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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 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 \subsection{\label{methodSection:DLM}Integrating the Equations of Motion: the
39 DLM method}
40
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 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}