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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 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 the canonical and isobaric-isothermal ensembles. In addition to
9 > the standard ensemble, specific ensembles have been developed to
10 > account for the anisotropy between the lateral and normal directions
11 > of membranes. The $NPAT$ ensemble, in which the normal pressure and
12 > the lateral surface area of the membrane are kept constant, and the
13 > $NP\gamma T$ ensemble, in which the normal pressure and the lateral
14 > surface tension are kept constant were proposed to address the
15 > issues.
16  
17 < \section{\label{methodSection:hydrodynamics}Hydrodynamics}
17 > Integration schemes for the rotational motion of the rigid molecules
18 > in the microcanonical ensemble have been extensively studied over
19 > the last two decades. Matubayasi 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 Euler angle methods because of
23 > the time-reversible nature. Extending the Trotter-Suzuki
24 > factorization to general system with a flat phase space, Miller and
25 > his colleagues devised a novel symplectic, time-reversible and
26 > volume-preserving integrator in the quaternion representation, which
27 > was shown to be superior to the Matubayasi's time-reversible
28 > integrator. However, all of the integrators in the quaternion
29 > representation suffer from the computational penalty of constructing
30 > a rotation matrix from quaternions to evolve coordinates and
31 > velocities at every time step. An alternative integration scheme
32 > utilizing the rotation matrix directly proposed by Dullweber,
33 > Leimkuhler and McLachlan (DLM) also preserved the same structural
34 > properties of the Hamiltonian flow. In this section, the integration
35 > scheme of DLM method will be reviewed and extended to other
36 > ensembles.
37  
38 < \section{\label{methodSection:langevin}Integrators for Langevin Dynamics of Rigid Bodies}
38 > \subsection{\label{methodSection:DLM}Integrating the Equations of Motion: the
39 > DLM method}
40  
41 < \section{\label{methodSection:coarseGrained}Coarse-Grained Modeling}
41 > The DLM method uses a Trotter factorization of the orientational
42 > propagator.  This has three effects:
43 > \begin{enumerate}
44 > \item the integrator is area-preserving in phase space (i.e. it is
45 > {\it symplectic}),
46 > \item the integrator is time-{\it reversible}, making it suitable for Hybrid
47 > Monte Carlo applications, and
48 > \item the error for a single time step is of order $\mathcal{O}\left(h^4\right)$
49 > for timesteps of length $h$.
50 > \end{enumerate}
51  
52 < \section{\label{methodSection:moleculeScale}Molecular-Scale Modeling}
52 > The integration of the equations of motion is carried out in a
53 > velocity-Verlet style 2-part algorithm, where $h= \delta t$:
54 >
55 > {\tt moveA:}
56 > \begin{align*}
57 > {\bf v}\left(t + h / 2\right)  &\leftarrow  {\bf v}(t)
58 >    + \frac{h}{2} \left( {\bf f}(t) / m \right), \\
59 > %
60 > {\bf r}(t + h) &\leftarrow {\bf r}(t)
61 >    + h  {\bf v}\left(t + h / 2 \right), \\
62 > %
63 > {\bf j}\left(t + h / 2 \right)  &\leftarrow {\bf j}(t)
64 >    + \frac{h}{2} {\bf \tau}^b(t), \\
65 > %
66 > \mathsf{A}(t + h) &\leftarrow \mathrm{rotate}\left( h {\bf j}
67 >    (t + h / 2) \cdot \overleftrightarrow{\mathsf{I}}^{-1} \right).
68 > \end{align*}
69 >
70 > In this context, the $\mathrm{rotate}$ function is the reversible
71 > product of the three body-fixed rotations,
72 > \begin{equation}
73 > \mathrm{rotate}({\bf a}) = \mathsf{G}_x(a_x / 2) \cdot
74 > \mathsf{G}_y(a_y / 2) \cdot \mathsf{G}_z(a_z) \cdot \mathsf{G}_y(a_y
75 > / 2) \cdot \mathsf{G}_x(a_x /2),
76 > \end{equation}
77 > where each rotational propagator, $\mathsf{G}_\alpha(\theta)$,
78 > rotates both the rotation matrix ($\mathsf{A}$) and the body-fixed
79 > angular momentum (${\bf j}$) by an angle $\theta$ around body-fixed
80 > axis $\alpha$,
81 > \begin{equation}
82 > \mathsf{G}_\alpha( \theta ) = \left\{
83 > \begin{array}{lcl}
84 > \mathsf{A}(t) & \leftarrow & \mathsf{A}(0) \cdot \mathsf{R}_\alpha(\theta)^T, \\
85 > {\bf j}(t) & \leftarrow & \mathsf{R}_\alpha(\theta) \cdot {\bf
86 > j}(0).
87 > \end{array}
88 > \right.
89 > \end{equation}
90 > $\mathsf{R}_\alpha$ is a quadratic approximation to the single-axis
91 > rotation matrix.  For example, in the small-angle limit, the
92 > rotation matrix around the body-fixed x-axis can be approximated as
93 > \begin{equation}
94 > \mathsf{R}_x(\theta) \approx \left(
95 > \begin{array}{ccc}
96 > 1 & 0 & 0 \\
97 > 0 & \frac{1-\theta^2 / 4}{1 + \theta^2 / 4}  & -\frac{\theta}{1+
98 > \theta^2 / 4} \\
99 > 0 & \frac{\theta}{1+ \theta^2 / 4} & \frac{1-\theta^2 / 4}{1 +
100 > \theta^2 / 4}
101 > \end{array}
102 > \right).
103 > \end{equation}
104 > All other rotations follow in a straightforward manner.
105 >
106 > After the first part of the propagation, the forces and body-fixed
107 > torques are calculated at the new positions and orientations
108 >
109 > {\tt doForces:}
110 > \begin{align*}
111 > {\bf f}(t + h) &\leftarrow
112 >    - \left(\frac{\partial V}{\partial {\bf r}}\right)_{{\bf r}(t + h)}, \\
113 > %
114 > {\bf \tau}^{s}(t + h) &\leftarrow {\bf u}(t + h)
115 >    \times (\frac{\partial V}{\partial {\bf u}})_{u(t+h)}, \\
116 > %
117 > {\bf \tau}^{b}(t + h) &\leftarrow \mathsf{A}(t + h)
118 >    \cdot {\bf \tau}^s(t + h).
119 > \end{align*}
120 >
121 > ${\bf u}$ is automatically updated when the rotation matrix
122 > $\mathsf{A}$ is calculated in {\tt moveA}.  Once the forces and
123 > torques have been obtained at the new time step, the velocities can
124 > be advanced to the same time value.
125 >
126 > {\tt moveB:}
127 > \begin{align*}
128 > {\bf v}\left(t + h \right)  &\leftarrow  {\bf v}\left(t + h / 2
129 > \right)
130 >    + \frac{h}{2} \left( {\bf f}(t + h) / m \right), \\
131 > %
132 > {\bf j}\left(t + h \right)  &\leftarrow {\bf j}\left(t + h / 2
133 > \right)
134 >    + \frac{h}{2} {\bf \tau}^b(t + h) .
135 > \end{align*}
136 >
137 > The matrix rotations used in the DLM method end up being more costly
138 > computationally than the simpler arithmetic quaternion propagation.
139 > With the same time step, a 1000-molecule water simulation shows an
140 > average 7\% increase in computation time using the DLM method in
141 > place of quaternions. This cost is more than justified when
142 > comparing the energy conservation of the two methods as illustrated
143 > in Fig.~\ref{methodFig:timestep}.
144 >
145 > \begin{figure}
146 > \centering
147 > \includegraphics[width=\linewidth]{timeStep.eps}
148 > \caption[Energy conservation for quaternion versus DLM
149 > dynamics]{Energy conservation using quaternion based integration
150 > versus the method proposed by Dullweber \emph{et al.} with
151 > increasing time step. For each time step, the dotted line is total
152 > energy using the DLM integrator, and the solid line comes from the
153 > quaternion integrator. The larger time step plots are shifted up
154 > from the true energy baseline for clarity.}
155 > \label{methodFig:timestep}
156 > \end{figure}
157 >
158 > In Fig.~\ref{methodFig:timestep}, the resulting energy drift at
159 > various time steps for both the DLM and quaternion integration
160 > schemes is compared. All of the 1000 molecule water simulations
161 > started with the same configuration, and the only difference was the
162 > method for handling rotational motion. At time steps of 0.1 and 0.5
163 > fs, both methods for propagating molecule rotation conserve energy
164 > fairly well, with the quaternion method showing a slight energy
165 > drift over time in the 0.5 fs time step simulation. At time steps of
166 > 1 and 2 fs, the energy conservation benefits of the DLM method are
167 > clearly demonstrated. Thus, while maintaining the same degree of
168 > energy conservation, one can take considerably longer time steps,
169 > leading to an overall reduction in computation time.
170 >
171 > \subsection{\label{methodSection:NVT}Nos\'{e}-Hoover Thermostatting}
172 >
173 > The Nos\'e-Hoover equations of motion are given by\cite{Hoover1985}
174 > \begin{eqnarray}
175 > \dot{{\bf r}} & = & {\bf v}, \\
176 > \dot{{\bf v}} & = & \frac{{\bf f}}{m} - \chi {\bf v} ,\\
177 > \dot{\mathsf{A}} & = & \mathsf{A} \cdot
178 > \mbox{ skew}\left(\overleftrightarrow{\mathsf{I}}^{-1} \cdot {\bf j}\right), \\
179 > \dot{{\bf j}} & = & {\bf j} \times \left(
180 > \overleftrightarrow{\mathsf{I}}^{-1} \cdot {\bf j} \right) - \mbox{
181 > rot}\left(\mathsf{A}^{T} \cdot \frac{\partial V}{\partial
182 > \mathsf{A}} \right) - \chi {\bf j}. \label{eq:nosehoovereom}
183 > \end{eqnarray}
184 >
185 > $\chi$ is an ``extra'' variable included in the extended system, and
186 > it is propagated using the first order equation of motion
187 > \begin{equation}
188 > \dot{\chi} = \frac{1}{\tau_{T}^2} \left(
189 > \frac{T}{T_{\mathrm{target}}} - 1 \right). \label{eq:nosehooverext}
190 > \end{equation}
191 >
192 > The instantaneous temperature $T$ is proportional to the total
193 > kinetic energy (both translational and orientational) and is given
194 > by
195 > \begin{equation}
196 > T = \frac{2 K}{f k_B}
197 > \end{equation}
198 > Here, $f$ is the total number of degrees of freedom in the system,
199 > \begin{equation}
200 > f = 3 N + 3 N_{\mathrm{orient}} - N_{\mathrm{constraints}},
201 > \end{equation}
202 > where $N_{\mathrm{orient}}$ is the number of molecules with
203 > orientational degrees of freedom, and $K$ is the total kinetic
204 > energy,
205 > \begin{equation}
206 > K = \sum_{i=1}^{N} \frac{1}{2} m_i {\bf v}_i^T \cdot {\bf v}_i +
207 > \sum_{i=1}^{N_{\mathrm{orient}}}  \frac{1}{2} {\bf j}_i^T \cdot
208 > \overleftrightarrow{\mathsf{I}}_i^{-1} \cdot {\bf j}_i.
209 > \end{equation}
210 >
211 > In eq.(\ref{eq:nosehooverext}), $\tau_T$ is the time constant for
212 > relaxation of the temperature to the target value. The integration
213 > of the equations of motion is carried out in a velocity-Verlet style
214 > 2 part algorithm:
215 >
216 > {\tt moveA:}
217 > \begin{align*}
218 > T(t) &\leftarrow \left\{{\bf v}(t)\right\}, \left\{{\bf j}(t)\right\} ,\\
219 > %
220 > {\bf v}\left(t + h / 2\right)  &\leftarrow {\bf v}(t)
221 >    + \frac{h}{2} \left( \frac{{\bf f}(t)}{m} - {\bf v}(t)
222 >    \chi(t)\right), \\
223 > %
224 > {\bf r}(t + h) &\leftarrow {\bf r}(t)
225 >    + h {\bf v}\left(t + h / 2 \right) ,\\
226 > %
227 > {\bf j}\left(t + h / 2 \right)  &\leftarrow {\bf j}(t)
228 >    + \frac{h}{2} \left( {\bf \tau}^b(t) - {\bf j}(t)
229 >    \chi(t) \right) ,\\
230 > %
231 > \mathsf{A}(t + h) &\leftarrow \mathrm{rotate}
232 >    \left(h * {\bf j}(t + h / 2)
233 >    \overleftrightarrow{\mathsf{I}}^{-1} \right) ,\\
234 > %
235 > \chi\left(t + h / 2 \right) &\leftarrow \chi(t)
236 >    + \frac{h}{2 \tau_T^2} \left( \frac{T(t)}
237 >    {T_{\mathrm{target}}} - 1 \right) .
238 > \end{align*}
239 >
240 > Here $\mathrm{rotate}(h * {\bf j}
241 > \overleftrightarrow{\mathsf{I}}^{-1})$ is the same symplectic
242 > Trotter factorization of the three rotation operations that was
243 > discussed in the section on the DLM integrator.  Note that this
244 > operation modifies both the rotation matrix $\mathsf{A}$ and the
245 > angular momentum ${\bf j}$.  {\tt moveA} propagates velocities by a
246 > half time step, and positional degrees of freedom by a full time
247 > step.  The new positions (and orientations) are then used to
248 > calculate a new set of forces and torques in exactly the same way
249 > they are calculated in the {\tt doForces} portion of the DLM
250 > integrator.
251 >
252 > Once the forces and torques have been obtained at the new time step,
253 > the temperature, velocities, and the extended system variable can be
254 > advanced to the same time value.
255 >
256 > {\tt moveB:}
257 > \begin{align*}
258 > T(t + h) &\leftarrow \left\{{\bf v}(t + h)\right\},
259 >    \left\{{\bf j}(t + h)\right\}, \\
260 > %
261 > \chi\left(t + h \right) &\leftarrow \chi\left(t + h /
262 >    2 \right) + \frac{h}{2 \tau_T^2} \left( \frac{T(t+h)}
263 >    {T_{\mathrm{target}}} - 1 \right), \\
264 > %
265 > {\bf v}\left(t + h \right)  &\leftarrow {\bf v}\left(t
266 >    + h / 2 \right) + \frac{h}{2} \left(
267 >    \frac{{\bf f}(t + h)}{m} - {\bf v}(t + h)
268 >    \chi(t h)\right) ,\\
269 > %
270 > {\bf j}\left(t + h \right) &\leftarrow {\bf j}\left(t
271 >    + h / 2 \right) + \frac{h}{2}
272 >    \left( {\bf \tau}^b(t + h) - {\bf j}(t + h)
273 >    \chi(t + h) \right) .
274 > \end{align*}
275 >
276 > Since ${\bf v}(t + h)$ and ${\bf j}(t + h)$ are required to
277 > caclculate $T(t + h)$ as well as $\chi(t + h)$, they indirectly
278 > depend on their own values at time $t + h$.  {\tt moveB} is
279 > therefore done in an iterative fashion until $\chi(t + h)$ becomes
280 > self-consistent.
281 >
282 > The Nos\'e-Hoover algorithm is known to conserve a Hamiltonian for
283 > the extended system that is, to within a constant, identical to the
284 > Helmholtz free energy,\cite{Melchionna1993}
285 > \begin{equation}
286 > H_{\mathrm{NVT}} = V + K + f k_B T_{\mathrm{target}} \left(
287 > \frac{\tau_{T}^2 \chi^2(t)}{2} + \int_{0}^{t} \chi(t^\prime)
288 > dt^\prime \right).
289 > \end{equation}
290 > Poor choices of $h$ or $\tau_T$ can result in non-conservation of
291 > $H_{\mathrm{NVT}}$, so the conserved quantity is maintained in the
292 > last column of the {\tt .stat} file to allow checks on the quality
293 > of the integration.
294 >
295 > \subsection{\label{methodSection:NPTi}Constant-pressure integration with
296 > isotropic box deformations (NPTi)}
297 >
298 > We can used an isobaric-isothermal ensemble integrator which is
299 > implemented using the Melchionna modifications to the
300 > Nos\'e-Hoover-Andersen equations of motion,\cite{Melchionna1993}
301 >
302 > \begin{eqnarray}
303 > \dot{{\bf r}} & = & {\bf v} + \eta \left( {\bf r} - {\bf R}_0 \right), \\
304 > \dot{{\bf v}} & = & \frac{{\bf f}}{m} - (\eta + \chi) {\bf v}, \\
305 > \dot{\mathsf{A}} & = & \mathsf{A} \cdot
306 > \mbox{ skew}\left(\overleftrightarrow{I}^{-1} \cdot {\bf j}\right),\\
307 > \dot{{\bf j}} & = & {\bf j} \times \left(
308 > \overleftrightarrow{I}^{-1} \cdot {\bf j} \right) - \mbox{
309 > rot}\left(\mathsf{A}^{T} \cdot \frac{\partial
310 > V}{\partial \mathsf{A}} \right) - \chi {\bf j}, \\
311 > \dot{\chi} & = & \frac{1}{\tau_{T}^2} \left(
312 > \frac{T}{T_{\mathrm{target}}} - 1 \right) ,\\
313 > \dot{\eta} & = & \frac{1}{\tau_{B}^2 f k_B T_{\mathrm{target}}} V
314 > \left( P -
315 > P_{\mathrm{target}} \right), \\
316 > \dot{\mathcal{V}} & = & 3 \mathcal{V} \eta . \label{eq:melchionna1}
317 > \end{eqnarray}
318 >
319 > $\chi$ and $\eta$ are the ``extra'' degrees of freedom in the
320 > extended system.  $\chi$ is a thermostat, and it has the same
321 > function as it does in the Nos\'e-Hoover NVT integrator.  $\eta$ is
322 > a barostat which controls changes to the volume of the simulation
323 > box.  ${\bf R}_0$ is the location of the center of mass for the
324 > entire system, and $\mathcal{V}$ is the volume of the simulation
325 > box.  At any time, the volume can be calculated from the determinant
326 > of the matrix which describes the box shape:
327 > \begin{equation}
328 > \mathcal{V} = \det(\mathsf{H}).
329 > \end{equation}
330 >
331 > The NPTi integrator requires an instantaneous pressure. This
332 > quantity is calculated via the pressure tensor,
333 > \begin{equation}
334 > \overleftrightarrow{\mathsf{P}}(t) = \frac{1}{\mathcal{V}(t)} \left(
335 > \sum_{i=1}^{N} m_i {\bf v}_i(t) \otimes {\bf v}_i(t) \right) +
336 > \overleftrightarrow{\mathsf{W}}(t).
337 > \end{equation}
338 > The kinetic contribution to the pressure tensor utilizes the {\it
339 > outer} product of the velocities denoted by the $\otimes$ symbol.
340 > The stress tensor is calculated from another outer product of the
341 > inter-atomic separation vectors (${\bf r}_{ij} = {\bf r}_j - {\bf
342 > r}_i$) with the forces between the same two atoms,
343 > \begin{equation}
344 > \overleftrightarrow{\mathsf{W}}(t) = \sum_{i} \sum_{j>i} {\bf
345 > r}_{ij}(t) \otimes {\bf f}_{ij}(t).
346 > \end{equation}
347 > The instantaneous pressure is then simply obtained from the trace of
348 > the Pressure tensor,
349 > \begin{equation}
350 > P(t) = \frac{1}{3} \mathrm{Tr} \left(
351 > \overleftrightarrow{\mathsf{P}}(t). \right)
352 > \end{equation}
353 >
354 > In eq.(\ref{eq:melchionna1}), $\tau_B$ is the time constant for
355 > relaxation of the pressure to the target value. Like in the NVT
356 > integrator, the integration of the equations of motion is carried
357 > out in a velocity-Verlet style 2 part algorithm:
358 >
359 > {\tt moveA:}
360 > \begin{align*}
361 > T(t) &\leftarrow \left\{{\bf v}(t)\right\}, \left\{{\bf j}(t)\right\} ,\\
362 > %
363 > P(t) &\leftarrow \left\{{\bf r}(t)\right\}, \left\{{\bf v}(t)\right\} ,\\
364 > %
365 > {\bf v}\left(t + h / 2\right)  &\leftarrow {\bf v}(t)
366 >    + \frac{h}{2} \left( \frac{{\bf f}(t)}{m} - {\bf v}(t)
367 >    \left(\chi(t) + \eta(t) \right) \right), \\
368 > %
369 > {\bf j}\left(t + h / 2 \right)  &\leftarrow {\bf j}(t)
370 >    + \frac{h}{2} \left( {\bf \tau}^b(t) - {\bf j}(t)
371 >    \chi(t) \right), \\
372 > %
373 > \mathsf{A}(t + h) &\leftarrow \mathrm{rotate}\left(h *
374 >    {\bf j}(t + h / 2) \overleftrightarrow{\mathsf{I}}^{-1}
375 >    \right) ,\\
376 > %
377 > \chi\left(t + h / 2 \right) &\leftarrow \chi(t) +
378 >    \frac{h}{2 \tau_T^2} \left( \frac{T(t)}{T_{\mathrm{target}}} - 1
379 >    \right) ,\\
380 > %
381 > \eta(t + h / 2) &\leftarrow \eta(t) + \frac{h
382 >    \mathcal{V}(t)}{2 N k_B T(t) \tau_B^2} \left( P(t)
383 >    - P_{\mathrm{target}} \right), \\
384 > %
385 > {\bf r}(t + h) &\leftarrow {\bf r}(t) + h
386 >    \left\{ {\bf v}\left(t + h / 2 \right)
387 >    + \eta(t + h / 2)\left[ {\bf r}(t + h)
388 >    - {\bf R}_0 \right] \right\} ,\\
389 > %
390 > \mathsf{H}(t + h) &\leftarrow e^{-h \eta(t + h / 2)}
391 >    \mathsf{H}(t).
392 > \end{align*}
393 >
394 > Most of these equations are identical to their counterparts in the
395 > NVT integrator, but the propagation of positions to time $t + h$
396 > depends on the positions at the same time. The simulation box
397 > $\mathsf{H}$ is scaled uniformly for one full time step by an
398 > exponential factor that depends on the value of $\eta$ at time $t +
399 > h / 2$.  Reshaping the box uniformly also scales the volume of the
400 > box by
401 > \begin{equation}
402 > \mathcal{V}(t + h) \leftarrow e^{ - 3 h \eta(t + h /2)}.
403 > \mathcal{V}(t)
404 > \end{equation}
405 >
406 > The {\tt doForces} step for the NPTi integrator is exactly the same
407 > as in both the DLM and NVT integrators.  Once the forces and torques
408 > have been obtained at the new time step, the velocities can be
409 > advanced to the same time value.
410 >
411 > {\tt moveB:}
412 > \begin{align*}
413 > T(t + h) &\leftarrow \left\{{\bf v}(t + h)\right\},
414 >    \left\{{\bf j}(t + h)\right\} ,\\
415 > %
416 > P(t + h) &\leftarrow  \left\{{\bf r}(t + h)\right\},
417 >    \left\{{\bf v}(t + h)\right\}, \\
418 > %
419 > \chi\left(t + h \right) &\leftarrow \chi\left(t + h /
420 >    2 \right) + \frac{h}{2 \tau_T^2} \left( \frac{T(t+h)}
421 >    {T_{\mathrm{target}}} - 1 \right), \\
422 > %
423 > \eta(t + h) &\leftarrow \eta(t + h / 2) +
424 >    \frac{h \mathcal{V}(t + h)}{2 N k_B T(t + h)
425 >    \tau_B^2} \left( P(t + h) - P_{\mathrm{target}} \right), \\
426 > %
427 > {\bf v}\left(t + h \right)  &\leftarrow {\bf v}\left(t
428 >    + h / 2 \right) + \frac{h}{2} \left(
429 >    \frac{{\bf f}(t + h)}{m} - {\bf v}(t + h)
430 >    (\chi(t + h) + \eta(t + h)) \right) ,\\
431 > %
432 > {\bf j}\left(t + h \right)  &\leftarrow {\bf j}\left(t
433 >    + h / 2 \right) + \frac{h}{2} \left( {\bf
434 >    \tau}^b(t + h) - {\bf j}(t + h)
435 >    \chi(t + h) \right) .
436 > \end{align*}
437 >
438 > Once again, since ${\bf v}(t + h)$ and ${\bf j}(t + h)$ are required
439 > to caclculate $T(t + h)$, $P(t + h)$, $\chi(t + h)$, and $\eta(t +
440 > h)$, they indirectly depend on their own values at time $t + h$.
441 > {\tt moveB} is therefore done in an iterative fashion until $\chi(t
442 > + h)$ and $\eta(t + h)$ become self-consistent.
443 >
444 > The Melchionna modification of the Nos\'e-Hoover-Andersen algorithm
445 > is known to conserve a Hamiltonian for the extended system that is,
446 > to within a constant, identical to the Gibbs free energy,
447 > \begin{equation}
448 > H_{\mathrm{NPTi}} = V + K + f k_B T_{\mathrm{target}} \left(
449 > \frac{\tau_{T}^2 \chi^2(t)}{2} + \int_{0}^{t} \chi(t^\prime)
450 > dt^\prime \right) + P_{\mathrm{target}} \mathcal{V}(t).
451 > \end{equation}
452 > Poor choices of $\delta t$, $\tau_T$, or $\tau_B$ can result in
453 > non-conservation of $H_{\mathrm{NPTi}}$, so the conserved quantity
454 > is maintained in the last column of the {\tt .stat} file to allow
455 > checks on the quality of the integration.  It is also known that
456 > this algorithm samples the equilibrium distribution for the enthalpy
457 > (including contributions for the thermostat and barostat),
458 > \begin{equation}
459 > H_{\mathrm{NPTi}} = V + K + \frac{f k_B T_{\mathrm{target}}}{2}
460 > \left( \chi^2 \tau_T^2 + \eta^2 \tau_B^2 \right) +
461 > P_{\mathrm{target}} \mathcal{V}(t).
462 > \end{equation}
463 >
464 > \subsection{\label{methodSection:NPTf}Constant-pressure integration with a
465 > flexible box (NPTf)}
466 >
467 > There is a relatively simple generalization of the
468 > Nos\'e-Hoover-Andersen method to include changes in the simulation
469 > box {\it shape} as well as in the volume of the box.  This method
470 > utilizes the full $3 \times 3$ pressure tensor and introduces a
471 > tensor of extended variables ($\overleftrightarrow{\eta}$) to
472 > control changes to the box shape.  The equations of motion for this
473 > method are
474 > \begin{eqnarray}
475 > \dot{{\bf r}} & = & {\bf v} + \overleftrightarrow{\eta} \cdot \left( {\bf r} - {\bf R}_0 \right), \\
476 > \dot{{\bf v}} & = & \frac{{\bf f}}{m} - (\overleftrightarrow{\eta} +
477 > \chi \cdot \mathsf{1}) {\bf v}, \\
478 > \dot{\mathsf{A}} & = & \mathsf{A} \cdot
479 > \mbox{ skew}\left(\overleftrightarrow{I}^{-1} \cdot {\bf j}\right) ,\\
480 > \dot{{\bf j}} & = & {\bf j} \times \left(
481 > \overleftrightarrow{I}^{-1} \cdot {\bf j} \right) - \mbox{
482 > rot}\left(\mathsf{A}^{T} \cdot \frac{\partial
483 > V}{\partial \mathsf{A}} \right) - \chi {\bf j} ,\\
484 > \dot{\chi} & = & \frac{1}{\tau_{T}^2} \left(
485 > \frac{T}{T_{\mathrm{target}}} - 1 \right) ,\\
486 > \dot{\overleftrightarrow{\eta}} & = & \frac{1}{\tau_{B}^2 f k_B
487 > T_{\mathrm{target}}} V \left( \overleftrightarrow{\mathsf{P}} - P_{\mathrm{target}}\mathsf{1} \right) ,\\
488 > \dot{\mathsf{H}} & = &  \overleftrightarrow{\eta} \cdot \mathsf{H} .
489 > \label{eq:melchionna2}
490 > \end{eqnarray}
491 >
492 > Here, $\mathsf{1}$ is the unit matrix and
493 > $\overleftrightarrow{\mathsf{P}}$ is the pressure tensor.  Again,
494 > the volume, $\mathcal{V} = \det \mathsf{H}$.
495 >
496 > The propagation of the equations of motion is nearly identical to
497 > the NPTi integration:
498 >
499 > {\tt moveA:}
500 > \begin{align*}
501 > T(t) &\leftarrow \left\{{\bf v}(t)\right\}, \left\{{\bf j}(t)\right\} ,\\
502 > %
503 > \overleftrightarrow{\mathsf{P}}(t) &\leftarrow \left\{{\bf
504 > r}(t)\right\},
505 >    \left\{{\bf v}(t)\right\} ,\\
506 > %
507 > {\bf v}\left(t + h / 2\right)  &\leftarrow {\bf v}(t)
508 >    + \frac{h}{2} \left( \frac{{\bf f}(t)}{m} -
509 >    \left(\chi(t)\mathsf{1} + \overleftrightarrow{\eta}(t) \right) \cdot
510 >    {\bf v}(t) \right), \\
511 > %
512 > {\bf j}\left(t + h / 2 \right)  &\leftarrow {\bf j}(t)
513 >    + \frac{h}{2} \left( {\bf \tau}^b(t) - {\bf j}(t)
514 >    \chi(t) \right), \\
515 > %
516 > \mathsf{A}(t + h) &\leftarrow \mathrm{rotate}\left(h *
517 >    {\bf j}(t + h / 2) \overleftrightarrow{\mathsf{I}}^{-1}
518 >    \right), \\
519 > %
520 > \chi\left(t + h / 2 \right) &\leftarrow \chi(t) +
521 >    \frac{h}{2 \tau_T^2} \left( \frac{T(t)}{T_{\mathrm{target}}}
522 >    - 1 \right), \\
523 > %
524 > \overleftrightarrow{\eta}(t + h / 2) &\leftarrow
525 >    \overleftrightarrow{\eta}(t) + \frac{h \mathcal{V}(t)}{2 N k_B
526 >    T(t) \tau_B^2} \left( \overleftrightarrow{\mathsf{P}}(t)
527 >    - P_{\mathrm{target}}\mathsf{1} \right), \\
528 > %
529 > {\bf r}(t + h) &\leftarrow {\bf r}(t) + h \left\{ {\bf v}
530 >    \left(t + h / 2 \right) + \overleftrightarrow{\eta}(t +
531 >    h / 2) \cdot \left[ {\bf r}(t + h)
532 >    - {\bf R}_0 \right] \right\}, \\
533 > %
534 > \mathsf{H}(t + h) &\leftarrow \mathsf{H}(t) \cdot e^{-h
535 >    \overleftrightarrow{\eta}(t + h / 2)} .
536 > \end{align*}
537 > Here, a power series expansion truncated at second order for the
538 > exponential operation is used to scale the simulation box.
539 >
540 > The {\tt moveB} portion of the algorithm is largely unchanged from
541 > the NPTi integrator:
542 >
543 > {\tt moveB:}
544 > \begin{align*}
545 > T(t + h) &\leftarrow \left\{{\bf v}(t + h)\right\},
546 >    \left\{{\bf j}(t + h)\right\}, \\
547 > %
548 > \overleftrightarrow{\mathsf{P}}(t + h) &\leftarrow \left\{{\bf r}
549 >    (t + h)\right\}, \left\{{\bf v}(t
550 >    + h)\right\}, \left\{{\bf f}(t + h)\right\} ,\\
551 > %
552 > \chi\left(t + h \right) &\leftarrow \chi\left(t + h /
553 >    2 \right) + \frac{h}{2 \tau_T^2} \left( \frac{T(t+
554 >    h)}{T_{\mathrm{target}}} - 1 \right), \\
555 > %
556 > \overleftrightarrow{\eta}(t + h) &\leftarrow
557 >    \overleftrightarrow{\eta}(t + h / 2) +
558 >    \frac{h \mathcal{V}(t + h)}{2 N k_B T(t + h)
559 >    \tau_B^2} \left( \overleftrightarrow{P}(t + h)
560 >    - P_{\mathrm{target}}\mathsf{1} \right) ,\\
561 > %
562 > {\bf v}\left(t + h \right)  &\leftarrow {\bf v}\left(t
563 >    + h / 2 \right) + \frac{h}{2} \left(
564 >    \frac{{\bf f}(t + h)}{m} -
565 >    (\chi(t + h)\mathsf{1} + \overleftrightarrow{\eta}(t
566 >    + h)) \right) \cdot {\bf v}(t + h), \\
567 > %
568 > {\bf j}\left(t + h \right)  &\leftarrow {\bf j}\left(t
569 >    + h / 2 \right) + \frac{h}{2} \left( {\bf \tau}^b(t
570 >    + h) - {\bf j}(t + h) \chi(t + h) \right) .
571 > \end{align*}
572 >
573 > The iterative schemes for both {\tt moveA} and {\tt moveB} are
574 > identical to those described for the NPTi integrator.
575 >
576 > The NPTf integrator is known to conserve the following Hamiltonian:
577 > \begin{eqnarray*}
578 > H_{\mathrm{NPTf}} & = & V + K + f k_B T_{\mathrm{target}} \left(
579 > \frac{\tau_{T}^2 \chi^2(t)}{2} + \int_{0}^{t} \chi(t^\prime)
580 > dt^\prime \right) \\
581 > & & + P_{\mathrm{target}} \mathcal{V}(t) + \frac{f k_B
582 > T_{\mathrm{target}}}{2}
583 > \mathrm{Tr}\left[\overleftrightarrow{\eta}(t)\right]^2 \tau_B^2.
584 > \end{eqnarray*}
585 >
586 > This integrator must be used with care, particularly in liquid
587 > simulations.  Liquids have very small restoring forces in the
588 > off-diagonal directions, and the simulation box can very quickly
589 > form elongated and sheared geometries which become smaller than the
590 > electrostatic or Lennard-Jones cutoff radii.  The NPTf integrator
591 > finds most use in simulating crystals or liquid crystals which
592 > assume non-orthorhombic geometries.
593 >
594 > \subsection{\label{methodSection:NPAT}NPAT Ensemble}
595 >
596 > A comprehensive understanding of relations between structures and
597 > functions in biological membrane system ultimately relies on
598 > structure and dynamics of lipid bilayers, which are strongly
599 > affected by the interfacial interaction between lipid molecules and
600 > surrounding media. One quantity to describe the interfacial
601 > interaction is so called the average surface area per lipid.
602 > Constant area and constant lateral pressure simulations can be
603 > achieved by extending the standard NPT ensemble with a different
604 > 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, has been
630 > proposed to maintain the lateral surface tension and normal
631 > pressure. The equation of motion for the 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, and if $x$ and $y$ can move independently.
656 >
657 > \section{\label{methodSection:zcons}The 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, we 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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