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# 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 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 284 | Line 285 | Helmholtz free energy,\cite{melchionna93}
285  
286   The Nos\'e-Hoover algorithm is known to conserve a Hamiltonian for
287   the extended system that is, to within a constant, identical to the
288 < Helmholtz free energy,\cite{melchionna93}
288 > Helmholtz free energy,\cite{Melchionna1993}
289   \begin{equation}
290   H_{\mathrm{NVT}} = V + K + f k_B T_{\mathrm{target}} \left(
291   \frac{\tau_{T}^2 \chi^2(t)}{2} + \int_{0}^{t} \chi(t^\prime)
# Line 295 | Line 296 | Bond constraints are applied at the end of both the {\
296   last column of the {\tt .stat} file to allow checks on the quality
297   of the integration.
298  
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}.
301
299   \subsection{\label{methodSection:NPTi}Constant-pressure integration with
300   isotropic box deformations (NPTi)}
301  
302   To carry out isobaric-isothermal ensemble calculations {\sc oopse}
303   implements the Melchionna modifications to the
304 < Nos\'e-Hoover-Andersen equations of motion,\cite{melchionna93}
304 > Nos\'e-Hoover-Andersen equations of motion,\cite{Melchionna1993}
305  
306   \begin{eqnarray}
307   \dot{{\bf r}} & = & {\bf v} + \eta \left( {\bf r} - {\bf R}_0 \right), \\
# Line 359 | Line 356 | relaxation of the pressure to the target value.  To se
356   \end{equation}
357  
358   In eq.(\ref{eq:melchionna1}), $\tau_B$ is the time constant for
359 < 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
359 > relaxation of the pressure to the target value. Like in the NVT
360   integrator, the integration of the equations of motion is carried
361   out in a velocity-Verlet style 2 part algorithm:
362  
# Line 476 | Line 469 | Bond constraints are applied at the end of both the {\
469   P_{\mathrm{target}} \mathcal{V}(t).
470   \end{equation}
471  
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
472   \subsection{\label{methodSection:NPTf}Constant-pressure integration with a
473   flexible box (NPTf)}
474  
# Line 611 | Line 600 | assume non-orthorhombic geometries.
600  
601   \subsection{\label{methodSection:otherSpecialEnsembles}Other Special Ensembles}
602  
603 < \subsubsection{\label{methodSection:NPAT}NPAT Ensemble}
603 > \subsubsection{\label{methodSection:NPAT}\textbf{NPAT Ensemble}}
604  
605   A comprehensive understanding of structure¨Cfunction relations of
606   biological membrane system ultimately relies on structure and
# Line 634 | Line 623 | described for the NPTi integrator.
623   Note that the iterative schemes for NPAT are identical to those
624   described for the NPTi integrator.
625  
626 < \subsubsection{\label{methodSection:NPrT}NP$\gamma$T Ensemble}
626 > \subsubsection{\label{methodSection:NPrT}\textbf{NP$\gamma$T Ensemble}}
627  
628   Theoretically, the surface tension $\gamma$ of a stress free
629   membrane system should be zero since its surface free energy $G$ is
# Line 672 | Line 661 | $\gamma$ is set to zero.
661   integrator is a special case of $NP\gamma T$ if the surface tension
662   $\gamma$ is set to zero.
663  
664 < %\section{\label{methodSection:constraintMethod}Constraint Method}
664 > \section{\label{methodSection:zcons}Z-Constraint Method}
665  
666 < %\subsection{\label{methodSection:bondConstraint}Bond Constraint for Rigid Body}
667 <
668 < %\subsection{\label{methodSection:zcons}Z-constraint Method}
669 <
670 < \section{\label{methodSection:langevin}Integrators for Langevin Dynamics of Rigid Bodies}
671 <
672 < \subsection{\label{methodSection:temperature}Temperature Control}
673 <
674 < \subsection{\label{methodSection:pressureControl}Pressure Control}
675 <
676 < \section{\label{methodSection:hydrodynamics}Hydrodynamics}
677 <
689 < %\section{\label{methodSection:coarseGrained}Coarse-Grained Modeling}
666 > Based on the fluctuation-dissipation theorem, a force
667 > auto-correlation method was developed by Roux and Karplus to
668 > investigate the dynamics of ions inside ion channels\cite{Roux1991}.
669 > The time-dependent friction coefficient can be calculated from the
670 > deviation of the instantaneous force from its mean force.
671 > \begin{equation}
672 > \xi(z,t)=\langle\delta F(z,t)\delta F(z,0)\rangle/k_{B}T,
673 > \end{equation}
674 > where%
675 > \begin{equation}
676 > \delta F(z,t)=F(z,t)-\langle F(z,t)\rangle.
677 > \end{equation}
678  
679 < %\section{\label{methodSection:moleculeScale}Molecular-Scale Modeling}
679 > If the time-dependent friction decays rapidly, the static friction
680 > coefficient can be approximated by
681 > \begin{equation}
682 > \xi_{\text{static}}(z)=\int_{0}^{\infty}\langle\delta F(z,t)\delta
683 > F(z,0)\rangle dt.
684 > \end{equation}
685 > Allowing diffusion constant to then be calculated through the
686 > Einstein relation:\cite{Marrink1994}
687 > \begin{equation}
688 > D(z)=\frac{k_{B}T}{\xi_{\text{static}}(z)}=\frac{(k_{B}T)^{2}}{\int_{0}^{\infty
689 > }\langle\delta F(z,t)\delta F(z,0)\rangle dt}.%
690 > \end{equation}
691 >
692 > The Z-Constraint method, which fixes the z coordinates of the
693 > molecules with respect to the center of the mass of the system, has
694 > been a method suggested to obtain the forces required for the force
695 > auto-correlation calculation.\cite{Marrink1994} However, simply
696 > resetting the coordinate will move the center of the mass of the
697 > whole system. To avoid this problem, we reset the forces of
698 > z-constrained molecules as well as subtract the total constraint
699 > forces from the rest of the system after the force calculation at
700 > each time step instead of resetting the coordinate.
701 >
702 > After the force calculation, define $G_\alpha$ as
703 > \begin{equation}
704 > G_{\alpha} = \sum_i F_{\alpha i}, \label{oopseEq:zc1}
705 > \end{equation}
706 > where $F_{\alpha i}$ is the force in the z direction of atom $i$ in
707 > z-constrained molecule $\alpha$. The forces of the z constrained
708 > molecule are then set to:
709 > \begin{equation}
710 > F_{\alpha i} = F_{\alpha i} -
711 >    \frac{m_{\alpha i} G_{\alpha}}{\sum_i m_{\alpha i}}.
712 > \end{equation}
713 > Here, $m_{\alpha i}$ is the mass of atom $i$ in the z-constrained
714 > molecule. Having rescaled the forces, the velocities must also be
715 > rescaled to subtract out any center of mass velocity in the z
716 > direction.
717 > \begin{equation}
718 > v_{\alpha i} = v_{\alpha i} -
719 >    \frac{\sum_i m_{\alpha i} v_{\alpha i}}{\sum_i m_{\alpha i}},
720 > \end{equation}
721 > where $v_{\alpha i}$ is the velocity of atom $i$ in the z direction.
722 > Lastly, all of the accumulated z constrained forces must be
723 > subtracted from the system to keep the system center of mass from
724 > drifting.
725 > \begin{equation}
726 > F_{\beta i} = F_{\beta i} - \frac{m_{\beta i} \sum_{\alpha}
727 > G_{\alpha}}
728 >    {\sum_{\beta}\sum_i m_{\beta i}},
729 > \end{equation}
730 > where $\beta$ are all of the unconstrained molecules in the system.
731 > Similarly, the velocities of the unconstrained molecules must also
732 > be scaled.
733 > \begin{equation}
734 > v_{\beta i} = v_{\beta i} + \sum_{\alpha}
735 >    \frac{\sum_i m_{\alpha i} v_{\alpha i}}{\sum_i m_{\alpha i}}.
736 > \end{equation}
737 >
738 > At the very beginning of the simulation, the molecules may not be at
739 > their constrained positions. To move a z-constrained molecule to its
740 > specified position, a simple harmonic potential is used
741 > \begin{equation}
742 > U(t)=\frac{1}{2}k_{\text{Harmonic}}(z(t)-z_{\text{cons}})^{2},%
743 > \end{equation}
744 > where $k_{\text{Harmonic}}$ is the harmonic force constant, $z(t)$
745 > is the current $z$ coordinate of the center of mass of the
746 > constrained molecule, and $z_{\text{cons}}$ is the constrained
747 > position. The harmonic force operating on the z-constrained molecule
748 > at time $t$ can be calculated by
749 > \begin{equation}
750 > F_{z_{\text{Harmonic}}}(t)=-\frac{\partial U(t)}{\partial z(t)}=
751 >    -k_{\text{Harmonic}}(z(t)-z_{\text{cons}}).
752 > \end{equation}

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