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1 \chapter{\label{chapt:methodology}METHODOLOGY}
2
3 \section{\label{methodSection:rigidBodyIntegrators}Integrators for Rigid Body Motion in Molecular Dynamics}
4
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 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 \subsection{\label{methodSection:DLM}Integrating the Equations of Motion: the
38 DLM method}
39
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 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 k_B
583 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 \subsection{\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}