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2  
3   \section{\label{methodSection:rigidBodyIntegrators}Integrators for Rigid Body Motion in Molecular Dynamics}
4  
5 < \section{\label{methodSection:conservedQuantities}Integrators to Conserve Properties in Special Ensembles}
5 > In order to mimic the experiments, which are usually performed under
6 > constant temperature and/or pressure, extended Hamiltonian system
7 > methods have been developed to generate statistical ensembles, such
8 > as canonical ensemble and isobaric-isothermal ensemble \textit{etc}.
9 > In addition to the standard ensemble, specific ensembles have been
10 > developed to account for the anisotropy between the lateral and
11 > normal directions of membranes. The $NPAT$ ensemble, in which the
12 > normal pressure and the lateral surface area of the membrane are
13 > kept constant, and the $NP\gamma T$ ensemble, in which the normal
14 > pressure and the lateral surface tension are kept constant were
15 > proposed to address this issue.
16  
17 < \section{\label{methodSection:hydrodynamics}Hydrodynamics}
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 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
32 > proposed by Dullweber, Leimkuhler and McLachlan (DLM) also preserved
33 > the same structural properties of the Hamiltonian flow. In this
34 > section, the integration scheme of DLM method will be reviewed and
35 > extended to other ensembles.
36  
37 < \section{\label{methodSection:langevin}Integrators for Langevin Dynamics of Rigid Bodies}
37 > \subsection{\label{methodSection:DLM}Integrating the Equations of Motion: the
38 > DLM method}
39  
40 < \section{\label{methodSection:coarseGrained}Coarse-Grained Modeling}
40 > The DLM method uses a Trotter factorization of the orientational
41 > propagator.  This has three effects:
42 > \begin{enumerate}
43 > \item the integrator is area-preserving in phase space (i.e. it is
44 > {\it symplectic}),
45 > \item the integrator is time-{\it reversible}, making it suitable for Hybrid
46 > Monte Carlo applications, and
47 > \item the error for a single time step is of order $\mathcal{O}\left(h^4\right)$
48 > for timesteps of length $h$.
49 > \end{enumerate}
50  
51 < \section{\label{methodSection:moleculeScale}Molecular-Scale Modeling}
51 > The integration of the equations of motion is carried out in a
52 > velocity-Verlet style 2-part algorithm, where $h= \delta t$:
53 >
54 > {\tt moveA:}
55 > \begin{align*}
56 > {\bf v}\left(t + h / 2\right)  &\leftarrow  {\bf v}(t)
57 >    + \frac{h}{2} \left( {\bf f}(t) / m \right), \\
58 > %
59 > {\bf r}(t + h) &\leftarrow {\bf r}(t)
60 >    + h  {\bf v}\left(t + h / 2 \right), \\
61 > %
62 > {\bf j}\left(t + h / 2 \right)  &\leftarrow {\bf j}(t)
63 >    + \frac{h}{2} {\bf \tau}^b(t), \\
64 > %
65 > \mathsf{A}(t + h) &\leftarrow \mathrm{rotate}\left( h {\bf j}
66 >    (t + h / 2) \cdot \overleftrightarrow{\mathsf{I}}^{-1} \right).
67 > \end{align*}
68 >
69 > In this context, the $\mathrm{rotate}$ function is the reversible
70 > product of the three body-fixed rotations,
71 > \begin{equation}
72 > \mathrm{rotate}({\bf a}) = \mathsf{G}_x(a_x / 2) \cdot
73 > \mathsf{G}_y(a_y / 2) \cdot \mathsf{G}_z(a_z) \cdot \mathsf{G}_y(a_y
74 > / 2) \cdot \mathsf{G}_x(a_x /2),
75 > \end{equation}
76 > where each rotational propagator, $\mathsf{G}_\alpha(\theta)$,
77 > rotates both the rotation matrix ($\mathsf{A}$) and the body-fixed
78 > angular momentum (${\bf j}$) by an angle $\theta$ around body-fixed
79 > axis $\alpha$,
80 > \begin{equation}
81 > \mathsf{G}_\alpha( \theta ) = \left\{
82 > \begin{array}{lcl}
83 > \mathsf{A}(t) & \leftarrow & \mathsf{A}(0) \cdot \mathsf{R}_\alpha(\theta)^T, \\
84 > {\bf j}(t) & \leftarrow & \mathsf{R}_\alpha(\theta) \cdot {\bf
85 > j}(0).
86 > \end{array}
87 > \right.
88 > \end{equation}
89 > $\mathsf{R}_\alpha$ is a quadratic approximation to the single-axis
90 > rotation matrix.  For example, in the small-angle limit, the
91 > rotation matrix around the body-fixed x-axis can be approximated as
92 > \begin{equation}
93 > \mathsf{R}_x(\theta) \approx \left(
94 > \begin{array}{ccc}
95 > 1 & 0 & 0 \\
96 > 0 & \frac{1-\theta^2 / 4}{1 + \theta^2 / 4}  & -\frac{\theta}{1+
97 > \theta^2 / 4} \\
98 > 0 & \frac{\theta}{1+ \theta^2 / 4} & \frac{1-\theta^2 / 4}{1 +
99 > \theta^2 / 4}
100 > \end{array}
101 > \right).
102 > \end{equation}
103 > All other rotations follow in a straightforward manner.
104 >
105 > After the first part of the propagation, the forces and body-fixed
106 > torques are calculated at the new positions and orientations
107 >
108 > {\tt doForces:}
109 > \begin{align*}
110 > {\bf f}(t + h) &\leftarrow
111 >    - \left(\frac{\partial V}{\partial {\bf r}}\right)_{{\bf r}(t + h)}, \\
112 > %
113 > {\bf \tau}^{s}(t + h) &\leftarrow {\bf u}(t + h)
114 >    \times \frac{\partial V}{\partial {\bf u}}, \\
115 > %
116 > {\bf \tau}^{b}(t + h) &\leftarrow \mathsf{A}(t + h)
117 >    \cdot {\bf \tau}^s(t + h).
118 > \end{align*}
119 >
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.
124 >
125 > {\tt moveB:}
126 > \begin{align*}
127 > {\bf v}\left(t + h \right)  &\leftarrow  {\bf v}\left(t + h / 2
128 > \right)
129 >    + \frac{h}{2} \left( {\bf f}(t + h) / m \right), \\
130 > %
131 > {\bf j}\left(t + h \right)  &\leftarrow {\bf j}\left(t + h / 2
132 > \right)
133 >    + \frac{h}{2} {\bf \tau}^b(t + h) .
134 > \end{align*}
135 >
136 > The matrix rotations used in the DLM method end up being more costly
137 > computationally than the simpler arithmetic quaternion propagation.
138 > With the same time step, a 1000-molecule water simulation shows an
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{methodFig:timestep}.
143 >
144 > \begin{figure}
145 > \centering
146 > \includegraphics[width=\linewidth]{timeStep.eps}
147 > \caption[Energy conservation for quaternion versus DLM
148 > dynamics]{Energy conservation using quaternion based integration
149 > versus the method proposed by Dullweber \emph{et al.} with
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.}
154 > \label{methodFig:timestep}
155 > \end{figure}
156 >
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{Hoover1985}
173 > \begin{eqnarray}
174 > \dot{{\bf r}} & = & {\bf v}, \\
175 > \dot{{\bf v}} & = & \frac{{\bf f}}{m} - \chi {\bf v} ,\\
176 > \dot{\mathsf{A}} & = & \mathsf{A} \cdot
177 > \mbox{ skew}\left(\overleftrightarrow{\mathsf{I}}^{-1} \cdot {\bf j}\right), \\
178 > \dot{{\bf j}} & = & {\bf j} \times \left(
179 > \overleftrightarrow{\mathsf{I}}^{-1} \cdot {\bf j} \right) - \mbox{
180 > rot}\left(\mathsf{A}^{T} \cdot \frac{\partial V}{\partial
181 > \mathsf{A}} \right) - \chi {\bf j}. \label{eq:nosehoovereom}
182 > \end{eqnarray}
183 >
184 > $\chi$ is an ``extra'' variable included in the extended system, and
185 > it is propagated using the first order equation of motion
186 > \begin{equation}
187 > \dot{\chi} = \frac{1}{\tau_{T}^2} \left(
188 > \frac{T}{T_{\mathrm{target}}} - 1 \right). \label{eq:nosehooverext}
189 > \end{equation}
190 >
191 > The instantaneous temperature $T$ is proportional to the total
192 > kinetic energy (both translational and orientational) and is given
193 > by
194 > \begin{equation}
195 > T = \frac{2 K}{f k_B}
196 > \end{equation}
197 > Here, $f$ is the total number of degrees of freedom in the system,
198 > \begin{equation}
199 > f = 3 N + 3 N_{\mathrm{orient}} - N_{\mathrm{constraints}},
200 > \end{equation}
201 > and $K$ is the total kinetic energy,
202 > \begin{equation}
203 > K = \sum_{i=1}^{N} \frac{1}{2} m_i {\bf v}_i^T \cdot {\bf v}_i +
204 > \sum_{i=1}^{N_{\mathrm{orient}}}  \frac{1}{2} {\bf j}_i^T \cdot
205 > \overleftrightarrow{\mathsf{I}}_i^{-1} \cdot {\bf j}_i.
206 > \end{equation}
207 >
208 > In eq.(\ref{eq:nosehooverext}), $\tau_T$ is the time constant for
209 > relaxation of the temperature to the target value.  To set values
210 > for $\tau_T$ or $T_{\mathrm{target}}$ in a simulation, one would use
211 > the {\tt tauThermostat} and {\tt targetTemperature} keywords in the
212 > {\tt .bass} file.  The units for {\tt tauThermostat} are fs, and the
213 > units for the {\tt targetTemperature} are degrees K.   The
214 > integration of the equations of motion is carried out in a
215 > velocity-Verlet style 2 part algorithm:
216 >
217 > {\tt moveA:}
218 > \begin{align*}
219 > T(t) &\leftarrow \left\{{\bf v}(t)\right\}, \left\{{\bf j}(t)\right\} ,\\
220 > %
221 > {\bf v}\left(t + h / 2\right)  &\leftarrow {\bf v}(t)
222 >    + \frac{h}{2} \left( \frac{{\bf f}(t)}{m} - {\bf v}(t)
223 >    \chi(t)\right), \\
224 > %
225 > {\bf r}(t + h) &\leftarrow {\bf r}(t)
226 >    + h {\bf v}\left(t + h / 2 \right) ,\\
227 > %
228 > {\bf j}\left(t + h / 2 \right)  &\leftarrow {\bf j}(t)
229 >    + \frac{h}{2} \left( {\bf \tau}^b(t) - {\bf j}(t)
230 >    \chi(t) \right) ,\\
231 > %
232 > \mathsf{A}(t + h) &\leftarrow \mathrm{rotate}
233 >    \left(h * {\bf j}(t + h / 2)
234 >    \overleftrightarrow{\mathsf{I}}^{-1} \right) ,\\
235 > %
236 > \chi\left(t + h / 2 \right) &\leftarrow \chi(t)
237 >    + \frac{h}{2 \tau_T^2} \left( \frac{T(t)}
238 >    {T_{\mathrm{target}}} - 1 \right) .
239 > \end{align*}
240 >
241 > Here $\mathrm{rotate}(h * {\bf j}
242 > \overleftrightarrow{\mathsf{I}}^{-1})$ is the same symplectic
243 > Trotter factorization of the three rotation operations that was
244 > discussed in the section on the DLM integrator.  Note that this
245 > operation modifies both the rotation matrix $\mathsf{A}$ and the
246 > angular momentum ${\bf j}$.  {\tt moveA} propagates velocities by a
247 > half time step, and positional degrees of freedom by a full time
248 > step.  The new positions (and orientations) are then used to
249 > calculate a new set of forces and torques in exactly the same way
250 > they are calculated in the {\tt doForces} portion of the DLM
251 > integrator.
252 >
253 > Once the forces and torques have been obtained at the new time step,
254 > the temperature, velocities, and the extended system variable can be
255 > advanced to the same time value.
256 >
257 > {\tt moveB:}
258 > \begin{align*}
259 > T(t + h) &\leftarrow \left\{{\bf v}(t + h)\right\},
260 >    \left\{{\bf j}(t + h)\right\}, \\
261 > %
262 > \chi\left(t + h \right) &\leftarrow \chi\left(t + h /
263 >    2 \right) + \frac{h}{2 \tau_T^2} \left( \frac{T(t+h)}
264 >    {T_{\mathrm{target}}} - 1 \right), \\
265 > %
266 > {\bf v}\left(t + h \right)  &\leftarrow {\bf v}\left(t
267 >    + h / 2 \right) + \frac{h}{2} \left(
268 >    \frac{{\bf f}(t + h)}{m} - {\bf v}(t + h)
269 >    \chi(t h)\right) ,\\
270 > %
271 > {\bf j}\left(t + h \right) &\leftarrow {\bf j}\left(t
272 >    + h / 2 \right) + \frac{h}{2}
273 >    \left( {\bf \tau}^b(t + h) - {\bf j}(t + h)
274 >    \chi(t + h) \right) .
275 > \end{align*}
276 >
277 > Since ${\bf v}(t + h)$ and ${\bf j}(t + h)$ are required to
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.
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{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)
289 > dt^\prime \right).
290 > \end{equation}
291 > Poor choices of $h$ or $\tau_T$ can result in non-conservation of
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.
295 >
296 > \subsection{\label{methodSection:NPTi}Constant-pressure integration with
297 > isotropic box deformations (NPTi)}
298 >
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), \\
305 > \dot{{\bf v}} & = & \frac{{\bf f}}{m} - (\eta + \chi) {\bf v}, \\
306 > \dot{\mathsf{A}} & = & \mathsf{A} \cdot
307 > \mbox{ skew}\left(\overleftrightarrow{I}^{-1} \cdot {\bf j}\right),\\
308 > \dot{{\bf j}} & = & {\bf j} \times \left(
309 > \overleftrightarrow{I}^{-1} \cdot {\bf j} \right) - \mbox{
310 > rot}\left(\mathsf{A}^{T} \cdot \frac{\partial
311 > V}{\partial \mathsf{A}} \right) - \chi {\bf j}, \\
312 > \dot{\chi} & = & \frac{1}{\tau_{T}^2} \left(
313 > \frac{T}{T_{\mathrm{target}}} - 1 \right) ,\\
314 > \dot{\eta} & = & \frac{1}{\tau_{B}^2 f k_B T_{\mathrm{target}}} V
315 > \left( P -
316 > P_{\mathrm{target}} \right), \\
317 > \dot{\mathcal{V}} & = & 3 \mathcal{V} \eta . \label{eq:melchionna1}
318 > \end{eqnarray}
319 >
320 > $\chi$ and $\eta$ are the ``extra'' degrees of freedom in the
321 > extended system.  $\chi$ is a thermostat, and it has the same
322 > function as it does in the Nos\'e-Hoover NVT integrator.  $\eta$ is
323 > a barostat which controls changes to the volume of the simulation
324 > box.  ${\bf R}_0$ is the location of the center of mass for the
325 > entire system, and $\mathcal{V}$ is the volume of the simulation
326 > box.  At any time, the volume can be calculated from the determinant
327 > of the matrix which describes the box shape:
328 > \begin{equation}
329 > \mathcal{V} = \det(\mathsf{H}).
330 > \end{equation}
331 >
332 > The NPTi integrator requires an instantaneous pressure. This
333 > quantity is calculated via the pressure tensor,
334 > \begin{equation}
335 > \overleftrightarrow{\mathsf{P}}(t) = \frac{1}{\mathcal{V}(t)} \left(
336 > \sum_{i=1}^{N} m_i {\bf v}_i(t) \otimes {\bf v}_i(t) \right) +
337 > \overleftrightarrow{\mathsf{W}}(t).
338 > \end{equation}
339 > The kinetic contribution to the pressure tensor utilizes the {\it
340 > outer} product of the velocities denoted by the $\otimes$ symbol.
341 > The stress tensor is calculated from another outer product of the
342 > inter-atomic separation vectors (${\bf r}_{ij} = {\bf r}_j - {\bf
343 > r}_i$) with the forces between the same two atoms,
344 > \begin{equation}
345 > \overleftrightarrow{\mathsf{W}}(t) = \sum_{i} \sum_{j>i} {\bf
346 > r}_{ij}(t) \otimes {\bf f}_{ij}(t).
347 > \end{equation}
348 > The instantaneous pressure is then simply obtained from the trace of
349 > the Pressure tensor,
350 > \begin{equation}
351 > P(t) = \frac{1}{3} \mathrm{Tr} \left(
352 > \overleftrightarrow{\mathsf{P}}(t). \right)
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. 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 >
360 > {\tt moveA:}
361 > \begin{align*}
362 > T(t) &\leftarrow \left\{{\bf v}(t)\right\}, \left\{{\bf j}(t)\right\} ,\\
363 > %
364 > P(t) &\leftarrow \left\{{\bf r}(t)\right\}, \left\{{\bf v}(t)\right\} ,\\
365 > %
366 > {\bf v}\left(t + h / 2\right)  &\leftarrow {\bf v}(t)
367 >    + \frac{h}{2} \left( \frac{{\bf f}(t)}{m} - {\bf v}(t)
368 >    \left(\chi(t) + \eta(t) \right) \right), \\
369 > %
370 > {\bf j}\left(t + h / 2 \right)  &\leftarrow {\bf j}(t)
371 >    + \frac{h}{2} \left( {\bf \tau}^b(t) - {\bf j}(t)
372 >    \chi(t) \right), \\
373 > %
374 > \mathsf{A}(t + h) &\leftarrow \mathrm{rotate}\left(h *
375 >    {\bf j}(t + h / 2) \overleftrightarrow{\mathsf{I}}^{-1}
376 >    \right) ,\\
377 > %
378 > \chi\left(t + h / 2 \right) &\leftarrow \chi(t) +
379 >    \frac{h}{2 \tau_T^2} \left( \frac{T(t)}{T_{\mathrm{target}}} - 1
380 >    \right) ,\\
381 > %
382 > \eta(t + h / 2) &\leftarrow \eta(t) + \frac{h
383 >    \mathcal{V}(t)}{2 N k_B T(t) \tau_B^2} \left( P(t)
384 >    - P_{\mathrm{target}} \right), \\
385 > %
386 > {\bf r}(t + h) &\leftarrow {\bf r}(t) + h
387 >    \left\{ {\bf v}\left(t + h / 2 \right)
388 >    + \eta(t + h / 2)\left[ {\bf r}(t + h)
389 >    - {\bf R}_0 \right] \right\} ,\\
390 > %
391 > \mathsf{H}(t + h) &\leftarrow e^{-h \eta(t + h / 2)}
392 >    \mathsf{H}(t).
393 > \end{align*}
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. 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)
405 > \end{equation}
406 >
407 > The {\tt doForces} step for the NPTi integrator is exactly the same
408 > as in both the DLM and NVT integrators.  Once the forces and torques
409 > have been obtained at the new time step, the velocities can be
410 > advanced to the same time value.
411 >
412 > {\tt moveB:}
413 > \begin{align*}
414 > T(t + h) &\leftarrow \left\{{\bf v}(t + h)\right\},
415 >    \left\{{\bf j}(t + h)\right\} ,\\
416 > %
417 > P(t + h) &\leftarrow  \left\{{\bf r}(t + h)\right\},
418 >    \left\{{\bf v}(t + h)\right\}, \\
419 > %
420 > \chi\left(t + h \right) &\leftarrow \chi\left(t + h /
421 >    2 \right) + \frac{h}{2 \tau_T^2} \left( \frac{T(t+h)}
422 >    {T_{\mathrm{target}}} - 1 \right), \\
423 > %
424 > \eta(t + h) &\leftarrow \eta(t + h / 2) +
425 >    \frac{h \mathcal{V}(t + h)}{2 N k_B T(t + h)
426 >    \tau_B^2} \left( P(t + h) - P_{\mathrm{target}} \right), \\
427 > %
428 > {\bf v}\left(t + h \right)  &\leftarrow {\bf v}\left(t
429 >    + h / 2 \right) + \frac{h}{2} \left(
430 >    \frac{{\bf f}(t + h)}{m} - {\bf v}(t + h)
431 >    (\chi(t + h) + \eta(t + h)) \right) ,\\
432 > %
433 > {\bf j}\left(t + h \right)  &\leftarrow {\bf j}\left(t
434 >    + h / 2 \right) + \frac{h}{2} \left( {\bf
435 >    \tau}^b(t + h) - {\bf j}(t + h)
436 >    \chi(t + h) \right) .
437 > \end{align*}
438 >
439 > Once again, since ${\bf v}(t + h)$ and ${\bf j}(t + h)$ are required
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.
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,
447 > to within a constant, identical to the Gibbs free energy,
448 > \begin{equation}
449 > H_{\mathrm{NPTi}} = V + K + f k_B T_{\mathrm{target}} \left(
450 > \frac{\tau_{T}^2 \chi^2(t)}{2} + \int_{0}^{t} \chi(t^\prime)
451 > dt^\prime \right) + P_{\mathrm{target}} \mathcal{V}(t).
452 > \end{equation}
453 > Poor choices of $\delta t$, $\tau_T$, or $\tau_B$ can result in
454 > non-conservation of $H_{\mathrm{NPTi}}$, so the conserved quantity
455 > is maintained in the last column of the {\tt .stat} file to allow
456 > checks on the quality of the integration.  It is also known that
457 > this algorithm samples the equilibrium distribution for the enthalpy
458 > (including contributions for the thermostat and barostat),
459 > \begin{equation}
460 > H_{\mathrm{NPTi}} = V + K + \frac{f k_B T_{\mathrm{target}}}{2}
461 > \left( \chi^2 \tau_T^2 + \eta^2 \tau_B^2 \right) +
462 > P_{\mathrm{target}} \mathcal{V}(t).
463 > \end{equation}
464 >
465 > \subsection{\label{methodSection:NPTf}Constant-pressure integration with a
466 > flexible box (NPTf)}
467 >
468 > There is a relatively simple generalization of the
469 > Nos\'e-Hoover-Andersen method to include changes in the simulation
470 > box {\it shape} as well as in the volume of the box.  This method
471 > utilizes the full $3 \times 3$ pressure tensor and introduces a
472 > tensor of extended variables ($\overleftrightarrow{\eta}$) to
473 > control changes to the box shape.  The equations of motion for this
474 > method are
475 > \begin{eqnarray}
476 > \dot{{\bf r}} & = & {\bf v} + \overleftrightarrow{\eta} \cdot \left( {\bf r} - {\bf R}_0 \right), \\
477 > \dot{{\bf v}} & = & \frac{{\bf f}}{m} - (\overleftrightarrow{\eta} +
478 > \chi \cdot \mathsf{1}) {\bf v}, \\
479 > \dot{\mathsf{A}} & = & \mathsf{A} \cdot
480 > \mbox{ skew}\left(\overleftrightarrow{I}^{-1} \cdot {\bf j}\right) ,\\
481 > \dot{{\bf j}} & = & {\bf j} \times \left(
482 > \overleftrightarrow{I}^{-1} \cdot {\bf j} \right) - \mbox{
483 > rot}\left(\mathsf{A}^{T} \cdot \frac{\partial
484 > V}{\partial \mathsf{A}} \right) - \chi {\bf j} ,\\
485 > \dot{\chi} & = & \frac{1}{\tau_{T}^2} \left(
486 > \frac{T}{T_{\mathrm{target}}} - 1 \right) ,\\
487 > \dot{\overleftrightarrow{\eta}} & = & \frac{1}{\tau_{B}^2 f k_B
488 > T_{\mathrm{target}}} V \left( \overleftrightarrow{\mathsf{P}} - P_{\mathrm{target}}\mathsf{1} \right) ,\\
489 > \dot{\mathsf{H}} & = &  \overleftrightarrow{\eta} \cdot \mathsf{H} .
490 > \label{eq:melchionna2}
491 > \end{eqnarray}
492 >
493 > Here, $\mathsf{1}$ is the unit matrix and
494 > $\overleftrightarrow{\mathsf{P}}$ is the pressure tensor.  Again,
495 > the volume, $\mathcal{V} = \det \mathsf{H}$.
496 >
497 > The propagation of the equations of motion is nearly identical to
498 > the NPTi integration:
499 >
500 > {\tt moveA:}
501 > \begin{align*}
502 > T(t) &\leftarrow \left\{{\bf v}(t)\right\}, \left\{{\bf j}(t)\right\} ,\\
503 > %
504 > \overleftrightarrow{\mathsf{P}}(t) &\leftarrow \left\{{\bf
505 > r}(t)\right\},
506 >    \left\{{\bf v}(t)\right\} ,\\
507 > %
508 > {\bf v}\left(t + h / 2\right)  &\leftarrow {\bf v}(t)
509 >    + \frac{h}{2} \left( \frac{{\bf f}(t)}{m} -
510 >    \left(\chi(t)\mathsf{1} + \overleftrightarrow{\eta}(t) \right) \cdot
511 >    {\bf v}(t) \right), \\
512 > %
513 > {\bf j}\left(t + h / 2 \right)  &\leftarrow {\bf j}(t)
514 >    + \frac{h}{2} \left( {\bf \tau}^b(t) - {\bf j}(t)
515 >    \chi(t) \right), \\
516 > %
517 > \mathsf{A}(t + h) &\leftarrow \mathrm{rotate}\left(h *
518 >    {\bf j}(t + h / 2) \overleftrightarrow{\mathsf{I}}^{-1}
519 >    \right), \\
520 > %
521 > \chi\left(t + h / 2 \right) &\leftarrow \chi(t) +
522 >    \frac{h}{2 \tau_T^2} \left( \frac{T(t)}{T_{\mathrm{target}}}
523 >    - 1 \right), \\
524 > %
525 > \overleftrightarrow{\eta}(t + h / 2) &\leftarrow
526 >    \overleftrightarrow{\eta}(t) + \frac{h \mathcal{V}(t)}{2 N k_B
527 >    T(t) \tau_B^2} \left( \overleftrightarrow{\mathsf{P}}(t)
528 >    - P_{\mathrm{target}}\mathsf{1} \right), \\
529 > %
530 > {\bf r}(t + h) &\leftarrow {\bf r}(t) + h \left\{ {\bf v}
531 >    \left(t + h / 2 \right) + \overleftrightarrow{\eta}(t +
532 >    h / 2) \cdot \left[ {\bf r}(t + h)
533 >    - {\bf R}_0 \right] \right\}, \\
534 > %
535 > \mathsf{H}(t + h) &\leftarrow \mathsf{H}(t) \cdot e^{-h
536 >    \overleftrightarrow{\eta}(t + h / 2)} .
537 > \end{align*}
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:
543 >
544 > {\tt moveB:}
545 > \begin{align*}
546 > T(t + h) &\leftarrow \left\{{\bf v}(t + h)\right\},
547 >    \left\{{\bf j}(t + h)\right\}, \\
548 > %
549 > \overleftrightarrow{\mathsf{P}}(t + h) &\leftarrow \left\{{\bf r}
550 >    (t + h)\right\}, \left\{{\bf v}(t
551 >    + h)\right\}, \left\{{\bf f}(t + h)\right\} ,\\
552 > %
553 > \chi\left(t + h \right) &\leftarrow \chi\left(t + h /
554 >    2 \right) + \frac{h}{2 \tau_T^2} \left( \frac{T(t+
555 >    h)}{T_{\mathrm{target}}} - 1 \right), \\
556 > %
557 > \overleftrightarrow{\eta}(t + h) &\leftarrow
558 >    \overleftrightarrow{\eta}(t + h / 2) +
559 >    \frac{h \mathcal{V}(t + h)}{2 N k_B T(t + h)
560 >    \tau_B^2} \left( \overleftrightarrow{P}(t + h)
561 >    - P_{\mathrm{target}}\mathsf{1} \right) ,\\
562 > %
563 > {\bf v}\left(t + h \right)  &\leftarrow {\bf v}\left(t
564 >    + h / 2 \right) + \frac{h}{2} \left(
565 >    \frac{{\bf f}(t + h)}{m} -
566 >    (\chi(t + h)\mathsf{1} + \overleftrightarrow{\eta}(t
567 >    + h)) \right) \cdot {\bf v}(t + h), \\
568 > %
569 > {\bf j}\left(t + h \right)  &\leftarrow {\bf j}\left(t
570 >    + h / 2 \right) + \frac{h}{2} \left( {\bf \tau}^b(t
571 >    + h) - {\bf j}(t + h) \chi(t + h) \right) .
572 > \end{align*}
573 >
574 > The iterative schemes for both {\tt moveA} and {\tt moveB} are
575 > identical to those described for the NPTi integrator.
576 >
577 > The NPTf integrator is known to conserve the following Hamiltonian:
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) \\
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{eqnarray*}
586 >
587 > This integrator must be used with care, particularly in liquid
588 > simulations.  Liquids have very small restoring forces in the
589 > off-diagonal directions, and the simulation box can very quickly
590 > form elongated and sheared geometries which become smaller than the
591 > electrostatic or Lennard-Jones cutoff radii.  The NPTf integrator
592 > finds most use in simulating crystals or liquid crystals which
593 > assume non-orthorhombic geometries.
594 >
595 > \subsubsection{\label{methodSection:NPAT}NPAT Ensemble}
596 >
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
600 > interfacial interaction between lipid molecules and surrounding
601 > media. One quantity to describe the interfacial interaction is so
602 > called the average surface area per lipid. Constat area and constant
603 > lateral pressure simulation can be achieved by extending the
604 > standard NPT ensemble with a different pressure control strategy
605 >
606 > \begin{equation}
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$}\\
610 >                  0 & \mbox{otherwise}\\
611 >           \end{array}
612 >    \right.
613 > \end{equation}
614 >
615 > Note that the iterative schemes for NPAT are identical to those
616 > described for the NPTi integrator.
617 >
618 > \subsection{\label{methodSection:NPrT}NP$\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
623 > minimum with respect to surface area $A$
624 > \[
625 > \gamma  = \frac{{\partial G}}{{\partial A}}.
626 > \]
627 > However, a surface tension of zero is not appropriate for relatively
628 > small patches of membrane. In order to eliminate the edge effect of
629 > the membrane simulation, a special ensemble, NP$\gamma$T, is
630 > proposed to maintain the lateral surface tension and normal
631 > pressure. The equation of motion for cell size control tensor,
632 > $\eta$, in $NP\gamma T$ is
633 > \begin{equation}
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( \overleftrightarrow{P} _{\alpha \alpha }
645 > - P_{{\rm{target}}} )
646 > \label{methodEquation:instantaneousSurfaceTensor}
647 > \end{equation}
648 >
649 > There is one additional extended system integrator (NPTxyz), in
650 > which each attempt to preserve the target pressure along the box
651 > walls perpendicular to that particular axis.  The lengths of the box
652 > axes are allowed to fluctuate independently, but the angle between
653 > the box axes does not change. It should be noted that the NPTxyz
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:zcons}Z-Constraint Method}
658 >
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 > 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 > 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 > 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 > 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}

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