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\chapter{\label{chapt:methodology}METHODOLOGY} |
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|
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\section{\label{methodSection:rigidBodyIntegrators}Integrators for Rigid Body Motion in Molecular Dynamics} |
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|
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In order to mimic experiments which are usually performed under |
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constant temperature and/or pressure, extended Hamiltonian system |
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methods have been developed to generate statistical ensembles, such |
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as the canonical and isobaric-isothermal ensembles. In addition to |
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the standard ensemble, specific ensembles have been developed to |
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account for the anisotropy between the lateral and normal directions |
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of membranes. The $NPAT$ ensemble, in which the normal pressure and |
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the lateral surface area of the membrane are kept constant, and the |
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$NP\gamma T$ ensemble, in which the normal pressure and the lateral |
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surface tension are kept constant were proposed to address the |
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issues. |
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|
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Integration schemes for the rotational motion of the rigid molecules |
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in the microcanonical ensemble have been extensively studied over |
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the last two decades. Matubayasi developed a |
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time-reversible integrator for rigid bodies in quaternion |
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representation\cite{Matubayasi1999}. Although it is not symplectic, this integrator still |
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demonstrates a better long-time energy conservation than Euler angle |
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methods because of the time-reversible nature. Extending the |
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Trotter-Suzuki factorization to general system with a flat phase |
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space, Miller\cite{Miller2002} and his colleagues devised a novel |
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symplectic, time-reversible and volume-preserving integrator in the |
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quaternion representation, which was shown to be superior to the |
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Matubayasi's time-reversible integrator. However, all of the |
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integrators in the quaternion representation suffer from the |
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computational penalty of constructing a rotation matrix from |
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quaternions to evolve coordinates and velocities at every time step. |
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An alternative integration scheme utilizing the rotation matrix |
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directly proposed by Dullweber, Leimkuhler and McLachlan (DLM) also |
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preserved the same structural properties of the Hamiltonian |
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propagator\cite{Dullweber1997}. In this section, the integration |
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scheme of DLM method will be reviewed and extended to other |
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ensembles. |
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|
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\subsection{\label{methodSection:DLM}Integrating the Equations of Motion: the |
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DLM method} |
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|
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The DLM method uses a Trotter factorization of the orientational |
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propagator. This has three effects: |
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\begin{enumerate} |
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\item the integrator is area-preserving in phase space (i.e. it is |
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{\it symplectic}), |
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\item the integrator is time-{\it reversible}, making it suitable for Hybrid |
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Monte Carlo applications, and |
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\item the error for a single time step is of order $\mathcal{O}\left(h^3\right)$ |
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for timesteps of length $h$. |
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\end{enumerate} |
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The integration of the equations of motion is carried out in a |
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velocity-Verlet style 2-part algorithm, where $h= \delta t$: |
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|
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{\tt moveA:} |
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\begin{align*} |
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{\bf v}\left(t + h / 2\right) &\leftarrow {\bf v}(t) |
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+ \frac{h}{2} \left( {\bf f}(t) / m \right), \\ |
59 |
% |
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{\bf r}(t + h) &\leftarrow {\bf r}(t) |
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+ h {\bf v}\left(t + h / 2 \right), \\ |
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% |
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{\bf j}\left(t + h / 2 \right) &\leftarrow {\bf j}(t) |
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+ \frac{h}{2} {\bf \tau}^b(t), \\ |
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% |
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\mathsf{Q}(t + h) &\leftarrow \mathrm{rotate}\left( h {\bf j} |
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(t + h / 2) \cdot \overleftrightarrow{\mathsf{I}}^{-1} \right). |
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\end{align*} |
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In this context, the $\mathrm{rotate}$ function is the reversible |
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product of the three body-fixed rotations, |
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\begin{equation} |
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\mathrm{rotate}({\bf a}) = \mathsf{G}_x(a_x / 2) \cdot |
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\mathsf{G}_y(a_y / 2) \cdot \mathsf{G}_z(a_z) \cdot \mathsf{G}_y(a_y |
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/ 2) \cdot \mathsf{G}_x(a_x /2), |
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\end{equation} |
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where each rotational propagator, $\mathsf{G}_\alpha(\theta)$, |
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rotates both the rotation matrix $\mathsf{Q}$ and the body-fixed |
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angular momentum ${\bf j}$ by an angle $\theta$ around body-fixed |
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axis $\alpha$, |
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\begin{equation} |
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\mathsf{G}_\alpha( \theta ) = \left\{ |
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\begin{array}{lcl} |
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\mathsf{Q}(t) & \leftarrow & \mathsf{Q}(0) \cdot \mathsf{R}_\alpha(\theta)^T, \\ |
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{\bf j}(t) & \leftarrow & \mathsf{R}_\alpha(\theta) \cdot {\bf |
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j}(0). |
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\end{array} |
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\right. |
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\end{equation} |
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$\mathsf{R}_\alpha$ is a quadratic approximation to the single-axis |
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rotation matrix. For example, in the small-angle limit, the |
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rotation matrix around the body-fixed x-axis can be approximated as |
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\begin{equation} |
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\mathsf{R}_x(\theta) \approx \left( |
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\begin{array}{ccc} |
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1 & 0 & 0 \\ |
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0 & \frac{1-\theta^2 / 4}{1 + \theta^2 / 4} & -\frac{\theta}{1+ |
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\theta^2 / 4} \\ |
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0 & \frac{\theta}{1+ \theta^2 / 4} & \frac{1-\theta^2 / 4}{1 + |
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\theta^2 / 4} |
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\end{array} |
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\right). |
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\end{equation} |
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All other rotations follow in a straightforward manner. After the |
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first part of the propagation, the forces and body-fixed torques are |
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calculated at the new positions and orientations |
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|
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{\tt doForces:} |
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\begin{align*} |
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{\bf f}(t + h) &\leftarrow |
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- \left(\frac{\partial V}{\partial {\bf r}}\right)_{{\bf r}(t + h)}, \\ |
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% |
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{\bf \tau}^{s}(t + h) &\leftarrow {\bf u}(t + h) |
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\times (\frac{\partial V}{\partial {\bf u}})_{u(t+h)}, \\ |
114 |
% |
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{\bf \tau}^{b}(t + h) &\leftarrow \mathsf{Q}(t + h) |
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\cdot {\bf \tau}^s(t + h). |
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\end{align*} |
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${\bf u}$ is automatically updated when the rotation matrix |
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$\mathsf{Q}$ is calculated in {\tt moveA}. Once the forces and |
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torques have been obtained at the new time step, the velocities can |
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be advanced to the same time value. |
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|
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{\tt moveB:} |
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\begin{align*} |
125 |
{\bf v}\left(t + h \right) &\leftarrow {\bf v}\left(t + h / 2 |
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\right) |
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+ \frac{h}{2} \left( {\bf f}(t + h) / m \right), \\ |
128 |
% |
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{\bf j}\left(t + h \right) &\leftarrow {\bf j}\left(t + h / 2 |
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\right) |
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+ \frac{h}{2} {\bf \tau}^b(t + h) . |
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\end{align*} |
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The matrix rotations used in the DLM method end up being more costly |
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computationally than the simpler arithmetic quaternion propagation. |
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With the same time step, a 1000-molecule water simulation shows an |
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average 7\% increase in computation time using the DLM method in |
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place of quaternions. This cost is more than justified when |
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comparing the energy conservation of the two methods as illustrated |
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in Fig.~\ref{methodFig:timestep} where the resulting energy drifts at |
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various time steps for both the DLM and quaternion integration |
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schemes are compared. All of the 1000 molecule water simulations |
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started with the same configuration, and the only difference was the |
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method for handling rotational motion. At time steps of 0.1 and 0.5 |
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fs, both methods for propagating molecule rotation conserve energy |
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fairly well, with the quaternion method showing a slight energy |
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drift over time in the 0.5 fs time step simulation. At time steps of |
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1 and 2 fs, the energy conservation benefits of the DLM method are |
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clearly demonstrated. Thus, while maintaining the same degree of |
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energy conservation, one can take considerably longer time steps, |
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leading to an overall reduction in computation time. |
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|
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\begin{figure} |
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\centering |
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\includegraphics[width=\linewidth]{timeStep.eps} |
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\caption[Energy conservation for quaternion versus DLM |
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dynamics]{Energy conservation using quaternion based integration |
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versus the method proposed by Dullweber \emph{et al.} with |
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increasing time step. For each time step, the dotted line is total |
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energy using the DLM integrator, and the solid line comes from the |
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quaternion integrator. The larger time step plots are shifted up |
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from the true energy baseline for clarity.} |
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\label{methodFig:timestep} |
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\end{figure} |
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|
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\subsection{\label{methodSection:NVT}Nos\'{e}-Hoover Thermostatting} |
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|
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The Nos\'e-Hoover equations of motion are given by\cite{Hoover1985} |
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\begin{eqnarray} |
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\dot{{\bf r}} & = & {\bf v}, \\ |
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\dot{{\bf v}} & = & \frac{{\bf f}}{m} - \chi {\bf v} ,\\ |
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\dot{\mathsf{Q}} & = & \mathsf{Q} \cdot |
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\mbox{ skew}\left(\overleftrightarrow{\mathsf{I}}^{-1} \cdot {\bf j}\right), \\ |
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\dot{{\bf j}} & = & {\bf j} \times \left( |
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\overleftrightarrow{\mathsf{I}}^{-1} \cdot {\bf j} \right) - \mbox{ |
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rot}\left(\mathsf{Q}^{T} \cdot \frac{\partial V}{\partial |
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\mathsf{Q}} \right) - \chi {\bf j}. \label{eq:nosehoovereom} |
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\end{eqnarray} |
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$\chi$ is an ``extra'' variable included in the extended system, and |
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it is propagated using the first order equation of motion |
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\begin{equation} |
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\dot{\chi} = \frac{1}{\tau_{T}^2} \left( |
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\frac{T}{T_{\mathrm{target}}} - 1 \right). \label{eq:nosehooverext} |
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\end{equation} |
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where $\tau_T$ is the time constant for relaxation of the |
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temperature to the target value, and the instantaneous temperature |
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$T$ is given by |
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\begin{equation} |
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T = \frac{2 K}{f k_B}. |
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\end{equation} |
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Here, $f$ is the total number of degrees of freedom in the system, |
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\begin{equation} |
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f = 3 N + 3 N_{\mathrm{orient}} - N_{\mathrm{constraints}}, |
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\end{equation} |
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where $N_{\mathrm{orient}}$ is the number of molecules with |
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orientational degrees of freedom. The integration of the equations of motion |
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is carried out in a velocity-Verlet style 2 part algorithm: |
197 |
|
198 |
{\tt moveA:} |
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\begin{align*} |
200 |
T(t) &\leftarrow \left\{{\bf v}(t)\right\}, \left\{{\bf j}(t)\right\} ,\\ |
201 |
% |
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{\bf v}\left(t + h / 2\right) &\leftarrow {\bf v}(t) |
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+ \frac{h}{2} \left( \frac{{\bf f}(t)}{m} - {\bf v}(t) |
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\chi(t)\right), \\ |
205 |
% |
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{\bf r}(t + h) &\leftarrow {\bf r}(t) |
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+ h {\bf v}\left(t + h / 2 \right) ,\\ |
208 |
% |
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{\bf j}\left(t + h / 2 \right) &\leftarrow {\bf j}(t) |
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+ \frac{h}{2} \left( {\bf \tau}^b(t) - {\bf j}(t) |
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\chi(t) \right) ,\\ |
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% |
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\mathsf{Q}(t + h) &\leftarrow \mathrm{rotate} |
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\left(h {\bf j}(t + h / 2) |
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\overleftrightarrow{\mathsf{I}}^{-1} \right) ,\\ |
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% |
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\chi\left(t + h / 2 \right) &\leftarrow \chi(t) |
218 |
+ \frac{h}{2 \tau_T^2} \left( \frac{T(t)} |
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{T_{\mathrm{target}}} - 1 \right) . |
220 |
\end{align*} |
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Here $\mathrm{rotate}(h * {\bf j} |
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\overleftrightarrow{\mathsf{I}}^{-1})$ is the same symplectic Strang |
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factorization of the three rotation operations that was discussed in |
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the section on the DLM integrator. Note that this operation |
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modifies both the rotation matrix $\mathsf{Q}$ and the angular |
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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 |
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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 |
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temperature, velocities, and the extended system variable can be |
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advanced to the same time value. |
234 |
|
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{\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} |
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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 |
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periodically to verify the quality of the integration. |
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|
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\subsection{\label{methodSection:NPTi}Constant-pressure integration with |
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isotropic box (NPTi)} |
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|
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We can used an isobaric-isothermal ensemble integrator which is |
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implemented using the Melchionna modifications to the |
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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 |
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function as it does in the Nos\'e-Hoover NVT integrator. $\eta$ is |
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a barostat which controls changes to the volume of the simulation |
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box. ${\bf R}_0$ is the location of the center of mass for the |
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entire system, and $\mathcal{V}$ is the volume of the simulation |
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box. At any time, the volume can be calculated from the determinant |
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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 |
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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 (${\bf r}_{ij} = {\bf r}_j - {\bf |
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r}_i$) 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} |