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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 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 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
20 time-reversible integrator for rigid bodies in quaternion
21 representation\cite{Matubayasi1999}. Although it is not symplectic, this integrator still
22 demonstrates a better long-time energy conservation than Euler angle
23 methods because of the time-reversible nature. Extending the
24 Trotter-Suzuki factorization to general system with a flat phase
25 space, Miller\cite{Miller2002} and his colleagues devised a novel
26 symplectic, time-reversible and volume-preserving integrator in the
27 quaternion representation, which was shown to be superior to the
28 Matubayasi's time-reversible integrator. However, all of the
29 integrators in the quaternion representation suffer from the
30 computational penalty of constructing a rotation matrix from
31 quaternions to evolve coordinates and velocities at every time step.
32 An alternative integration scheme utilizing the rotation matrix
33 directly proposed by Dullweber, Leimkuhler and McLachlan (DLM) also
34 preserved the same structural properties of the Hamiltonian
35 propagator\cite{Dullweber1997}. In this section, the integration
36 scheme of DLM method will be reviewed and extended to other
37 ensembles.
38
39 \subsection{\label{methodSection:DLM}Integrating the Equations of Motion: the
40 DLM method}
41
42 The DLM method uses a Trotter factorization of the orientational
43 propagator. This has three effects:
44 \begin{enumerate}
45 \item the integrator is area-preserving in phase space (i.e. it is
46 {\it symplectic}),
47 \item the integrator is time-{\it reversible}, making it suitable for Hybrid
48 Monte Carlo applications, and
49 \item the error for a single time step is of order $\mathcal{O}\left(h^3\right)$
50 for timesteps of length $h$.
51 \end{enumerate}
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{Q}(t + h) &\leftarrow \mathrm{rotate}\left( h {\bf j}
67 (t + h / 2) \cdot \overleftrightarrow{\mathsf{I}}^{-1} \right).
68 \end{align*}
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 $\mathsf{Q}$ 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{Q}(t) & \leftarrow & \mathsf{Q}(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. After the
104 first part of the propagation, the forces and body-fixed torques are
105 calculated at the new positions and orientations
106
107 {\tt doForces:}
108 \begin{align*}
109 {\bf f}(t + h) &\leftarrow
110 - \left(\frac{\partial V}{\partial {\bf r}}\right)_{{\bf r}(t + h)}, \\
111 %
112 {\bf \tau}^{s}(t + h) &\leftarrow {\bf u}(t + h)
113 \times (\frac{\partial V}{\partial {\bf u}})_{u(t+h)}, \\
114 %
115 {\bf \tau}^{b}(t + h) &\leftarrow \mathsf{Q}(t + h)
116 \cdot {\bf \tau}^s(t + h).
117 \end{align*}
118 ${\bf u}$ is automatically updated when the rotation matrix
119 $\mathsf{Q}$ is calculated in {\tt moveA}. Once the forces and
120 torques have been obtained at the new time step, the velocities can
121 be advanced to the same time value.
122
123 {\tt moveB:}
124 \begin{align*}
125 {\bf v}\left(t + h \right) &\leftarrow {\bf v}\left(t + h / 2
126 \right)
127 + \frac{h}{2} \left( {\bf f}(t + h) / m \right), \\
128 %
129 {\bf j}\left(t + h \right) &\leftarrow {\bf j}\left(t + h / 2
130 \right)
131 + \frac{h}{2} {\bf \tau}^b(t + h) .
132 \end{align*}
133 The matrix rotations used in the DLM method end up being more costly
134 computationally than the simpler arithmetic quaternion propagation.
135 With the same time step, a 1000-molecule water simulation shows an
136 average 7\% increase in computation time using the DLM method in
137 place of quaternions. This cost is more than justified when
138 comparing the energy conservation of the two methods as illustrated
139 in Fig.~\ref{methodFig:timestep} where the resulting energy drifts at
140 various time steps for both the DLM and quaternion integration
141 schemes are compared. All of the 1000 molecule water simulations
142 started with the same configuration, and the only difference was the
143 method for handling rotational motion. At time steps of 0.1 and 0.5
144 fs, both methods for propagating molecule rotation conserve energy
145 fairly well, with the quaternion method showing a slight energy
146 drift over time in the 0.5 fs time step simulation. At time steps of
147 1 and 2 fs, the energy conservation benefits of the DLM method are
148 clearly demonstrated. Thus, while maintaining the same degree of
149 energy conservation, one can take considerably longer time steps,
150 leading to an overall reduction in computation time.
151
152 \begin{figure}
153 \centering
154 \includegraphics[width=\linewidth]{timeStep.eps}
155 \caption[Energy conservation for quaternion versus DLM
156 dynamics]{Energy conservation using quaternion based integration
157 versus the method proposed by Dullweber \emph{et al.} with
158 increasing time step. For each time step, the dotted line is total
159 energy using the DLM integrator, and the solid line comes from the
160 quaternion integrator. The larger time step plots are shifted up
161 from the true energy baseline for clarity.}
162 \label{methodFig:timestep}
163 \end{figure}
164
165 \subsection{\label{methodSection:NVT}Nos\'{e}-Hoover Thermostatting}
166
167 The Nos\'e-Hoover equations of motion are given by\cite{Hoover1985}
168 \begin{eqnarray}
169 \dot{{\bf r}} & = & {\bf v}, \\
170 \dot{{\bf v}} & = & \frac{{\bf f}}{m} - \chi {\bf v} ,\\
171 \dot{\mathsf{Q}} & = & \mathsf{Q} \cdot
172 \mbox{ skew}\left(\overleftrightarrow{\mathsf{I}}^{-1} \cdot {\bf j}\right), \\
173 \dot{{\bf j}} & = & {\bf j} \times \left(
174 \overleftrightarrow{\mathsf{I}}^{-1} \cdot {\bf j} \right) - \mbox{
175 rot}\left(\mathsf{Q}^{T} \cdot \frac{\partial V}{\partial
176 \mathsf{Q}} \right) - \chi {\bf j}. \label{eq:nosehoovereom}
177 \end{eqnarray}
178 $\chi$ is an ``extra'' variable included in the extended system, and
179 it is propagated using the first order equation of motion
180 \begin{equation}
181 \dot{\chi} = \frac{1}{\tau_{T}^2} \left(
182 \frac{T}{T_{\mathrm{target}}} - 1 \right). \label{eq:nosehooverext}
183 \end{equation}
184 where $\tau_T$ is the time constant for relaxation of the
185 temperature to the target value, and the instantaneous temperature
186 $T$ is given by
187 \begin{equation}
188 T = \frac{2 K}{f k_B}.
189 \end{equation}
190 Here, $f$ is the total number of degrees of freedom in the system,
191 \begin{equation}
192 f = 3 N + 3 N_{\mathrm{orient}} - N_{\mathrm{constraints}},
193 \end{equation}
194 where $N_{\mathrm{orient}}$ is the number of molecules with
195 orientational degrees of freedom. The integration of the equations of motion
196 is carried out in a velocity-Verlet style 2 part algorithm:
197
198 {\tt moveA:}
199 \begin{align*}
200 T(t) &\leftarrow \left\{{\bf v}(t)\right\}, \left\{{\bf j}(t)\right\} ,\\
201 %
202 {\bf v}\left(t + h / 2\right) &\leftarrow {\bf v}(t)
203 + \frac{h}{2} \left( \frac{{\bf f}(t)}{m} - {\bf v}(t)
204 \chi(t)\right), \\
205 %
206 {\bf r}(t + h) &\leftarrow {\bf r}(t)
207 + h {\bf v}\left(t + h / 2 \right) ,\\
208 %
209 {\bf j}\left(t + h / 2 \right) &\leftarrow {\bf j}(t)
210 + \frac{h}{2} \left( {\bf \tau}^b(t) - {\bf j}(t)
211 \chi(t) \right) ,\\
212 %
213 \mathsf{Q}(t + h) &\leftarrow \mathrm{rotate}
214 \left(h * {\bf j}(t + h / 2)
215 \overleftrightarrow{\mathsf{I}}^{-1} \right) ,\\
216 %
217 \chi\left(t + h / 2 \right) &\leftarrow \chi(t)
218 + \frac{h}{2 \tau_T^2} \left( \frac{T(t)}
219 {T_{\mathrm{target}}} - 1 \right) .
220 \end{align*}
221 Here $\mathrm{rotate}(h * {\bf j}
222 \overleftrightarrow{\mathsf{I}}^{-1})$ is the same symplectic Strang
223 factorization of the three rotation operations that was discussed in
224 the section on the DLM integrator. Note that this operation
225 modifies both the rotation matrix $\mathsf{Q}$ and the angular
226 momentum ${\bf j}$. {\tt moveA} propagates velocities by a half
227 time step, and positional degrees of freedom by a full time step.
228 The new positions (and orientations) are then used to calculate a
229 new set of forces and torques in exactly the same way they are
230 calculated in the {\tt doForces} portion of the DLM integrator. Once
231 the forces and torques have been obtained at the new time step, the
232 temperature, velocities, and the extended system variable can be
233 advanced to the same time value.
234
235 {\tt moveB:}
236 \begin{align*}
237 T(t + h) &\leftarrow \left\{{\bf v}(t + h)\right\},
238 \left\{{\bf j}(t + h)\right\}, \\
239 %
240 \chi\left(t + h \right) &\leftarrow \chi\left(t + h /
241 2 \right) + \frac{h}{2 \tau_T^2} \left( \frac{T(t+h)}
242 {T_{\mathrm{target}}} - 1 \right), \\
243 %
244 {\bf v}\left(t + h \right) &\leftarrow {\bf v}\left(t
245 + h / 2 \right) + \frac{h}{2} \left(
246 \frac{{\bf f}(t + h)}{m} - {\bf v}(t + h)
247 \chi(t h)\right) ,\\
248 %
249 {\bf j}\left(t + h \right) &\leftarrow {\bf j}\left(t
250 + h / 2 \right) + \frac{h}{2}
251 \left( {\bf \tau}^b(t + h) - {\bf j}(t + h)
252 \chi(t + h) \right) .
253 \end{align*}
254 Since ${\bf v}(t + h)$ and ${\bf j}(t + h)$ are required to
255 caclculate $T(t + h)$ as well as $\chi(t + h)$, they indirectly
256 depend on their own values at time $t + h$. {\tt moveB} is
257 therefore done in an iterative fashion until $\chi(t + h)$ becomes
258 self-consistent. The Nos\'e-Hoover algorithm is known to conserve a
259 Hamiltonian for the extended system that is, to within a constant,
260 identical to the Helmholtz free energy,\cite{Melchionna1993}
261 \begin{equation}
262 H_{\mathrm{NVT}} = V + K + f k_B T_{\mathrm{target}} \left(
263 \frac{\tau_{T}^2 \chi^2(t)}{2} + \int_{0}^{t} \chi(t^\prime)
264 dt^\prime \right).
265 \end{equation}
266 Poor choices of $h$ or $\tau_T$ can result in non-conservation of
267 $H_{\mathrm{NVT}}$, so the conserved quantity should be checked
268 periodically to verify the quality of the integration.
269
270 \subsection{\label{methodSection:NPTi}Constant-pressure integration with
271 isotropic box (NPTi)}
272
273 We can used an isobaric-isothermal ensemble integrator which is
274 implemented using the Melchionna modifications to the
275 Nos\'e-Hoover-Andersen equations of motion\cite{Melchionna1993}
276 \begin{eqnarray}
277 \dot{{\bf r}} & = & {\bf v} + \eta \left( {\bf r} - {\bf R}_0 \right), \\
278 \dot{{\bf v}} & = & \frac{{\bf f}}{m} - (\eta + \chi) {\bf v}, \\
279 \dot{\mathsf{Q}} & = & \mathsf{Q} \cdot
280 \mbox{ skew}\left(\overleftrightarrow{I}^{-1} \cdot {\bf j}\right),\\
281 \dot{{\bf j}} & = & {\bf j} \times \left(
282 \overleftrightarrow{I}^{-1} \cdot {\bf j} \right) - \mbox{
283 rot}\left(\mathsf{Q}^{T} \cdot \frac{\partial
284 V}{\partial \mathsf{Q}} \right) - \chi {\bf j}, \\
285 \dot{\chi} & = & \frac{1}{\tau_{T}^2} \left(
286 \frac{T}{T_{\mathrm{target}}} - 1 \right) ,\\
287 \dot{\eta} & = & \frac{1}{\tau_{B}^2 f k_B T_{\mathrm{target}}} V
288 \left( P -
289 P_{\mathrm{target}} \right), \\
290 \dot{\mathcal{V}} & = & 3 \mathcal{V} \eta . \label{eq:melchionna1}
291 \end{eqnarray}
292 $\chi$ and $\eta$ are the ``extra'' degrees of freedom in the
293 extended system. $\chi$ is a thermostat, and it has the same
294 function as it does in the Nos\'e-Hoover NVT integrator. $\eta$ is
295 a barostat which controls changes to the volume of the simulation
296 box. ${\bf R}_0$ is the location of the center of mass for the
297 entire system, and $\mathcal{V}$ is the volume of the simulation
298 box. At any time, the volume can be calculated from the determinant
299 of the matrix which describes the box shape:
300 \begin{equation}
301 \mathcal{V} = \det(\mathsf{H}).
302 \end{equation}
303
304 The NPTi integrator requires an instantaneous pressure. This
305 quantity is calculated via the pressure tensor,
306 \begin{equation}
307 \overleftrightarrow{\mathsf{P}}(t) = \frac{1}{\mathcal{V}(t)} \left(
308 \sum_{i=1}^{N} m_i {\bf v}_i(t) \otimes {\bf v}_i(t) \right) +
309 \overleftrightarrow{\mathsf{W}}(t).
310 \end{equation}
311 The kinetic contribution to the pressure tensor utilizes the {\it
312 outer} product of the velocities denoted by the $\otimes$ symbol.
313 The stress tensor is calculated from another outer product of the
314 inter-atomic separation vectors (${\bf r}_{ij} = {\bf r}_j - {\bf
315 r}_i$) with the forces between the same two atoms,
316 \begin{equation}
317 \overleftrightarrow{\mathsf{W}}(t) = \sum_{i} \sum_{j>i} {\bf
318 r}_{ij}(t) \otimes {\bf f}_{ij}(t).
319 \end{equation}
320 The instantaneous pressure is then simply obtained from the trace of
321 the Pressure tensor,
322 \begin{equation}
323 P(t) = \frac{1}{3} \mathrm{Tr} \left(
324 \overleftrightarrow{\mathsf{P}}(t) \right) .
325 \end{equation}
326 In Eq.~\ref{eq:melchionna1}, $\tau_B$ is the time constant for
327 relaxation of the pressure to the target value. Like in the NVT
328 integrator, the integration of the equations of motion is carried
329 out in a velocity-Verlet style 2 part algorithm:
330
331 {\tt moveA:}
332 \begin{align*}
333 T(t) &\leftarrow \left\{{\bf v}(t)\right\}, \left\{{\bf j}(t)\right\} ,\\
334 %
335 P(t) &\leftarrow \left\{{\bf r}(t)\right\}, \left\{{\bf v}(t)\right\} ,\\
336 %
337 {\bf v}\left(t + h / 2\right) &\leftarrow {\bf v}(t)
338 + \frac{h}{2} \left( \frac{{\bf f}(t)}{m} - {\bf v}(t)
339 \left(\chi(t) + \eta(t) \right) \right), \\
340 %
341 {\bf j}\left(t + h / 2 \right) &\leftarrow {\bf j}(t)
342 + \frac{h}{2} \left( {\bf \tau}^b(t) - {\bf j}(t)
343 \chi(t) \right), \\
344 %
345 \mathsf{Q}(t + h) &\leftarrow \mathrm{rotate}\left(h *
346 {\bf j}(t + h / 2) \overleftrightarrow{\mathsf{I}}^{-1}
347 \right) ,\\
348 %
349 \chi\left(t + h / 2 \right) &\leftarrow \chi(t) +
350 \frac{h}{2 \tau_T^2} \left( \frac{T(t)}{T_{\mathrm{target}}} - 1
351 \right) ,\\
352 %
353 \eta(t + h / 2) &\leftarrow \eta(t) + \frac{h
354 \mathcal{V}(t)}{2 N k_B T(t) \tau_B^2} \left( P(t)
355 - P_{\mathrm{target}} \right), \\
356 %
357 {\bf r}(t + h) &\leftarrow {\bf r}(t) + h
358 \left\{ {\bf v}\left(t + h / 2 \right)
359 + \eta(t + h / 2)\left[ {\bf r}(t + h)
360 - {\bf R}_0 \right] \right\} ,\\
361 %
362 \mathsf{H}(t + h) &\leftarrow e^{-h \eta(t + h / 2)}
363 \mathsf{H}(t).
364 \end{align*}
365 Most of these equations are identical to their counterparts in the
366 NVT integrator, but the propagation of positions to time $t + h$
367 depends on the positions at the same time. The simulation box
368 $\mathsf{H}$ is scaled uniformly for one full time step by an
369 exponential factor that depends on the value of $\eta$ at time $t +
370 h / 2$. Reshaping the box uniformly also scales the volume of the
371 box by
372 \begin{equation}
373 \mathcal{V}(t + h) \leftarrow e^{ - 3 h \eta(t + h /2)}.
374 \mathcal{V}(t)
375 \end{equation}
376 The {\tt doForces} step for the NPTi integrator is exactly the same
377 as in both the DLM and NVT integrators. Once the forces and torques
378 have been obtained at the new time step, the velocities can be
379 advanced to the same time value.
380
381 {\tt moveB:}
382 \begin{align*}
383 T(t + h) &\leftarrow \left\{{\bf v}(t + h)\right\},
384 \left\{{\bf j}(t + h)\right\} ,\\
385 %
386 P(t + h) &\leftarrow \left\{{\bf r}(t + h)\right\},
387 \left\{{\bf v}(t + h)\right\}, \\
388 %
389 \chi\left(t + h \right) &\leftarrow \chi\left(t + h /
390 2 \right) + \frac{h}{2 \tau_T^2} \left( \frac{T(t+h)}
391 {T_{\mathrm{target}}} - 1 \right), \\
392 %
393 \eta(t + h) &\leftarrow \eta(t + h / 2) +
394 \frac{h \mathcal{V}(t + h)}{2 N k_B T(t + h)
395 \tau_B^2} \left( P(t + h) - P_{\mathrm{target}} \right), \\
396 %
397 {\bf v}\left(t + h \right) &\leftarrow {\bf v}\left(t
398 + h / 2 \right) + \frac{h}{2} \left(
399 \frac{{\bf f}(t + h)}{m} - {\bf v}(t + h)
400 (\chi(t + h) + \eta(t + h)) \right) ,\\
401 %
402 {\bf j}\left(t + h \right) &\leftarrow {\bf j}\left(t
403 + h / 2 \right) + \frac{h}{2} \left( {\bf
404 \tau}^b(t + h) - {\bf j}(t + h)
405 \chi(t + h) \right) .
406 \end{align*}
407 Once again, since ${\bf v}(t + h)$ and ${\bf j}(t + h)$ are required
408 to caclculate $T(t + h)$, $P(t + h)$, $\chi(t + h)$, and $\eta(t +
409 h)$, they indirectly depend on their own values at time $t + h$.
410 {\tt moveB} is therefore done in an iterative fashion until $\chi(t
411 + h)$ and $\eta(t + h)$ become self-consistent.
412
413 The Melchionna modification of the Nos\'e-Hoover-Andersen algorithm
414 is known to conserve a Hamiltonian for the extended system that is,
415 to within a constant, identical to the Gibbs free energy,
416 \begin{equation}
417 H_{\mathrm{NPTi}} = V + K + f k_B T_{\mathrm{target}} \left(
418 \frac{\tau_{T}^2 \chi^2(t)}{2} + \int_{0}^{t} \chi(t^\prime)
419 dt^\prime \right) + P_{\mathrm{target}} \mathcal{V}(t).
420 \end{equation}
421 It is also known that this algorithm samples the equilibrium
422 distribution for the enthalpy (including contributions for the
423 thermostat and barostat),
424 \begin{equation}
425 H_{\mathrm{NPTi}} = V + K + \frac{f k_B T_{\mathrm{target}}}{2}
426 \left( \chi^2 \tau_T^2 + \eta^2 \tau_B^2 \right) +
427 P_{\mathrm{target}} \mathcal{V}(t).
428 \end{equation}
429
430 \subsection{\label{methodSection:NPTf}Constant-pressure integration with a
431 flexible box (NPTf)}
432
433 There is a relatively simple generalization of the
434 Nos\'e-Hoover-Andersen method to include changes in the simulation
435 box {\it shape} as well as in the volume of the box. This method
436 utilizes the full $3 \times 3$ pressure tensor and introduces a
437 tensor of extended variables ($\overleftrightarrow{\eta}$) to
438 control changes to the box shape. The equations of motion for this
439 method are
440 \begin{eqnarray}
441 \dot{{\bf r}} & = & {\bf v} + \overleftrightarrow{\eta} \cdot \left( {\bf r} - {\bf R}_0 \right), \\
442 \dot{{\bf v}} & = & \frac{{\bf f}}{m} - (\overleftrightarrow{\eta} +
443 \chi \cdot \mathsf{1}) {\bf v}, \\
444 \dot{\mathsf{Q}} & = & \mathsf{Q} \cdot
445 \mbox{ skew}\left(\overleftrightarrow{I}^{-1} \cdot {\bf j}\right) ,\\
446 \dot{{\bf j}} & = & {\bf j} \times \left(
447 \overleftrightarrow{I}^{-1} \cdot {\bf j} \right) - \mbox{
448 rot}\left(\mathsf{Q}^{T} \cdot \frac{\partial
449 V}{\partial \mathsf{Q}} \right) - \chi {\bf j} ,\\
450 \dot{\chi} & = & \frac{1}{\tau_{T}^2} \left(
451 \frac{T}{T_{\mathrm{target}}} - 1 \right) ,\\
452 \dot{\overleftrightarrow{\eta}} & = & \frac{1}{\tau_{B}^2 f k_B
453 T_{\mathrm{target}}} V \left( \overleftrightarrow{\mathsf{P}} - P_{\mathrm{target}}\mathsf{1} \right) ,\\
454 \dot{\mathsf{H}} & = & \overleftrightarrow{\eta} \cdot \mathsf{H} .
455 \label{eq:melchionna2}
456 \end{eqnarray}
457
458 Here, $\mathsf{1}$ is the unit matrix and
459 $\overleftrightarrow{\mathsf{P}}$ is the pressure tensor. Again,
460 the volume, $\mathcal{V} = \det \mathsf{H}$.
461
462 The propagation of the equations of motion is nearly identical to
463 the NPTi integration:
464
465 {\tt moveA:}
466 \begin{align*}
467 T(t) &\leftarrow \left\{{\bf v}(t)\right\}, \left\{{\bf j}(t)\right\} ,\\
468 %
469 \overleftrightarrow{\mathsf{P}}(t) &\leftarrow \left\{{\bf
470 r}(t)\right\},
471 \left\{{\bf v}(t)\right\} ,\\
472 %
473 {\bf v}\left(t + h / 2\right) &\leftarrow {\bf v}(t)
474 + \frac{h}{2} \left( \frac{{\bf f}(t)}{m} -
475 \left(\chi(t)\mathsf{1} + \overleftrightarrow{\eta}(t) \right) \cdot
476 {\bf v}(t) \right), \\
477 %
478 {\bf j}\left(t + h / 2 \right) &\leftarrow {\bf j}(t)
479 + \frac{h}{2} \left( {\bf \tau}^b(t) - {\bf j}(t)
480 \chi(t) \right), \\
481 %
482 \mathsf{Q}(t + h) &\leftarrow \mathrm{rotate}\left(h *
483 {\bf j}(t + h / 2) \overleftrightarrow{\mathsf{I}}^{-1}
484 \right), \\
485 %
486 \chi\left(t + h / 2 \right) &\leftarrow \chi(t) +
487 \frac{h}{2 \tau_T^2} \left( \frac{T(t)}{T_{\mathrm{target}}}
488 - 1 \right), \\
489 %
490 \overleftrightarrow{\eta}(t + h / 2) &\leftarrow
491 \overleftrightarrow{\eta}(t) + \frac{h \mathcal{V}(t)}{2 N k_B
492 T(t) \tau_B^2} \left( \overleftrightarrow{\mathsf{P}}(t)
493 - P_{\mathrm{target}}\mathsf{1} \right), \\
494 %
495 {\bf r}(t + h) &\leftarrow {\bf r}(t) + h \left\{ {\bf v}
496 \left(t + h / 2 \right) + \overleftrightarrow{\eta}(t +
497 h / 2) \cdot \left[ {\bf r}(t + h)
498 - {\bf R}_0 \right] \right\}, \\
499 %
500 \mathsf{H}(t + h) &\leftarrow \mathsf{H}(t) \cdot e^{-h
501 \overleftrightarrow{\eta}(t + h / 2)} .
502 \end{align*}
503 Here, a power series expansion truncated at second order for the
504 exponential operation is used to scale the simulation box. The {\tt
505 moveB} portion of the algorithm is largely unchanged from the NPTi
506 integrator:
507
508 {\tt moveB:}
509 \begin{align*}
510 T(t + h) &\leftarrow \left\{{\bf v}(t + h)\right\},
511 \left\{{\bf j}(t + h)\right\}, \\
512 %
513 \overleftrightarrow{\mathsf{P}}(t + h) &\leftarrow \left\{{\bf r}
514 (t + h)\right\}, \left\{{\bf v}(t
515 + h)\right\}, \left\{{\bf f}(t + h)\right\} ,\\
516 %
517 \chi\left(t + h \right) &\leftarrow \chi\left(t + h /
518 2 \right) + \frac{h}{2 \tau_T^2} \left( \frac{T(t+
519 h)}{T_{\mathrm{target}}} - 1 \right), \\
520 %
521 \overleftrightarrow{\eta}(t + h) &\leftarrow
522 \overleftrightarrow{\eta}(t + h / 2) +
523 \frac{h \mathcal{V}(t + h)}{2 N k_B T(t + h)
524 \tau_B^2} \left( \overleftrightarrow{P}(t + h)
525 - P_{\mathrm{target}}\mathsf{1} \right) ,\\
526 %
527 {\bf v}\left(t + h \right) &\leftarrow {\bf v}\left(t
528 + h / 2 \right) + \frac{h}{2} \left(
529 \frac{{\bf f}(t + h)}{m} -
530 (\chi(t + h)\mathsf{1} + \overleftrightarrow{\eta}(t
531 + h)) \right) \cdot {\bf v}(t + h), \\
532 %
533 {\bf j}\left(t + h \right) &\leftarrow {\bf j}\left(t
534 + h / 2 \right) + \frac{h}{2} \left( {\bf \tau}^b(t
535 + h) - {\bf j}(t + h) \chi(t + h) \right) .
536 \end{align*}
537 The iterative schemes for both {\tt moveA} and {\tt moveB} are
538 identical to those described for the NPTi integrator. The NPTf
539 integrator is known to conserve the following Hamiltonian:
540 \begin{eqnarray*}
541 H_{\mathrm{NPTf}} & = & V + K + f k_B T_{\mathrm{target}} \left(
542 \frac{\tau_{T}^2 \chi^2(t)}{2} + \int_{0}^{t} \chi(t^\prime)
543 dt^\prime \right) \\
544 & & + P_{\mathrm{target}} \mathcal{V}(t) + \frac{f k_B
545 T_{\mathrm{target}}}{2}
546 \mathrm{Tr}\left[\overleftrightarrow{\eta}(t)\right]^2 \tau_B^2.
547 \end{eqnarray*}
548 This integrator must be used with care, particularly in liquid
549 simulations. Liquids have very small restoring forces in the
550 off-diagonal directions, and the simulation box can very quickly
551 form elongated and sheared geometries which become smaller than the
552 electrostatic or Lennard-Jones cutoff radii. The NPTf integrator
553 finds most use in simulating crystals or liquid crystals which
554 assume non-orthorhombic geometries.
555
556 \subsection{\label{methodSection:NPAT}NPAT Ensemble}
557
558 A comprehensive understanding of relations between structures and
559 functions in biological membrane system ultimately relies on
560 structure and dynamics of lipid bilayers, which are strongly
561 affected by the interfacial interaction between lipid molecules and
562 surrounding media. One quantity used to describe the interfacial
563 interaction is the average surface area per lipid.
564 Constant area and constant lateral pressure simulations can be
565 achieved by extending the standard NPT ensemble with a different
566 pressure control strategy
567
568 \begin{equation}
569 \dot {\overleftrightarrow{\eta}} _{\alpha \beta}=\left\{\begin{array}{ll}
570 \frac{{V(P_{\alpha \beta } - P_{{\rm{target}}} )}}{{\tau_{\rm{B}}^{\rm{2}} fk_B T_{{\rm{target}}} }}
571 & \mbox{if $ \alpha = \beta = z$}\\
572 0 & \mbox{otherwise}\\
573 \end{array}
574 \right.
575 \end{equation}
576 Note that the iterative schemes for NPAT are identical to those
577 described for the NPTi integrator.
578
579 \subsection{\label{methodSection:NPrT}NP$\gamma$T
580 Ensemble}
581
582 Theoretically, the surface tension $\gamma$ of a stress free
583 membrane system should be zero since its surface free energy $G$ is
584 minimum with respect to surface area $A$,
585 \begin{equation}
586 \gamma = \frac{{\partial G}}{{\partial A}}.
587 \end{equation}0
588 However, a surface tension of zero is not
589 appropriate for relatively small patches of membrane. In order to
590 eliminate the edge effect of membrane simulations, a special
591 ensemble, NP$\gamma$T, has been proposed to maintain the lateral
592 surface tension and normal pressure. The equation of motion for the
593 cell size control tensor, $\eta$, in $NP\gamma T$ is
594 \begin{equation}
595 \dot {\overleftrightarrow{\eta}} _{\alpha \beta}=\left\{\begin{array}{ll}
596 - A_{xy} (\gamma _\alpha - \gamma _{{\rm{target}}} ) & \mbox{$\alpha = \beta = x$ or $\alpha = \beta = y$}\\
597 \frac{{V(P_{\alpha \beta } - P_{{\rm{target}}} )}}{{\tau _{\rm{B}}^{\rm{2}} fk_B T_{{\rm{target}}}}} & \mbox{$\alpha = \beta = z$} \\
598 0 & \mbox{$\alpha \ne \beta$} \\
599 \end{array}
600 \right.
601 \end{equation}
602 where $ \gamma _{{\rm{target}}}$ is the external surface tension and
603 the instantaneous surface tensor $\gamma _\alpha$ is given by
604 \begin{equation}
605 \gamma _\alpha = - h_z( \overleftrightarrow{P} _{\alpha \alpha }
606 - P_{{\rm{target}}} )
607 \label{methodEquation:instantaneousSurfaceTensor}
608 \end{equation}
609 There is one additional extended system integrator (NPTxyz), in
610 which each attempt to preserve the target pressure along the box
611 walls perpendicular to that particular axis. The lengths of the box
612 axes are allowed to fluctuate independently, but the angle between
613 the box axes does not change. It should be noted that the NPTxyz
614 integrator is a special case of $NP\gamma T$ if the surface tension
615 $\gamma$ is set to zero, and if $x$ and $y$ can move independently.
616
617 \section{\label{methodSection:zcons}The Z-Constraint Method}
618
619 Based on the fluctuation-dissipation theorem, a force
620 auto-correlation method was developed by Roux and Karplus to
621 investigate the dynamics of ions inside ion channels\cite{Roux1991}.
622 The time-dependent friction coefficient can be calculated from the
623 deviation of the instantaneous force from its mean force.
624 \begin{equation}
625 \xi(z,t)=\langle\delta F(z,t)\delta F(z,0)\rangle/k_{B}T,
626 \end{equation}
627 where%
628 \begin{equation}
629 \delta F(z,t)=F(z,t)-\langle F(z,t)\rangle.
630 \end{equation}
631 If the time-dependent friction decays rapidly, the static friction
632 coefficient can be approximated by
633 \begin{equation}
634 \xi_{\text{static}}(z)=\int_{0}^{\infty}\langle\delta F(z,t)\delta
635 F(z,0)\rangle dt.
636 \end{equation}
637 Allowing diffusion constant to then be calculated through the
638 Einstein relation:\cite{Marrink1994}
639 \begin{equation}
640 D(z)=\frac{k_{B}T}{\xi_{\text{static}}(z)}=\frac{(k_{B}T)^{2}}{\int_{0}^{\infty
641 }\langle\delta F(z,t)\delta F(z,0)\rangle dt}.%
642 \end{equation}
643 The Z-Constraint method, which fixes the z coordinates of the
644 molecules with respect to the center of the mass of the system, has
645 been a method suggested to obtain the forces required for the force
646 auto-correlation calculation.\cite{Marrink1994} However, simply
647 resetting the coordinate will move the center of the mass of the
648 whole system. To avoid this problem, we reset the forces of
649 z-constrained molecules as well as subtract the total constraint
650 forces from the rest of the system after the force calculation at
651 each time step instead of resetting the coordinate. After the force
652 calculation, we define $G_\alpha$ as
653 \begin{equation}
654 G_{\alpha} = \sum_i F_{\alpha i}, \label{oopseEq:zc1}
655 \end{equation}
656 where $F_{\alpha i}$ is the force in the z direction of atom $i$ in
657 z-constrained molecule $\alpha$. The forces of the z constrained
658 molecule are then set to:
659 \begin{equation}
660 F_{\alpha i} = F_{\alpha i} -
661 \frac{m_{\alpha i} G_{\alpha}}{\sum_i m_{\alpha i}}.
662 \end{equation}
663 Here, $m_{\alpha i}$ is the mass of atom $i$ in the z-constrained
664 molecule. Having rescaled the forces, the velocities must also be
665 rescaled to subtract out any center of mass velocity in the z
666 direction.
667 \begin{equation}
668 v_{\alpha i} = v_{\alpha i} -
669 \frac{\sum_i m_{\alpha i} v_{\alpha i}}{\sum_i m_{\alpha i}},
670 \end{equation}
671 where $v_{\alpha i}$ is the velocity of atom $i$ in the z direction.
672 Lastly, all of the accumulated z constrained forces must be
673 subtracted from the system to keep the system center of mass from
674 drifting.
675 \begin{equation}
676 F_{\beta i} = F_{\beta i} - \frac{m_{\beta i} \sum_{\alpha}
677 G_{\alpha}}
678 {\sum_{\beta}\sum_i m_{\beta i}},
679 \end{equation}
680 where $\beta$ are all of the unconstrained molecules in the system.
681 Similarly, the velocities of the unconstrained molecules must also
682 be scaled.
683 \begin{equation}
684 v_{\beta i} = v_{\beta i} + \sum_{\alpha}
685 \frac{\sum_i m_{\alpha i} v_{\alpha i}}{\sum_i m_{\alpha i}}.
686 \end{equation}
687 At the very beginning of the simulation, the molecules may not be at
688 their constrained positions. To move a z-constrained molecule to its
689 specified position, a simple harmonic potential is used
690 \begin{equation}
691 U(t)=\frac{1}{2}k_{\text{Harmonic}}(z(t)-z_{\text{cons}})^{2},%
692 \end{equation}
693 where $k_{\text{Harmonic}}$ is the harmonic force constant, $z(t)$
694 is the current $z$ coordinate of the center of mass of the
695 constrained molecule, and $z_{\text{cons}}$ is the constrained
696 position. The harmonic force operating on the z-constrained molecule
697 at time $t$ can be calculated by
698 \begin{equation}
699 F_{z_{\text{Harmonic}}}(t)=-\frac{\partial U(t)}{\partial z(t)}=
700 -k_{\text{Harmonic}}(z(t)-z_{\text{cons}}).
701 \end{equation}