
# Line 269 | Line 254 | will be the best choice.
254   Carlo techniques\cite{metropolis:1949} can be utilized. Or if the
255   system lends itself to a time averaging approach, the Molecular
256   Dynamics techniques in Sec.~\ref{introSection:molecularDynamics}
257 < will be the best choice.
257 > will be the best choice\cite{Frenkel1996}.
258 >
259 > \section{\label{introSection:geometricIntegratos}Geometric Integrators}
260 > A variety of numerical integrators were proposed to simulate the
261 > motions. They usually begin with an initial conditionals and move
262 > the objects in the direction governed by the differential equations.
263 > However, most of them ignore the hidden physical law contained
264 > within the equations. Since 1990, geometric integrators, which
265 > preserve various phase-flow invariants such as symplectic structure,
266 > volume and time reversal symmetry, are developed to address this
267 > issue. The velocity verlet method, which happens to be a simple
268 > example of symplectic integrator, continues to gain its popularity
269 > in molecular dynamics community. This fact can be partly explained
270 > by its geometric nature.
271 >
272 > \subsection{\label{introSection:symplecticManifold}Symplectic Manifold}
273 > A \emph{manifold} is an abstract mathematical space. It locally
274 > looks like Euclidean space, but when viewed globally, it may have
275 > more complicate structure. A good example of manifold is the surface
276 > of Earth. It seems to be flat locally, but it is round if viewed as
277 > a whole. A \emph{differentiable manifold} (also known as
278 > \emph{smooth manifold}) is a manifold with an open cover in which
279 > the covering neighborhoods are all smoothly isomorphic to one
280 > another. In other words,it is possible to apply calculus on
281 > \emph{differentiable manifold}. A \emph{symplectic manifold} is
282 > defined as a pair $(M, \omega)$ which consisting of a
283 > \emph{differentiable manifold} $M$ and a close, non-degenerated,
284 > bilinear symplectic form, $\omega$. A symplectic form on a vector
285 > space $V$ is a function $\omega(x, y)$ which satisfies
286 > $\omega(\lambda_1x_1+\lambda_2x_2, y) = \lambda_1\omega(x_1, y)+
287 > \lambda_2\omega(x_2, y)$, $\omega(x, y) = - \omega(y, x)$ and
288 > $\omega(x, x) = 0$. Cross product operation in vector field is an
289 > example of symplectic form.
290 >
291 > One of the motivations to study \emph{symplectic manifold} in
292 > Hamiltonian Mechanics is that a symplectic manifold can represent
293 > all possible configurations of the system and the phase space of the
294 > system can be described by it's cotangent bundle. Every symplectic
295 > manifold is even dimensional. For instance, in Hamilton equations,
296 > coordinate and momentum always appear in pairs.
297 >
298 > Let  $(M,\omega)$ and $(N, \eta)$ be symplectic manifolds. A map
299 > \[
300 > f : M \rightarrow N
301 > \]
302 > is a \emph{symplectomorphism} if it is a \emph{diffeomorphims} and
303 > the \emph{pullback} of $\eta$ under f is equal to $\omega$.
304 > Canonical transformation is an example of symplectomorphism in
305 > classical mechanics.
306 >
307 > \subsection{\label{introSection:ODE}Ordinary Differential Equations}
308 >
309 > For a ordinary differential system defined as
310 > \begin{equation}
311 > \dot x = f(x)
312 > \end{equation}
313 > where $x = x(q,p)^T$, this system is canonical Hamiltonian, if
314 > \begin{equation}
315 > f(r) = J\nabla _x H(r).
316 > \end{equation}
317 > $H = H (q, p)$ is Hamiltonian function and $J$ is the skew-symmetric
318 > matrix
319 > \begin{equation}
320 > J = \left( {\begin{array}{*{20}c}
321 >   0 & I  \\
322 >   { - I} & 0  \\
323 > \end{array}} \right)
324 > \label{introEquation:canonicalMatrix}
325 > \end{equation}
326 > where $I$ is an identity matrix. Using this notation, Hamiltonian
327 > system can be rewritten as,
328 > \begin{equation}
329 > \frac{d}{{dt}}x = J\nabla _x H(x)
330 > \label{introEquation:compactHamiltonian}
331 > \end{equation}In this case, $f$ is
332 > called a \emph{Hamiltonian vector field}.
333 >
334 > Another generalization of Hamiltonian dynamics is Poisson Dynamics,
335 > \begin{equation}
336 > \dot x = J(x)\nabla _x H \label{introEquation:poissonHamiltonian}
337 > \end{equation}
338 > The most obvious change being that matrix $J$ now depends on $x$.
339 > The free rigid body is an example of Poisson system (actually a
340 > Lie-Poisson system) with Hamiltonian function of angular kinetic
341 > energy.
342 > \begin{equation}
343 > J(\pi ) = \left( {\begin{array}{*{20}c}
344 >   0 & {\pi _3 } & { - \pi _2 }  \\
345 >   { - \pi _3 } & 0 & {\pi _1 }  \\
346 >   {\pi _2 } & { - \pi _1 } & 0  \\
347 > \end{array}} \right)
348 > \end{equation}
349 >
350 > \begin{equation}
351 > H = \frac{1}{2}\left( {\frac{{\pi _1^2 }}{{I_1 }} + \frac{{\pi _2^2
352 > }}{{I_2 }} + \frac{{\pi _3^2 }}{{I_3 }}} \right)
353 > \end{equation}
354 >
355 > \subsection{\label{introSection:geometricProperties}Geometric Properties}
356 > Let $x(t)$ be the exact solution of the ODE system,
357 > \begin{equation}
358 > \frac{{dx}}{{dt}} = f(x) \label{introEquation:ODE}
359 > \end{equation}
360 > The exact flow(solution) $\varphi_\tau$ is defined by
361 > \[
362 > x(t+\tau) =\varphi_\tau(x(t))
363 > \]
364 > where $\tau$ is a fixed time step and $\varphi$ is a map from phase
365 > space to itself. In most cases, it is not easy to find the exact
366 > flow $\varphi_\tau$. Instead, we use a approximate map, $\psi_\tau$,
367 > which is usually called integrator. The order of an integrator
368 > $\psi_\tau$ is $p$, if the Taylor series of $\psi_\tau$ agree to
369 > order $p$,
370 > \begin{equation}
371 > \psi_tau(x) = x + \tau f(x) + O(\tau^{p+1})
372 > \end{equation}
373 >
374 > The hidden geometric properties of ODE and its flow play important
375 > roles in numerical studies. Let $\varphi$ be the flow of Hamiltonian
376 > vector field, $\varphi$ is a \emph{symplectic} flow if it satisfies,
377 > \begin{equation}
378 > '\varphi^T J '\varphi = J.
379 > \end{equation}
380 > According to Liouville's theorem, the symplectic volume is invariant
381 > under a Hamiltonian flow, which is the basis for classical
382 > statistical mechanics. Furthermore, the flow of a Hamiltonian vector
383 > field on a symplectic manifold can be shown to be a
384 > symplectomorphism. As to the Poisson system,
385 > \begin{equation}
386 > '\varphi ^T J '\varphi  = J \circ \varphi
387 > \end{equation}
388 > is the property must be preserved by the integrator. It is possible
389 > to construct a \emph{volume-preserving} flow for a source free($
390 > \nabla \cdot f = 0 $) ODE, if the flow satisfies $ \det d\varphi  =
391 > 1$. Changing the variables $y = h(x)$ in a
392 > ODE\ref{introEquation:ODE} will result in a new system,
393 > \[
394 > \dot y = \tilde f(y) = ((dh \cdot f)h^{ - 1} )(y).
395 > \]
396 > The vector filed $f$ has reversing symmetry $h$ if $f = - \tilde f$.
397 > In other words, the flow of this vector field is reversible if and
398 > only if $ h \circ \varphi ^{ - 1}  = \varphi  \circ h $. When
399 > designing any numerical methods, one should always try to preserve
400 > the structural properties of the original ODE and its flow.
401 >
402 > \subsection{\label{introSection:constructionSymplectic}Construction of Symplectic Methods}
403 > A lot of well established and very effective numerical methods have
404 > been successful precisely because of their symplecticities even
405 > though this fact was not recognized when they were first
406 > constructed. The most famous example is leapfrog methods in
407 > molecular dynamics. In general, symplectic integrators can be
408 > constructed using one of four different methods.
409 > \begin{enumerate}
410 > \item Generating functions
411 > \item Variational methods
412 > \item Runge-Kutta methods
413 > \item Splitting methods
414 > \end{enumerate}
415 >
416 > Generating function tends to lead to methods which are cumbersome
417 > and difficult to use\cite{}. In dissipative systems, variational
418 > methods can capture the decay of energy accurately\cite{}. Since
419 > their geometrically unstable nature against non-Hamiltonian
420 > perturbations, ordinary implicit Runge-Kutta methods are not
421 > suitable for Hamiltonian system. Recently, various high-order
422 > explicit Runge--Kutta methods have been developed to overcome this
423 > instability \cite{}. However, due to computational penalty involved
424 > in implementing the Runge-Kutta methods, they do not attract too
425 > much attention from Molecular Dynamics community. Instead, splitting
426 > have been widely accepted since they exploit natural decompositions
427 > of the system\cite{Tuckerman92}. The main idea behind splitting
428 > methods is to decompose the discrete $\varphi_h$ as a composition of
429 > simpler flows,
430 > \begin{equation}
431 > \varphi _h  = \varphi _{h_1 }  \circ \varphi _{h_2 }  \ldots  \circ
432 > \varphi _{h_n }
433 > \label{introEquation:FlowDecomposition}
434 > \end{equation}
435 > where each of the sub-flow is chosen such that each represent a
436 > simpler integration of the system. Let $\phi$ and $\psi$ both be
437 > symplectic maps, it is easy to show that any composition of
438 > symplectic flows yields a symplectic map,
439 > \begin{equation}
440 > (\varphi '\phi ')^T J\varphi '\phi ' = \phi '^T \varphi '^T J\varphi
441 > '\phi ' = \phi '^T J\phi ' = J.
442 > \label{introEquation:SymplecticFlowComposition}
443 > \end{equation}
444 > Suppose that a Hamiltonian system has a form with $H = T + V$
445  
446 +
447 +
448   \section{\label{introSection:molecularDynamics}Molecular Dynamics}
449  
450   As a special discipline of molecular modeling, Molecular dynamics
# Line 303 | Line 477 | Applications of dynamics of rigid bodies.
477  
478   \section{\label{introSection:langevinDynamics}Langevin Dynamics}
479  
480 + \subsection{\label{introSection:LDIntroduction}Introduction and application of Langevin Dynamics}
481 +
482   \subsection{\label{introSection:generalizedLangevinDynamics}Generalized Langevin Dynamics}
483  
484 < \subsection{\label{introSection:hydroynamics}Hydrodynamics}
484 > \begin{equation}
485 > H = \frac{{p^2 }}{{2m}} + U(x) + H_B  + \Delta U(x,x_1 , \ldots x_N)
486 > \label{introEquation:bathGLE}
487 > \end{equation}
488 > where $H_B$ is harmonic bath Hamiltonian,
489 > \[
490 > H_B  =\sum\limits_{\alpha  = 1}^N {\left\{ {\frac{{p_\alpha ^2
491 > }}{{2m_\alpha  }} + \frac{1}{2}m_\alpha  w_\alpha ^2 } \right\}}
492 > \]
493 > and $\Delta U$ is bilinear system-bath coupling,
494 > \[
495 > \Delta U =  - \sum\limits_{\alpha  = 1}^N {g_\alpha  x_\alpha  x}
496 > \]
497 > Completing the square,
498 > \[
499 > H_B  + \Delta U = \sum\limits_{\alpha  = 1}^N {\left\{
500 > {\frac{{p_\alpha ^2 }}{{2m_\alpha  }} + \frac{1}{2}m_\alpha
501 > w_\alpha ^2 \left( {x_\alpha   - \frac{{g_\alpha  }}{{m_\alpha
502 > w_\alpha ^2 }}x} \right)^2 } \right\}}  - \sum\limits_{\alpha  =
503 > 1}^N {\frac{{g_\alpha ^2 }}{{2m_\alpha  w_\alpha ^2 }}} x^2
504 > \]
505 > and putting it back into Eq.~\ref{introEquation:bathGLE},
506 > \[
507 > H = \frac{{p^2 }}{{2m}} + W(x) + \sum\limits_{\alpha  = 1}^N
508 > {\left\{ {\frac{{p_\alpha ^2 }}{{2m_\alpha  }} + \frac{1}{2}m_\alpha
509 > w_\alpha ^2 \left( {x_\alpha   - \frac{{g_\alpha  }}{{m_\alpha
510 > w_\alpha ^2 }}x} \right)^2 } \right\}}
511 > \]
512 > where
513 > \[
514 > W(x) = U(x) - \sum\limits_{\alpha  = 1}^N {\frac{{g_\alpha ^2
515 > }}{{2m_\alpha  w_\alpha ^2 }}} x^2
516 > \]
517 > Since the first two terms of the new Hamiltonian depend only on the
518 > system coordinates, we can get the equations of motion for
519 > Generalized Langevin Dynamics by Hamilton's equations
520 > \ref{introEquation:motionHamiltonianCoordinate,
521 > introEquation:motionHamiltonianMomentum},
522 > \begin{align}
523 > \dot p &=  - \frac{{\partial H}}{{\partial x}}
524 >       &= m\ddot x
525 >       &= - \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)}
526 > \label{introEq:Lp5}
527 > \end{align}
528 > , and
529 > \begin{align}
530 > \dot p_\alpha   &=  - \frac{{\partial H}}{{\partial x_\alpha  }}
531 >                &= m\ddot x_\alpha
532 >                &= \- m_\alpha  w_\alpha ^2 \left( {x_\alpha   - \frac{{g_\alpha}}{{m_\alpha  w_\alpha ^2 }}x} \right)
533 > \end{align}
534 >
535 > \subsection{\label{introSection:laplaceTransform}The Laplace Transform}
536 >
537 > \[
538 > L(x) = \int_0^\infty  {x(t)e^{ - pt} dt}
539 > \]
540 >
541 > \[
542 > L(x + y) = L(x) + L(y)
543 > \]
544 >
545 > \[
546 > L(ax) = aL(x)
547 > \]
548 >
549 > \[
550 > L(\dot x) = pL(x) - px(0)
551 > \]
552 >
553 > \[
554 > L(\ddot x) = p^2 L(x) - px(0) - \dot x(0)
555 > \]
556 >
557 > \[
558 > L\left( {\int_0^t {g(t - \tau )h(\tau )d\tau } } \right) = G(p)H(p)
559 > \]
560 >
561 > Some relatively important transformation,
562 > \[
563 > L(\cos at) = \frac{p}{{p^2  + a^2 }}
564 > \]
565 >
566 > \[
567 > L(\sin at) = \frac{a}{{p^2  + a^2 }}
568 > \]
569 >
570 > \[
571 > L(1) = \frac{1}{p}
572 > \]
573 >
574 > First, the bath coordinates,
575 > \[
576 > p^2 L(x_\alpha  ) - px_\alpha  (0) - \dot x_\alpha  (0) =  - \omega
577 > _\alpha ^2 L(x_\alpha  ) + \frac{{g_\alpha  }}{{\omega _\alpha
578 > }}L(x)
579 > \]
580 > \[
581 > L(x_\alpha  ) = \frac{{\frac{{g_\alpha  }}{{\omega _\alpha  }}L(x) +
582 > px_\alpha  (0) + \dot x_\alpha  (0)}}{{p^2  + \omega _\alpha ^2 }}
583 > \]
584 > Then, the system coordinates,
585 > \begin{align}
586 > mL(\ddot x) &=  - \frac{1}{p}\frac{{\partial W(x)}}{{\partial x}} -
587 > \sum\limits_{\alpha  = 1}^N {\left\{ {\frac{{\frac{{g_\alpha
588 > }}{{\omega _\alpha  }}L(x) + px_\alpha  (0) + \dot x_\alpha
589 > (0)}}{{p^2  + \omega _\alpha ^2 }} - \frac{{g_\alpha ^2 }}{{m_\alpha
590 > }}\omega _\alpha ^2 L(x)} \right\}}
591 > %
592 > &= - \frac{1}{p}\frac{{\partial W(x)}}{{\partial x}} -
593 > \sum\limits_{\alpha  = 1}^N {\left\{ { - \frac{{g_\alpha ^2 }}{{m_\alpha  \omega _\alpha ^2 }}\frac{p}{{p^2  + \omega _\alpha ^2 }}pL(x)
594 > - \frac{p}{{p^2  + \omega _\alpha ^2 }}g_\alpha  x_\alpha  (0)
595 > - \frac{1}{{p^2  + \omega _\alpha ^2 }}g_\alpha  \dot x_\alpha  (0)} \right\}}
596 > \end{align}
597 > Then, the inverse transform,
598 >
599 > \begin{align}
600 > m\ddot x &=  - \frac{{\partial W(x)}}{{\partial x}} -
601 > \sum\limits_{\alpha  = 1}^N {\left\{ {\left( { - \frac{{g_\alpha ^2
602 > }}{{m_\alpha  \omega _\alpha ^2 }}} \right)\int_0^t {\cos (\omega
603 > _\alpha  t)\dot x(t - \tau )d\tau  - \left[ {g_\alpha  x_\alpha  (0)
604 > - \frac{{g_\alpha  }}{{m_\alpha  \omega _\alpha  }}} \right]\cos
605 > (\omega _\alpha  t) - \frac{{g_\alpha  \dot x_\alpha  (0)}}{{\omega
606 > _\alpha  }}\sin (\omega _\alpha  t)} } \right\}}
607 > %
608 > &= - \frac{{\partial W(x)}}{{\partial x}} - \int_0^t
609 > {\sum\limits_{\alpha  = 1}^N {\left( { - \frac{{g_\alpha ^2
610 > }}{{m_\alpha  \omega _\alpha ^2 }}} \right)\cos (\omega _\alpha
611 > t)\dot x(t - \tau )d} \tau }  + \sum\limits_{\alpha  = 1}^N {\left\{
612 > {\left[ {g_\alpha  x_\alpha  (0) - \frac{{g_\alpha  }}{{m_\alpha
613 > \omega _\alpha  }}} \right]\cos (\omega _\alpha  t) +
614 > \frac{{g_\alpha  \dot x_\alpha  (0)}}{{\omega _\alpha  }}\sin
615 > (\omega _\alpha  t)} \right\}}
616 > \end{align}
617 >
618 > \begin{equation}
619 > m\ddot x =  - \frac{{\partial W}}{{\partial x}} - \int_0^t {\xi
620 > (t)\dot x(t - \tau )d\tau }  + R(t)
621 > \label{introEuqation:GeneralizedLangevinDynamics}
622 > \end{equation}
623 > %where $ {\xi (t)}$ is friction kernel, $R(t)$ is random force and
624 > %$W$ is the potential of mean force. $W(x) =  - kT\ln p(x)$
625 > \[
626 > \xi (t) = \sum\limits_{\alpha  = 1}^N {\left( { - \frac{{g_\alpha ^2
627 > }}{{m_\alpha  \omega _\alpha ^2 }}} \right)\cos (\omega _\alpha  t)}
628 > \]
629 > For an infinite harmonic bath, we can use the spectral density and
630 > an integral over frequencies.
631 >
632 > \[
633 > R(t) = \sum\limits_{\alpha  = 1}^N {\left( {g_\alpha  x_\alpha  (0)
634 > - \frac{{g_\alpha ^2 }}{{m_\alpha  \omega _\alpha ^2 }}x(0)}
635 > \right)\cos (\omega _\alpha  t)}  + \frac{{\dot x_\alpha
636 > (0)}}{{\omega _\alpha  }}\sin (\omega _\alpha  t)
637 > \]
638 > The random forces depend only on initial conditions.
639 >
640 > \subsubsection{\label{introSection:secondFluctuationDissipation}The Second Fluctuation Dissipation Theorem}
641 > So we can define a new set of coordinates,
642 > \[
643 > q_\alpha  (t) = x_\alpha  (t) - \frac{1}{{m_\alpha  \omega _\alpha
644 > ^2 }}x(0)
645 > \]
646 > This makes
647 > \[
648 > R(t) = \sum\limits_{\alpha  = 1}^N {g_\alpha  q_\alpha  (t)}
649 > \]
650 > And since the $q$ coordinates are harmonic oscillators,
651 > \[
652 > \begin{array}{l}
653 > \left\langle {q_\alpha  (t)q_\alpha  (0)} \right\rangle  = \left\langle {q_\alpha ^2 (0)} \right\rangle \cos (\omega _\alpha  t) \\
654 > \left\langle {q_\alpha  (t)q_\beta  (0)} \right\rangle  = \delta _{\alpha \beta } \left\langle {q_\alpha  (t)q_\alpha  (0)} \right\rangle  \\
655 > \end{array}
656 > \]
657 >
658 > \begin{align}
659 > \left\langle {R(t)R(0)} \right\rangle  &= \sum\limits_\alpha
660 > {\sum\limits_\beta  {g_\alpha  g_\beta  \left\langle {q_\alpha
661 > (t)q_\beta  (0)} \right\rangle } }
662 > %
663 > &= \sum\limits_\alpha  {g_\alpha ^2 \left\langle {q_\alpha ^2 (0)}
664 > \right\rangle \cos (\omega _\alpha  t)}
665 > %
666 > &= kT\xi (t)
667 > \end{align}
668 >
669 > \begin{equation}
670 > \xi (t) = \left\langle {R(t)R(0)} \right\rangle
671 > \label{introEquation:secondFluctuationDissipation}
672 > \end{equation}
673 >
674 > \section{\label{introSection:hydroynamics}Hydrodynamics}
675 >
676 > \subsection{\label{introSection:frictionTensor} Friction Tensor}
677 > \subsection{\label{introSection:analyticalApproach}Analytical
678 > Approach}
679 >
680 > \subsection{\label{introSection:approximationApproach}Approximation
681 > Approach}
682 >
683 > \subsection{\label{introSection:centersRigidBody}Centers of Rigid
684 > Body}

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