ViewVC Help
View File | Revision Log | Show Annotations | View Changeset | Root Listing
root/group/trunk/tengDissertation/Methodology.tex
(Generate patch)

Comparing trunk/tengDissertation/Methodology.tex (file contents):
Revision 2798 by tim, Tue Jun 6 14:12:59 2006 UTC vs.
Revision 2855 by tim, Sun Jun 11 02:55:13 2006 UTC

# Line 16 | Line 16 | two decades. Matubayasi and Nakahara developed a time-
16  
17   Integration schemes for rotational motion of the rigid molecules in
18   microcanonical ensemble have been extensively studied in the last
19 < two decades. Matubayasi and Nakahara developed a time-reversible
20 < integrator for rigid bodies in quaternion representation. Although
21 < it is not symplectic, this integrator still demonstrates a better
22 < long-time energy conservation than traditional methods because of
23 < the time-reversible nature. Extending Trotter-Suzuki to general
24 < system with a flat phase space, Miller and his colleagues devised an
25 < novel symplectic, time-reversible and volume-preserving integrator
26 < in quaternion representation, which was shown to be superior to the
27 < time-reversible integrator of Matubayasi and Nakahara. However, all
28 < of the integrators in quaternion representation suffer from the
19 > two decades. Matubayasi developed a time-reversible integrator for
20 > rigid bodies in quaternion representation. Although it is not
21 > symplectic, this integrator still demonstrates a better long-time
22 > energy conservation than traditional methods because of the
23 > time-reversible nature. Extending Trotter-Suzuki to general system
24 > with a flat phase space, Miller and his colleagues devised an novel
25 > symplectic, time-reversible and volume-preserving integrator in
26 > quaternion representation, which was shown to be superior to the
27 > Matubayasi's time-reversible integrator. However, all of the
28 > integrators in quaternion representation suffer from the
29   computational penalty of constructing a rotation matrix from
30   quaternions to evolve coordinates and velocities at every time step.
31   An alternative integration scheme utilizing rotation matrix directly
# Line 117 | Line 117 | torques are calculated at the new positions and orient
117      \cdot {\bf \tau}^s(t + h).
118   \end{align*}
119  
120 < {\sc oopse} automatically updates ${\bf u}$ when the rotation matrix
120 > ${\bf u}$ will be automatically updated when the rotation matrix
121   $\mathsf{A}$ is calculated in {\tt moveA}.  Once the forces and
122   torques have been obtained at the new time step, the velocities can
123   be advanced to the same time value.
# Line 139 | Line 139 | in Fig.~\ref{timestep}.
139   average 7\% increase in computation time using the DLM method in
140   place of quaternions. This cost is more than justified when
141   comparing the energy conservation of the two methods as illustrated
142 < in Fig.~\ref{timestep}.
142 > in Fig.~\ref{methodFig:timestep}.
143  
144   \begin{figure}
145   \centering
# Line 150 | Line 150 | from the true energy baseline for clarity.} \label{tim
150   increasing time step. For each time step, the dotted line is total
151   energy using the DLM integrator, and the solid line comes from the
152   quaternion integrator. The larger time step plots are shifted up
153 < from the true energy baseline for clarity.} \label{timestep}
153 > from the true energy baseline for clarity.}
154 > \label{methodFig:timestep}
155   \end{figure}
156  
157 < In Fig.~\ref{timestep}, the resulting energy drift at various time
158 < steps for both the DLM and quaternion integration schemes is
159 < compared. All of the 1000 molecule water simulations started with
160 < the same configuration, and the only difference was the method for
161 < handling rotational motion. At time steps of 0.1 and 0.5 fs, both
162 < methods for propagating molecule rotation conserve energy fairly
163 < well, with the quaternion method showing a slight energy drift over
164 < time in the 0.5 fs time step simulation. At time steps of 1 and 2
165 < fs, the energy conservation benefits of the DLM method are clearly
166 < demonstrated. Thus, while maintaining the same degree of energy
167 < conservation, one can take considerably longer time steps, leading
168 < to an overall reduction in computation time.
157 > In Fig.~\ref{methodFig:timestep}, the resulting energy drift at
158 > various time steps for both the DLM and quaternion integration
159 > schemes is compared. All of the 1000 molecule water simulations
160 > started with the same configuration, and the only difference was the
161 > method for handling rotational motion. At time steps of 0.1 and 0.5
162 > fs, both methods for propagating molecule rotation conserve energy
163 > fairly well, with the quaternion method showing a slight energy
164 > drift over time in the 0.5 fs time step simulation. At time steps of
165 > 1 and 2 fs, the energy conservation benefits of the DLM method are
166 > clearly demonstrated. Thus, while maintaining the same degree of
167 > energy conservation, one can take considerably longer time steps,
168 > leading to an overall reduction in computation time.
169  
170   \subsection{\label{methodSection:NVT}Nos\'{e}-Hoover Thermostatting}
171  
172 < The Nos\'e-Hoover equations of motion are given by\cite{Hoover85}
172 > The Nos\'e-Hoover equations of motion are given by\cite{Hoover1985}
173   \begin{eqnarray}
174   \dot{{\bf r}} & = & {\bf v}, \\
175   \dot{{\bf v}} & = & \frac{{\bf f}}{m} - \chi {\bf v} ,\\
# Line 277 | Line 278 | self-consistent.  The relative tolerance for the self-
278   caclculate $T(t + h)$ as well as $\chi(t + h)$, they indirectly
279   depend on their own values at time $t + h$.  {\tt moveB} is
280   therefore done in an iterative fashion until $\chi(t + h)$ becomes
281 < self-consistent.  The relative tolerance for the self-consistency
281 < check defaults to a value of $\mbox{10}^{-6}$, but {\sc oopse} will
282 < terminate the iteration after 4 loops even if the consistency check
283 < has not been satisfied.
281 > self-consistent.
282  
283   The Nos\'e-Hoover algorithm is known to conserve a Hamiltonian for
284   the extended system that is, to within a constant, identical to the
285 < Helmholtz free energy,\cite{melchionna93}
285 > Helmholtz free energy,\cite{Melchionna1993}
286   \begin{equation}
287   H_{\mathrm{NVT}} = V + K + f k_B T_{\mathrm{target}} \left(
288   \frac{\tau_{T}^2 \chi^2(t)}{2} + \int_{0}^{t} \chi(t^\prime)
# Line 294 | Line 292 | of the integration.
292   $H_{\mathrm{NVT}}$, so the conserved quantity is maintained in the
293   last column of the {\tt .stat} file to allow checks on the quality
294   of the integration.
297
298 Bond constraints are applied at the end of both the {\tt moveA} and
299 {\tt moveB} portions of the algorithm.  Details on the constraint
300 algorithms are given in section \ref{oopseSec:rattle}.
295  
296   \subsection{\label{methodSection:NPTi}Constant-pressure integration with
297   isotropic box deformations (NPTi)}
298  
299 < To carry out isobaric-isothermal ensemble calculations {\sc oopse}
300 < implements the Melchionna modifications to the
301 < Nos\'e-Hoover-Andersen equations of motion,\cite{melchionna93}
299 > Isobaric-isothermal ensemble integrator is implemented using the
300 > Melchionna modifications to the Nos\'e-Hoover-Andersen equations of
301 > motion,\cite{Melchionna1993}
302  
303   \begin{eqnarray}
304   \dot{{\bf r}} & = & {\bf v} + \eta \left( {\bf r} - {\bf R}_0 \right), \\
# Line 359 | Line 353 | relaxation of the pressure to the target value.  To se
353   \end{equation}
354  
355   In eq.(\ref{eq:melchionna1}), $\tau_B$ is the time constant for
356 < relaxation of the pressure to the target value.  To set values for
363 < $\tau_B$ or $P_{\mathrm{target}}$ in a simulation, one would use the
364 < {\tt tauBarostat} and {\tt targetPressure} keywords in the {\tt
365 < .bass} file.  The units for {\tt tauBarostat} are fs, and the units
366 < for the {\tt targetPressure} are atmospheres.  Like in the NVT
356 > relaxation of the pressure to the target value. Like in the NVT
357   integrator, the integration of the equations of motion is carried
358   out in a velocity-Verlet style 2 part algorithm:
359  
# Line 404 | Line 394 | depends on the positions at the same time.  {\sc oopse
394  
395   Most of these equations are identical to their counterparts in the
396   NVT integrator, but the propagation of positions to time $t + h$
397 < depends on the positions at the same time.  {\sc oopse} carries out
398 < this step iteratively (with a limit of 5 passes through the
399 < iterative loop).  Also, the simulation box $\mathsf{H}$ is scaled
400 < uniformly for one full time step by an exponential factor that
401 < depends on the value of $\eta$ at time $t + h / 2$.  Reshaping the
412 < box uniformly also scales the volume of the box by
397 > depends on the positions at the same time. The simulation box
398 > $\mathsf{H}$ is scaled uniformly for one full time step by an
399 > exponential factor that depends on the value of $\eta$ at time $t +
400 > h / 2$.  Reshaping the box uniformly also scales the volume of the
401 > box by
402   \begin{equation}
403   \mathcal{V}(t + h) \leftarrow e^{ - 3 h \eta(t + h /2)}.
404   \mathcal{V}(t)
# Line 451 | Line 440 | + h)$ and $\eta(t + h)$ become self-consistent.  The r
440   to caclculate $T(t + h)$, $P(t + h)$, $\chi(t + h)$, and $\eta(t +
441   h)$, they indirectly depend on their own values at time $t + h$.
442   {\tt moveB} is therefore done in an iterative fashion until $\chi(t
443 < + h)$ and $\eta(t + h)$ become self-consistent.  The relative
455 < tolerance for the self-consistency check defaults to a value of
456 < $\mbox{10}^{-6}$, but {\sc oopse} will terminate the iteration after
457 < 4 loops even if the consistency check has not been satisfied.
443 > + h)$ and $\eta(t + h)$ become self-consistent.
444  
445   The Melchionna modification of the Nos\'e-Hoover-Andersen algorithm
446   is known to conserve a Hamiltonian for the extended system that is,
# Line 476 | Line 462 | Bond constraints are applied at the end of both the {\
462   P_{\mathrm{target}} \mathcal{V}(t).
463   \end{equation}
464  
479 Bond constraints are applied at the end of both the {\tt moveA} and
480 {\tt moveB} portions of the algorithm.  Details on the constraint
481 algorithms are given in section \ref{oopseSec:rattle}.
482
465   \subsection{\label{methodSection:NPTf}Constant-pressure integration with a
466   flexible box (NPTf)}
467  
# Line 553 | Line 535 | r}(t)\right\},
535   \mathsf{H}(t + h) &\leftarrow \mathsf{H}(t) \cdot e^{-h
536      \overleftrightarrow{\eta}(t + h / 2)} .
537   \end{align*}
538 < {\sc oopse} uses a power series expansion truncated at second order
539 < for the exponential operation which scales the simulation box.
538 > Here, a power series expansion truncated at second order for the
539 > exponential operation is used to scale the simulation box.
540  
541   The {\tt moveB} portion of the algorithm is largely unchanged from
542   the NPTi integrator:
# Line 593 | Line 575 | The NPTf integrator is known to conserve the following
575   identical to those described for the NPTi integrator.
576  
577   The NPTf integrator is known to conserve the following Hamiltonian:
578 < \begin{equation}
579 < H_{\mathrm{NPTf}} = V + K + f k_B T_{\mathrm{target}} \left(
578 > \begin{eqnarray*}
579 > H_{\mathrm{NPTf}} & = & V + K + f k_B T_{\mathrm{target}} \left(
580   \frac{\tau_{T}^2 \chi^2(t)}{2} + \int_{0}^{t} \chi(t^\prime)
581 < dt^\prime \right) + P_{\mathrm{target}} \mathcal{V}(t) + \frac{f k_B
582 < T_{\mathrm{target}}}{2}
581 > dt^\prime \right) \\
582 > + P_{\mathrm{target}} \mathcal{V}(t) + \frac{f
583 > k_B T_{\mathrm{target}}}{2}
584   \mathrm{Tr}\left[\overleftrightarrow{\eta}(t)\right]^2 \tau_B^2.
585 < \end{equation}
585 > \end{eqnarray*}
586  
587   This integrator must be used with care, particularly in liquid
588   simulations.  Liquids have very small restoring forces in the
# Line 609 | Line 592 | assume non-orthorhombic geometries.
592   finds most use in simulating crystals or liquid crystals which
593   assume non-orthorhombic geometries.
594  
595 < \subsection{\label{methodSection:otherSpecialEnsembles}Other Special Ensembles}
595 > \subsection{\label{methodSection:NPAT}NPAT Ensemble}
596  
614 \subsubsection{\label{methodSection:NPAT}NPAT Ensemble}
615
597   A comprehensive understanding of structure¨Cfunction relations of
598   biological membrane system ultimately relies on structure and
599   dynamics of lipid bilayer, which are strongly affected by the
# Line 623 | Line 604 | standard NPT ensemble with a different pressure contro
604   standard NPT ensemble with a different pressure control strategy
605  
606   \begin{equation}
607 < \.{\overleftrightarrow{{\eta _{\alpha \beta}}}}=\left\{\begin{array}{ll}
607 > \dot {\overleftrightarrow{\eta}} _{\alpha \beta}=\left\{\begin{array}{ll}
608                    \frac{{V(P_{\alpha \beta }  - P_{{\rm{target}}} )}}{{\tau_{\rm{B}}^{\rm{2}} fk_B T_{{\rm{target}}} }}
609 <                  & \mbox{if \[ \alpha = \beta  = z)$}\\
609 >                  & \mbox{if $ \alpha = \beta  = z$}\\
610                    0 & \mbox{otherwise}\\
611             \end{array}
612      \right.
# Line 634 | Line 615 | described for the NPTi integrator.
615   Note that the iterative schemes for NPAT are identical to those
616   described for the NPTi integrator.
617  
618 < \subsubsection{\label{methodSection:NPrT}NP$\gamma$T Ensemble}
618 > \subsection{\label{methodSection:NPrT}NP$\gamma$T
619 > Ensemble}
620  
621   Theoretically, the surface tension $\gamma$ of a stress free
622   membrane system should be zero since its surface free energy $G$ is
# Line 649 | Line 631 | $\eta$, in $NP\gamma T$ is
631   pressure. The equation of motion for cell size control tensor,
632   $\eta$, in $NP\gamma T$ is
633   \begin{equation}
634 < \.{\overleftrightarrow{{\eta _{\alpha \beta}}}}=\left\{\begin{array}{ll}
634 > \dot {\overleftrightarrow{\eta}} _{\alpha \beta}=\left\{\begin{array}{ll}
635      - A_{xy} (\gamma _\alpha   - \gamma _{{\rm{target}}} ) & \mbox{$\alpha  = \beta  = x$ or $\alpha  = \beta  = y$}\\
636      \frac{{V(P_{\alpha \beta }  - P_{{\rm{target}}} )}}{{\tau _{\rm{B}}^{\rm{2}} fk_B T_{{\rm{target}}}}} & \mbox{$\alpha  = \beta  = z$} \\
637      0 & \mbox{$\alpha  \ne \beta$} \\
638 +       \end{array}
639      \right.
640   \end{equation}
641   where $ \gamma _{{\rm{target}}}$ is the external surface tension and
642   the instantaneous surface tensor $\gamma _\alpha$ is given by
643   \begin{equation}
644 < \gamma _\alpha   =  - h_z
645 < (\mathord{\buildrel{\lower3pt\hbox{$\scriptscriptstyle\leftrightarrow$}}
663 < \over P} _{\alpha \alpha }  - P_{{\rm{target}}} )
644 > \gamma _\alpha   =  - h_z( \overleftrightarrow{P} _{\alpha \alpha }
645 > - P_{{\rm{target}}} )
646   \label{methodEquation:instantaneousSurfaceTensor}
647   \end{equation}
648  
# Line 672 | Line 654 | $\gamma$ is set to zero.
654   integrator is a special case of $NP\gamma T$ if the surface tension
655   $\gamma$ is set to zero.
656  
657 < %\section{\label{methodSection:constraintMethod}Constraint Method}
657 > \section{\label{methodSection:zcons}Z-Constraint Method}
658  
659 < %\subsection{\label{methodSection:bondConstraint}Bond Constraint for Rigid Body}
659 > Based on the fluctuation-dissipation theorem, a force
660 > auto-correlation method was developed by Roux and Karplus to
661 > investigate the dynamics of ions inside ion channels\cite{Roux1991}.
662 > The time-dependent friction coefficient can be calculated from the
663 > deviation of the instantaneous force from its mean force.
664 > \begin{equation}
665 > \xi(z,t)=\langle\delta F(z,t)\delta F(z,0)\rangle/k_{B}T,
666 > \end{equation}
667 > where%
668 > \begin{equation}
669 > \delta F(z,t)=F(z,t)-\langle F(z,t)\rangle.
670 > \end{equation}
671  
672 < %\subsection{\label{methodSection:zcons}Z-constraint Method}
672 > If the time-dependent friction decays rapidly, the static friction
673 > coefficient can be approximated by
674 > \begin{equation}
675 > \xi_{\text{static}}(z)=\int_{0}^{\infty}\langle\delta F(z,t)\delta
676 > F(z,0)\rangle dt.
677 > \end{equation}
678 > Allowing diffusion constant to then be calculated through the
679 > Einstein relation:\cite{Marrink1994}
680 > \begin{equation}
681 > D(z)=\frac{k_{B}T}{\xi_{\text{static}}(z)}=\frac{(k_{B}T)^{2}}{\int_{0}^{\infty
682 > }\langle\delta F(z,t)\delta F(z,0)\rangle dt}.%
683 > \end{equation}
684  
685 < \section{\label{methodSection:langevin}Integrators for Langevin Dynamics of Rigid Bodies}
685 > The Z-Constraint method, which fixes the z coordinates of the
686 > molecules with respect to the center of the mass of the system, has
687 > been a method suggested to obtain the forces required for the force
688 > auto-correlation calculation.\cite{Marrink1994} However, simply
689 > resetting the coordinate will move the center of the mass of the
690 > whole system. To avoid this problem, we reset the forces of
691 > z-constrained molecules as well as subtract the total constraint
692 > forces from the rest of the system after the force calculation at
693 > each time step instead of resetting the coordinate.
694  
695 < \subsection{\label{methodSection:temperature}Temperature Control}
695 > After the force calculation, define $G_\alpha$ as
696 > \begin{equation}
697 > G_{\alpha} = \sum_i F_{\alpha i}, \label{oopseEq:zc1}
698 > \end{equation}
699 > where $F_{\alpha i}$ is the force in the z direction of atom $i$ in
700 > z-constrained molecule $\alpha$. The forces of the z constrained
701 > molecule are then set to:
702 > \begin{equation}
703 > F_{\alpha i} = F_{\alpha i} -
704 >    \frac{m_{\alpha i} G_{\alpha}}{\sum_i m_{\alpha i}}.
705 > \end{equation}
706 > Here, $m_{\alpha i}$ is the mass of atom $i$ in the z-constrained
707 > molecule. Having rescaled the forces, the velocities must also be
708 > rescaled to subtract out any center of mass velocity in the z
709 > direction.
710 > \begin{equation}
711 > v_{\alpha i} = v_{\alpha i} -
712 >    \frac{\sum_i m_{\alpha i} v_{\alpha i}}{\sum_i m_{\alpha i}},
713 > \end{equation}
714 > where $v_{\alpha i}$ is the velocity of atom $i$ in the z direction.
715 > Lastly, all of the accumulated z constrained forces must be
716 > subtracted from the system to keep the system center of mass from
717 > drifting.
718 > \begin{equation}
719 > F_{\beta i} = F_{\beta i} - \frac{m_{\beta i} \sum_{\alpha}
720 > G_{\alpha}}
721 >    {\sum_{\beta}\sum_i m_{\beta i}},
722 > \end{equation}
723 > where $\beta$ are all of the unconstrained molecules in the system.
724 > Similarly, the velocities of the unconstrained molecules must also
725 > be scaled.
726 > \begin{equation}
727 > v_{\beta i} = v_{\beta i} + \sum_{\alpha}
728 >    \frac{\sum_i m_{\alpha i} v_{\alpha i}}{\sum_i m_{\alpha i}}.
729 > \end{equation}
730  
731 < \subsection{\label{methodSection:pressureControl}Pressure Control}
732 <
733 < \section{\label{methodSection:hydrodynamics}Hydrodynamics}
734 <
735 < %\section{\label{methodSection:coarseGrained}Coarse-Grained Modeling}
736 <
737 < %\section{\label{methodSection:moleculeScale}Molecular-Scale Modeling}
731 > At the very beginning of the simulation, the molecules may not be at
732 > their constrained positions. To move a z-constrained molecule to its
733 > specified position, a simple harmonic potential is used
734 > \begin{equation}
735 > U(t)=\frac{1}{2}k_{\text{Harmonic}}(z(t)-z_{\text{cons}})^{2},%
736 > \end{equation}
737 > where $k_{\text{Harmonic}}$ is the harmonic force constant, $z(t)$
738 > is the current $z$ coordinate of the center of mass of the
739 > constrained molecule, and $z_{\text{cons}}$ is the constrained
740 > position. The harmonic force operating on the z-constrained molecule
741 > at time $t$ can be calculated by
742 > \begin{equation}
743 > F_{z_{\text{Harmonic}}}(t)=-\frac{\partial U(t)}{\partial z(t)}=
744 >    -k_{\text{Harmonic}}(z(t)-z_{\text{cons}}).
745 > \end{equation}

Diff Legend

Removed lines
+ Added lines
< Changed lines
> Changed lines