| 822 |
|
% |
| 823 |
|
q(\Delta t) &= q(0) + \frac{{\Delta t}}{2}\left[ {\dot q(0) + \dot |
| 824 |
|
q(\Delta t)} \right]. % |
| 825 |
< |
\label{introEquation:positionVerlet1} |
| 825 |
> |
\label{introEquation:positionVerlet2} |
| 826 |
|
\end{align} |
| 827 |
|
|
| 828 |
|
\subsubsection{\label{introSection:errorAnalysis}Error Analysis and Higher Order Methods} |
| 887 |
|
has proven to be a powerful tool for studying the functions of |
| 888 |
|
biological systems, providing structural, thermodynamic and |
| 889 |
|
dynamical information. |
| 890 |
+ |
|
| 891 |
+ |
One of the principal tools for modeling proteins, nucleic acids and |
| 892 |
+ |
their complexes. Stability of proteins Folding of proteins. |
| 893 |
+ |
Molecular recognition by:proteins, DNA, RNA, lipids, hormones STP, |
| 894 |
+ |
etc. Enzyme reactions Rational design of biologically active |
| 895 |
+ |
molecules (drug design) Small and large-scale conformational |
| 896 |
+ |
changes. determination and construction of 3D structures (homology, |
| 897 |
+ |
Xray diffraction, NMR) Dynamic processes such as ion transport in |
| 898 |
+ |
biological systems. |
| 899 |
|
|
| 900 |
+ |
Macroscopic properties are related to microscopic behavior. |
| 901 |
+ |
|
| 902 |
+ |
Time dependent (and independent) microscopic behavior of a molecule |
| 903 |
+ |
can be calculated by molecular dynamics simulations. |
| 904 |
+ |
|
| 905 |
|
\subsection{\label{introSec:mdInit}Initialization} |
| 906 |
|
|
| 907 |
|
\subsection{\label{introSec:forceEvaluation}Force Evaluation} |
| 941 |
|
The break through in geometric literature suggests that, in order to |
| 942 |
|
develop a long-term integration scheme, one should preserve the |
| 943 |
|
symplectic structure of the flow. Introducing conjugate momentum to |
| 944 |
< |
rotation matrix $A$ and re-formulating Hamiltonian's equation, a |
| 944 |
> |
rotation matrix $Q$ and re-formulating Hamiltonian's equation, a |
| 945 |
|
symplectic integrator, RSHAKE, was proposed to evolve the |
| 946 |
|
Hamiltonian system in a constraint manifold by iteratively |
| 947 |
< |
satisfying the orthogonality constraint $A_t A = 1$. An alternative |
| 947 |
> |
satisfying the orthogonality constraint $Q_T Q = 1$. An alternative |
| 948 |
|
method using quaternion representation was developed by Omelyan. |
| 949 |
|
However, both of these methods are iterative and inefficient. In |
| 950 |
|
this section, we will present a symplectic Lie-Poisson integrator |
| 1150 |
|
0 & { - \sin \theta _1 } & {\cos \theta _1 } \\ |
| 1151 |
|
\end{array}} \right),\theta _1 = \frac{{\pi _1 }}{{I_1 }}\Delta t. |
| 1152 |
|
\] |
| 1153 |
< |
To reduce the cost of computing expensive functions in e^{\Delta |
| 1154 |
< |
tR_1 }, we can use Cayley transformation, |
| 1153 |
> |
To reduce the cost of computing expensive functions in $e^{\Delta |
| 1154 |
> |
tR_1 }$, we can use Cayley transformation, |
| 1155 |
|
\[ |
| 1156 |
|
e^{\Delta tR_1 } \approx (1 - \Delta tR_1 )^{ - 1} (1 + \Delta tR_1 |
| 1157 |
|
) |
| 1227 |
|
\varphi _{\Delta t} = \varphi _{\Delta t/2,V} \circ \varphi |
| 1228 |
|
_{\Delta t,T} \circ \varphi _{\Delta t/2,V}. |
| 1229 |
|
\] |
| 1230 |
< |
Moreover, \varphi _{\Delta t/2,V} can be divided into two sub-flows |
| 1231 |
< |
which corresponding to force and torque respectively, |
| 1230 |
> |
Moreover, $\varphi _{\Delta t/2,V}$ can be divided into two |
| 1231 |
> |
sub-flows which corresponding to force and torque respectively, |
| 1232 |
|
\[ |
| 1233 |
|
\varphi _{\Delta t/2,V} = \varphi _{\Delta t/2,F} \circ \varphi |
| 1234 |
|
_{\Delta t/2,\tau }. |
| 1235 |
|
\] |
| 1236 |
|
Since the associated operators of $\varphi _{\Delta t/2,F} $ and |
| 1237 |
|
$\circ \varphi _{\Delta t/2,\tau }$ are commuted, the composition |
| 1238 |
< |
order inside \varphi _{\Delta t/2,V} does not matter. |
| 1238 |
> |
order inside $\varphi _{\Delta t/2,V}$ does not matter. |
| 1239 |
|
|
| 1240 |
|
Furthermore, kinetic potential can be separated to translational |
| 1241 |
|
kinetic term, $T^t (p)$, and rotational kinetic term, $T^r (\pi )$, |
| 1265 |
|
mimics a simple heat bath with stochastic and dissipative forces, |
| 1266 |
|
has been applied in a variety of studies. This section will review |
| 1267 |
|
the theory of Langevin dynamics simulation. A brief derivation of |
| 1268 |
< |
generalized Langevin Dynamics will be given first. Follow that, we |
| 1268 |
> |
generalized Langevin equation will be given first. Follow that, we |
| 1269 |
|
will discuss the physical meaning of the terms appearing in the |
| 1270 |
|
equation as well as the calculation of friction tensor from |
| 1271 |
|
hydrodynamics theory. |
| 1272 |
|
|
| 1273 |
< |
\subsection{\label{introSection:generalizedLangevinDynamics}Generalized Langevin Dynamics} |
| 1273 |
> |
\subsection{\label{introSection:generalizedLangevinDynamics}Derivation of Generalized Langevin Equation} |
| 1274 |
|
|
| 1275 |
+ |
Harmonic bath model, in which an effective set of harmonic |
| 1276 |
+ |
oscillators are used to mimic the effect of a linearly responding |
| 1277 |
+ |
environment, has been widely used in quantum chemistry and |
| 1278 |
+ |
statistical mechanics. One of the successful applications of |
| 1279 |
+ |
Harmonic bath model is the derivation of Deriving Generalized |
| 1280 |
+ |
Langevin Dynamics. Lets consider a system, in which the degree of |
| 1281 |
+ |
freedom $x$ is assumed to couple to the bath linearly, giving a |
| 1282 |
+ |
Hamiltonian of the form |
| 1283 |
|
\begin{equation} |
| 1284 |
|
H = \frac{{p^2 }}{{2m}} + U(x) + H_B + \Delta U(x,x_1 , \ldots x_N) |
| 1285 |
< |
\label{introEquation:bathGLE} |
| 1285 |
> |
\label{introEquation:bathGLE}. |
| 1286 |
|
\end{equation} |
| 1287 |
< |
where $H_B$ is harmonic bath Hamiltonian, |
| 1287 |
> |
Here $p$ is a momentum conjugate to $q$, $m$ is the mass associated |
| 1288 |
> |
with this degree of freedom, $H_B$ is harmonic bath Hamiltonian, |
| 1289 |
|
\[ |
| 1290 |
< |
H_B =\sum\limits_{\alpha = 1}^N {\left\{ {\frac{{p_\alpha ^2 |
| 1291 |
< |
}}{{2m_\alpha }} + \frac{1}{2}m_\alpha w_\alpha ^2 } \right\}} |
| 1290 |
> |
H_B = \sum\limits_{\alpha = 1}^N {\left\{ {\frac{{p_\alpha ^2 |
| 1291 |
> |
}}{{2m_\alpha }} + \frac{1}{2}m_\alpha \omega _\alpha ^2 } |
| 1292 |
> |
\right\}} |
| 1293 |
|
\] |
| 1294 |
< |
and $\Delta U$ is bilinear system-bath coupling, |
| 1294 |
> |
where the index $\alpha$ runs over all the bath degrees of freedom, |
| 1295 |
> |
$\omega _\alpha$ are the harmonic bath frequencies, $m_\alpha$ are |
| 1296 |
> |
the harmonic bath masses, and $\Delta U$ is bilinear system-bath |
| 1297 |
> |
coupling, |
| 1298 |
|
\[ |
| 1299 |
|
\Delta U = - \sum\limits_{\alpha = 1}^N {g_\alpha x_\alpha x} |
| 1300 |
|
\] |
| 1301 |
< |
Completing the square, |
| 1301 |
> |
where $g_\alpha$ are the coupling constants between the bath and the |
| 1302 |
> |
coordinate $x$. Introducing |
| 1303 |
|
\[ |
| 1304 |
< |
H_B + \Delta U = \sum\limits_{\alpha = 1}^N {\left\{ |
| 1305 |
< |
{\frac{{p_\alpha ^2 }}{{2m_\alpha }} + \frac{1}{2}m_\alpha |
| 1306 |
< |
w_\alpha ^2 \left( {x_\alpha - \frac{{g_\alpha }}{{m_\alpha |
| 1307 |
< |
w_\alpha ^2 }}x} \right)^2 } \right\}} - \sum\limits_{\alpha = |
| 1308 |
< |
1}^N {\frac{{g_\alpha ^2 }}{{2m_\alpha w_\alpha ^2 }}} x^2 |
| 1281 |
< |
\] |
| 1282 |
< |
and putting it back into Eq.~\ref{introEquation:bathGLE}, |
| 1304 |
> |
W(x) = U(x) - \sum\limits_{\alpha = 1}^N {\frac{{g_\alpha ^2 |
| 1305 |
> |
}}{{2m_\alpha w_\alpha ^2 }}} x^2 |
| 1306 |
> |
\] and combining the last two terms in Equation |
| 1307 |
> |
\ref{introEquation:bathGLE}, we may rewrite the Harmonic bath |
| 1308 |
> |
Hamiltonian as |
| 1309 |
|
\[ |
| 1310 |
|
H = \frac{{p^2 }}{{2m}} + W(x) + \sum\limits_{\alpha = 1}^N |
| 1311 |
|
{\left\{ {\frac{{p_\alpha ^2 }}{{2m_\alpha }} + \frac{1}{2}m_\alpha |
| 1312 |
|
w_\alpha ^2 \left( {x_\alpha - \frac{{g_\alpha }}{{m_\alpha |
| 1313 |
|
w_\alpha ^2 }}x} \right)^2 } \right\}} |
| 1314 |
|
\] |
| 1289 |
– |
where |
| 1290 |
– |
\[ |
| 1291 |
– |
W(x) = U(x) - \sum\limits_{\alpha = 1}^N {\frac{{g_\alpha ^2 |
| 1292 |
– |
}}{{2m_\alpha w_\alpha ^2 }}} x^2 |
| 1293 |
– |
\] |
| 1315 |
|
Since the first two terms of the new Hamiltonian depend only on the |
| 1316 |
|
system coordinates, we can get the equations of motion for |
| 1317 |
|
Generalized Langevin Dynamics by Hamilton's equations |
| 1318 |
|
\ref{introEquation:motionHamiltonianCoordinate, |
| 1319 |
|
introEquation:motionHamiltonianMomentum}, |
| 1320 |
< |
\begin{align} |
| 1321 |
< |
\dot p &= - \frac{{\partial H}}{{\partial x}} |
| 1322 |
< |
&= m\ddot x |
| 1323 |
< |
&= - \frac{{\partial W(x)}}{{\partial x}} - \sum\limits_{\alpha = 1}^N {g_\alpha \left( {x_\alpha - \frac{{g_\alpha }}{{m_\alpha w_\alpha ^2 }}x} \right)} |
| 1324 |
< |
\label{introEquation:Lp5} |
| 1325 |
< |
\end{align} |
| 1326 |
< |
, and |
| 1327 |
< |
\begin{align} |
| 1328 |
< |
\dot p_\alpha &= - \frac{{\partial H}}{{\partial x_\alpha }} |
| 1329 |
< |
&= m\ddot x_\alpha |
| 1330 |
< |
&= \- m_\alpha w_\alpha ^2 \left( {x_\alpha - \frac{{g_\alpha}}{{m_\alpha w_\alpha ^2 }}x} \right) |
| 1331 |
< |
\end{align} |
| 1320 |
> |
\begin{equation} |
| 1321 |
> |
m\ddot x = - \frac{{\partial W(x)}}{{\partial x}} - |
| 1322 |
> |
\sum\limits_{\alpha = 1}^N {g_\alpha \left( {x_\alpha - |
| 1323 |
> |
\frac{{g_\alpha }}{{m_\alpha w_\alpha ^2 }}x} \right)}, |
| 1324 |
> |
\label{introEquation:coorMotionGLE} |
| 1325 |
> |
\end{equation} |
| 1326 |
> |
and |
| 1327 |
> |
\begin{equation} |
| 1328 |
> |
m\ddot x_\alpha = - m_\alpha w_\alpha ^2 \left( {x_\alpha - |
| 1329 |
> |
\frac{{g_\alpha }}{{m_\alpha w_\alpha ^2 }}x} \right). |
| 1330 |
> |
\label{introEquation:bathMotionGLE} |
| 1331 |
> |
\end{equation} |
| 1332 |
|
|
| 1333 |
< |
\subsection{\label{introSection:laplaceTransform}The Laplace Transform} |
| 1333 |
> |
In order to derive an equation for $x$, the dynamics of the bath |
| 1334 |
> |
variables $x_\alpha$ must be solved exactly first. As an integral |
| 1335 |
> |
transform which is particularly useful in solving linear ordinary |
| 1336 |
> |
differential equations, Laplace transform is the appropriate tool to |
| 1337 |
> |
solve this problem. The basic idea is to transform the difficult |
| 1338 |
> |
differential equations into simple algebra problems which can be |
| 1339 |
> |
solved easily. Then applying inverse Laplace transform, also known |
| 1340 |
> |
as the Bromwich integral, we can retrieve the solutions of the |
| 1341 |
> |
original problems. |
| 1342 |
|
|
| 1343 |
+ |
Let $f(t)$ be a function defined on $ [0,\infty ) $. The Laplace |
| 1344 |
+ |
transform of f(t) is a new function defined as |
| 1345 |
|
\[ |
| 1346 |
< |
L(x) = \int_0^\infty {x(t)e^{ - pt} dt} |
| 1346 |
> |
L(f(t)) \equiv F(p) = \int_0^\infty {f(t)e^{ - pt} dt} |
| 1347 |
|
\] |
| 1348 |
+ |
where $p$ is real and $L$ is called the Laplace Transform |
| 1349 |
+ |
Operator. Below are some important properties of Laplace transform |
| 1350 |
+ |
\begin{equation} |
| 1351 |
+ |
\begin{array}{c} |
| 1352 |
+ |
L(x + y) = L(x) + L(y) \\ |
| 1353 |
+ |
L(ax) = aL(x) \\ |
| 1354 |
+ |
L(\dot x) = pL(x) - px(0) \\ |
| 1355 |
+ |
L(\ddot x) = p^2 L(x) - px(0) - \dot x(0) \\ |
| 1356 |
+ |
L\left( {\int_0^t {g(t - \tau )h(\tau )d\tau } } \right) = G(p)H(p) \\ |
| 1357 |
+ |
\end{array} |
| 1358 |
+ |
\end{equation} |
| 1359 |
|
|
| 1360 |
+ |
Applying Laplace transform to the bath coordinates, we obtain |
| 1361 |
|
\[ |
| 1362 |
< |
L(x + y) = L(x) + L(y) |
| 1362 |
> |
\begin{array}{c} |
| 1363 |
> |
p^2 L(x_\alpha ) - px_\alpha (0) - \dot x_\alpha (0) = - \omega _\alpha ^2 L(x_\alpha ) + \frac{{g_\alpha }}{{\omega _\alpha }}L(x) \\ |
| 1364 |
> |
L(x_\alpha ) = \frac{{\frac{{g_\alpha }}{{\omega _\alpha }}L(x) + px_\alpha (0) + \dot x_\alpha (0)}}{{p^2 + \omega _\alpha ^2 }} \\ |
| 1365 |
> |
\end{array} |
| 1366 |
|
\] |
| 1367 |
< |
|
| 1367 |
> |
By the same way, the system coordinates become |
| 1368 |
|
\[ |
| 1369 |
< |
L(ax) = aL(x) |
| 1369 |
> |
\begin{array}{c} |
| 1370 |
> |
mL(\ddot x) = - \frac{1}{p}\frac{{\partial W(x)}}{{\partial x}} \\ |
| 1371 |
> |
- \sum\limits_{\alpha = 1}^N {\left\{ { - \frac{{g_\alpha ^2 }}{{m_\alpha \omega _\alpha ^2 }}\frac{p}{{p^2 + \omega _\alpha ^2 }}pL(x) - \frac{p}{{p^2 + \omega _\alpha ^2 }}g_\alpha x_\alpha (0) - \frac{1}{{p^2 + \omega _\alpha ^2 }}g_\alpha \dot x_\alpha (0)} \right\}} \\ |
| 1372 |
> |
\end{array} |
| 1373 |
|
\] |
| 1374 |
|
|
| 1375 |
+ |
With the help of some relatively important inverse Laplace |
| 1376 |
+ |
transformations: |
| 1377 |
|
\[ |
| 1378 |
< |
L(\dot x) = pL(x) - px(0) |
| 1379 |
< |
\] |
| 1380 |
< |
|
| 1381 |
< |
\[ |
| 1382 |
< |
L(\ddot x) = p^2 L(x) - px(0) - \dot x(0) |
| 1332 |
< |
\] |
| 1333 |
< |
|
| 1334 |
< |
\[ |
| 1335 |
< |
L\left( {\int_0^t {g(t - \tau )h(\tau )d\tau } } \right) = G(p)H(p) |
| 1336 |
< |
\] |
| 1337 |
< |
|
| 1338 |
< |
Some relatively important transformation, |
| 1339 |
< |
\[ |
| 1340 |
< |
L(\cos at) = \frac{p}{{p^2 + a^2 }} |
| 1341 |
< |
\] |
| 1342 |
< |
|
| 1343 |
< |
\[ |
| 1344 |
< |
L(\sin at) = \frac{a}{{p^2 + a^2 }} |
| 1345 |
< |
\] |
| 1346 |
< |
|
| 1347 |
< |
\[ |
| 1348 |
< |
L(1) = \frac{1}{p} |
| 1378 |
> |
\begin{array}{c} |
| 1379 |
> |
L(\cos at) = \frac{p}{{p^2 + a^2 }} \\ |
| 1380 |
> |
L(\sin at) = \frac{a}{{p^2 + a^2 }} \\ |
| 1381 |
> |
L(1) = \frac{1}{p} \\ |
| 1382 |
> |
\end{array} |
| 1383 |
|
\] |
| 1384 |
< |
|
| 1351 |
< |
First, the bath coordinates, |
| 1352 |
< |
\[ |
| 1353 |
< |
p^2 L(x_\alpha ) - px_\alpha (0) - \dot x_\alpha (0) = - \omega |
| 1354 |
< |
_\alpha ^2 L(x_\alpha ) + \frac{{g_\alpha }}{{\omega _\alpha |
| 1355 |
< |
}}L(x) |
| 1356 |
< |
\] |
| 1357 |
< |
\[ |
| 1358 |
< |
L(x_\alpha ) = \frac{{\frac{{g_\alpha }}{{\omega _\alpha }}L(x) + |
| 1359 |
< |
px_\alpha (0) + \dot x_\alpha (0)}}{{p^2 + \omega _\alpha ^2 }} |
| 1360 |
< |
\] |
| 1361 |
< |
Then, the system coordinates, |
| 1384 |
> |
, we obtain |
| 1385 |
|
\begin{align} |
| 1363 |
– |
mL(\ddot x) &= - \frac{1}{p}\frac{{\partial W(x)}}{{\partial x}} - |
| 1364 |
– |
\sum\limits_{\alpha = 1}^N {\left\{ {\frac{{\frac{{g_\alpha |
| 1365 |
– |
}}{{\omega _\alpha }}L(x) + px_\alpha (0) + \dot x_\alpha |
| 1366 |
– |
(0)}}{{p^2 + \omega _\alpha ^2 }} - \frac{{g_\alpha ^2 }}{{m_\alpha |
| 1367 |
– |
}}\omega _\alpha ^2 L(x)} \right\}} |
| 1368 |
– |
% |
| 1369 |
– |
&= - \frac{1}{p}\frac{{\partial W(x)}}{{\partial x}} - |
| 1370 |
– |
\sum\limits_{\alpha = 1}^N {\left\{ { - \frac{{g_\alpha ^2 }}{{m_\alpha \omega _\alpha ^2 }}\frac{p}{{p^2 + \omega _\alpha ^2 }}pL(x) |
| 1371 |
– |
- \frac{p}{{p^2 + \omega _\alpha ^2 }}g_\alpha x_\alpha (0) |
| 1372 |
– |
- \frac{1}{{p^2 + \omega _\alpha ^2 }}g_\alpha \dot x_\alpha (0)} \right\}} |
| 1373 |
– |
\end{align} |
| 1374 |
– |
Then, the inverse transform, |
| 1375 |
– |
|
| 1376 |
– |
\begin{align} |
| 1386 |
|
m\ddot x &= - \frac{{\partial W(x)}}{{\partial x}} - |
| 1387 |
|
\sum\limits_{\alpha = 1}^N {\left\{ {\left( { - \frac{{g_\alpha ^2 |
| 1388 |
|
}}{{m_\alpha \omega _\alpha ^2 }}} \right)\int_0^t {\cos (\omega |
| 1401 |
|
(\omega _\alpha t)} \right\}} |
| 1402 |
|
\end{align} |
| 1403 |
|
|
| 1404 |
+ |
Introducing a \emph{dynamic friction kernel} |
| 1405 |
|
\begin{equation} |
| 1406 |
+ |
\xi (t) = \sum\limits_{\alpha = 1}^N {\left( { - \frac{{g_\alpha ^2 |
| 1407 |
+ |
}}{{m_\alpha \omega _\alpha ^2 }}} \right)\cos (\omega _\alpha t)} |
| 1408 |
+ |
\label{introEquation:dynamicFrictionKernelDefinition} |
| 1409 |
+ |
\end{equation} |
| 1410 |
+ |
and \emph{a random force} |
| 1411 |
+ |
\begin{equation} |
| 1412 |
+ |
R(t) = \sum\limits_{\alpha = 1}^N {\left( {g_\alpha x_\alpha (0) |
| 1413 |
+ |
- \frac{{g_\alpha ^2 }}{{m_\alpha \omega _\alpha ^2 }}x(0)} |
| 1414 |
+ |
\right)\cos (\omega _\alpha t)} + \frac{{\dot x_\alpha |
| 1415 |
+ |
(0)}}{{\omega _\alpha }}\sin (\omega _\alpha t), |
| 1416 |
+ |
\label{introEquation:randomForceDefinition} |
| 1417 |
+ |
\end{equation} |
| 1418 |
+ |
the equation of motion can be rewritten as |
| 1419 |
+ |
\begin{equation} |
| 1420 |
|
m\ddot x = - \frac{{\partial W}}{{\partial x}} - \int_0^t {\xi |
| 1421 |
|
(t)\dot x(t - \tau )d\tau } + R(t) |
| 1422 |
|
\label{introEuqation:GeneralizedLangevinDynamics} |
| 1423 |
|
\end{equation} |
| 1424 |
< |
%where $ {\xi (t)}$ is friction kernel, $R(t)$ is random force and |
| 1425 |
< |
%$W$ is the potential of mean force. $W(x) = - kT\ln p(x)$ |
| 1424 |
> |
which is known as the \emph{generalized Langevin equation}. |
| 1425 |
> |
|
| 1426 |
> |
\subsubsection{\label{introSection:randomForceDynamicFrictionKernel}Random Force and Dynamic Friction Kernel} |
| 1427 |
> |
|
| 1428 |
> |
One may notice that $R(t)$ depends only on initial conditions, which |
| 1429 |
> |
implies it is completely deterministic within the context of a |
| 1430 |
> |
harmonic bath. However, it is easy to verify that $R(t)$ is totally |
| 1431 |
> |
uncorrelated to $x$ and $\dot x$, |
| 1432 |
|
\[ |
| 1433 |
< |
\xi (t) = \sum\limits_{\alpha = 1}^N {\left( { - \frac{{g_\alpha ^2 |
| 1434 |
< |
}}{{m_\alpha \omega _\alpha ^2 }}} \right)\cos (\omega _\alpha t)} |
| 1433 |
> |
\begin{array}{l} |
| 1434 |
> |
\left\langle {x(t)R(t)} \right\rangle = 0, \\ |
| 1435 |
> |
\left\langle {\dot x(t)R(t)} \right\rangle = 0. \\ |
| 1436 |
> |
\end{array} |
| 1437 |
|
\] |
| 1438 |
< |
For an infinite harmonic bath, we can use the spectral density and |
| 1439 |
< |
an integral over frequencies. |
| 1438 |
> |
This property is what we expect from a truly random process. As long |
| 1439 |
> |
as the model, which is gaussian distribution in general, chosen for |
| 1440 |
> |
$R(t)$ is a truly random process, the stochastic nature of the GLE |
| 1441 |
> |
still remains. |
| 1442 |
|
|
| 1443 |
+ |
%dynamic friction kernel |
| 1444 |
+ |
The convolution integral |
| 1445 |
|
\[ |
| 1446 |
< |
R(t) = \sum\limits_{\alpha = 1}^N {\left( {g_\alpha x_\alpha (0) |
| 1411 |
< |
- \frac{{g_\alpha ^2 }}{{m_\alpha \omega _\alpha ^2 }}x(0)} |
| 1412 |
< |
\right)\cos (\omega _\alpha t)} + \frac{{\dot x_\alpha |
| 1413 |
< |
(0)}}{{\omega _\alpha }}\sin (\omega _\alpha t) |
| 1446 |
> |
\int_0^t {\xi (t)\dot x(t - \tau )d\tau } |
| 1447 |
|
\] |
| 1448 |
< |
The random forces depend only on initial conditions. |
| 1448 |
> |
depends on the entire history of the evolution of $x$, which implies |
| 1449 |
> |
that the bath retains memory of previous motions. In other words, |
| 1450 |
> |
the bath requires a finite time to respond to change in the motion |
| 1451 |
> |
of the system. For a sluggish bath which responds slowly to changes |
| 1452 |
> |
in the system coordinate, we may regard $\xi(t)$ as a constant |
| 1453 |
> |
$\xi(t) = \Xi_0$. Hence, the convolution integral becomes |
| 1454 |
> |
\[ |
| 1455 |
> |
\int_0^t {\xi (t)\dot x(t - \tau )d\tau } = \xi _0 (x(t) - x(0)) |
| 1456 |
> |
\] |
| 1457 |
> |
and Equation \ref{introEuqation:GeneralizedLangevinDynamics} becomes |
| 1458 |
> |
\[ |
| 1459 |
> |
m\ddot x = - \frac{\partial }{{\partial x}}\left( {W(x) + |
| 1460 |
> |
\frac{1}{2}\xi _0 (x - x_0 )^2 } \right) + R(t), |
| 1461 |
> |
\] |
| 1462 |
> |
which can be used to describe dynamic caging effect. The other |
| 1463 |
> |
extreme is the bath that responds infinitely quickly to motions in |
| 1464 |
> |
the system. Thus, $\xi (t)$ can be taken as a $delta$ function in |
| 1465 |
> |
time: |
| 1466 |
> |
\[ |
| 1467 |
> |
\xi (t) = 2\xi _0 \delta (t) |
| 1468 |
> |
\] |
| 1469 |
> |
Hence, the convolution integral becomes |
| 1470 |
> |
\[ |
| 1471 |
> |
\int_0^t {\xi (t)\dot x(t - \tau )d\tau } = 2\xi _0 \int_0^t |
| 1472 |
> |
{\delta (t)\dot x(t - \tau )d\tau } = \xi _0 \dot x(t), |
| 1473 |
> |
\] |
| 1474 |
> |
and Equation \ref{introEuqation:GeneralizedLangevinDynamics} becomes |
| 1475 |
> |
\begin{equation} |
| 1476 |
> |
m\ddot x = - \frac{{\partial W(x)}}{{\partial x}} - \xi _0 \dot |
| 1477 |
> |
x(t) + R(t) \label{introEquation:LangevinEquation} |
| 1478 |
> |
\end{equation} |
| 1479 |
> |
which is known as the Langevin equation. The static friction |
| 1480 |
> |
coefficient $\xi _0$ can either be calculated from spectral density |
| 1481 |
> |
or be determined by Stokes' law for regular shaped particles.A |
| 1482 |
> |
briefly review on calculating friction tensor for arbitrary shaped |
| 1483 |
> |
particles is given in section \ref{introSection:frictionTensor}. |
| 1484 |
|
|
| 1485 |
|
\subsubsection{\label{introSection:secondFluctuationDissipation}The Second Fluctuation Dissipation Theorem} |
| 1486 |
< |
So we can define a new set of coordinates, |
| 1486 |
> |
|
| 1487 |
> |
Defining a new set of coordinates, |
| 1488 |
|
\[ |
| 1489 |
|
q_\alpha (t) = x_\alpha (t) - \frac{1}{{m_\alpha \omega _\alpha |
| 1490 |
|
^2 }}x(0) |
| 1491 |
< |
\] |
| 1492 |
< |
This makes |
| 1491 |
> |
\], |
| 1492 |
> |
we can rewrite $R(T)$ as |
| 1493 |
|
\[ |
| 1494 |
< |
R(t) = \sum\limits_{\alpha = 1}^N {g_\alpha q_\alpha (t)} |
| 1494 |
> |
R(t) = \sum\limits_{\alpha = 1}^N {g_\alpha q_\alpha (t)}. |
| 1495 |
|
\] |
| 1496 |
|
And since the $q$ coordinates are harmonic oscillators, |
| 1497 |
|
\[ |
| 1498 |
< |
\begin{array}{l} |
| 1498 |
> |
\begin{array}{c} |
| 1499 |
> |
\left\langle {q_\alpha ^2 } \right\rangle = \frac{{kT}}{{m_\alpha \omega _\alpha ^2 }} \\ |
| 1500 |
|
\left\langle {q_\alpha (t)q_\alpha (0)} \right\rangle = \left\langle {q_\alpha ^2 (0)} \right\rangle \cos (\omega _\alpha t) \\ |
| 1501 |
|
\left\langle {q_\alpha (t)q_\beta (0)} \right\rangle = \delta _{\alpha \beta } \left\langle {q_\alpha (t)q_\alpha (0)} \right\rangle \\ |
| 1502 |
+ |
\left\langle {R(t)R(0)} \right\rangle = \sum\limits_\alpha {\sum\limits_\beta {g_\alpha g_\beta \left\langle {q_\alpha (t)q_\beta (0)} \right\rangle } } \\ |
| 1503 |
+ |
= \sum\limits_\alpha {g_\alpha ^2 \left\langle {q_\alpha ^2 (0)} \right\rangle \cos (\omega _\alpha t)} \\ |
| 1504 |
+ |
= kT\xi (t) \\ |
| 1505 |
|
\end{array} |
| 1506 |
|
\] |
| 1507 |
< |
|
| 1435 |
< |
\begin{align} |
| 1436 |
< |
\left\langle {R(t)R(0)} \right\rangle &= \sum\limits_\alpha |
| 1437 |
< |
{\sum\limits_\beta {g_\alpha g_\beta \left\langle {q_\alpha |
| 1438 |
< |
(t)q_\beta (0)} \right\rangle } } |
| 1439 |
< |
% |
| 1440 |
< |
&= \sum\limits_\alpha {g_\alpha ^2 \left\langle {q_\alpha ^2 (0)} |
| 1441 |
< |
\right\rangle \cos (\omega _\alpha t)} |
| 1442 |
< |
% |
| 1443 |
< |
&= kT\xi (t) |
| 1444 |
< |
\end{align} |
| 1445 |
< |
|
| 1507 |
> |
Thus, we recover the \emph{second fluctuation dissipation theorem} |
| 1508 |
|
\begin{equation} |
| 1509 |
|
\xi (t) = \left\langle {R(t)R(0)} \right\rangle |
| 1510 |
< |
\label{introEquation:secondFluctuationDissipation} |
| 1510 |
> |
\label{introEquation:secondFluctuationDissipation}. |
| 1511 |
|
\end{equation} |
| 1512 |
+ |
In effect, it acts as a constraint on the possible ways in which one |
| 1513 |
+ |
can model the random force and friction kernel. |
| 1514 |
|
|
| 1515 |
|
\subsection{\label{introSection:frictionTensor} Friction Tensor} |
| 1516 |
|
Theoretically, the friction kernel can be determined using velocity |
| 1686 |
|
B_{ij} = \delta _{ij} \frac{I}{{6\pi \eta R}} + (1 - \delta _{ij} |
| 1687 |
|
)T_{ij} |
| 1688 |
|
\] |
| 1689 |
< |
where \delta _{ij} is Kronecker delta function. Inverting matrix |
| 1689 |
> |
where $\delta _{ij}$ is Kronecker delta function. Inverting matrix |
| 1690 |
|
$B$, we obtain |
| 1691 |
|
|
| 1692 |
|
\[ |
| 1730 |
|
Form Equation \ref{introEquation:ResistanceTensorArbitraryOrigin}, |
| 1731 |
|
we can easily find out that the translational resistance tensor is |
| 1732 |
|
origin independent, while the rotational resistance tensor and |
| 1733 |
< |
translation-rotation coupling resistance tensor do depend on the |
| 1733 |
> |
translation-rotation coupling resistance tensor depend on the |
| 1734 |
|
origin. Given resistance tensor at an arbitrary origin $O$, and a |
| 1735 |
|
vector ,$r_{OP}(x_{OP}, y_{OP}, z_{OP})$, from $O$ to $P$, we can |
| 1736 |
|
obtain the resistance tensor at $P$ by |
