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@ -1397,6 +1397,9 @@ gfortran hydrogen.f90 qmc_stats.f90 qmc_uniform.f90 -o qmc_uniform
step such that the acceptance rate is close to 0.5 is a good step such that the acceptance rate is close to 0.5 is a good
compromise for the current problem. compromise for the current problem.
NOTE: below, we use the symbol dt for dL for reasons which will
become clear later.
*** Exercise *** Exercise
@ -2080,11 +2083,13 @@ gfortran hydrogen.f90 qmc_stats.f90 vmc_metropolis.f90 -o vmc_metropolis
Consider the time-dependent Schrödinger equation: Consider the time-dependent Schrödinger equation:
\[ \[
i\frac{\partial \Psi(\mathbf{r},t)}{\partial t} = \hat{H} \Psi(\mathbf{r},t)\,. i\frac{\partial \Psi(\mathbf{r},t)}{\partial t} = (\hat{H} -E_T) \Psi(\mathbf{r},t)\,.
\] \]
where we introduced a shift in the energy, $E_T$, which will come useful below.
We can expand a given starting wave function, $\Psi(\mathbf{r},0)$, in the basis of the eigenstates We can expand a given starting wave function, $\Psi(\mathbf{r},0)$, in the basis of the eigenstates
of the time-independent Hamiltonian: of the time-independent Hamiltonian, $\Phi_k$, with energies $E_k$:
\[ \[
\Psi(\mathbf{r},0) = \sum_k a_k\, \Phi_k(\mathbf{r}). \Psi(\mathbf{r},0) = \sum_k a_k\, \Phi_k(\mathbf{r}).
@ -2093,36 +2098,48 @@ gfortran hydrogen.f90 qmc_stats.f90 vmc_metropolis.f90 -o vmc_metropolis
The solution of the Schrödinger equation at time $t$ is The solution of the Schrödinger equation at time $t$ is
\[ \[
\Psi(\mathbf{r},t) = \sum_k a_k \exp \left( -i\, E_k\, t \right) \Phi_k(\mathbf{r}). \Psi(\mathbf{r},t) = \sum_k a_k \exp \left( -i\, (E_k-E_T)\, t \right) \Phi_k(\mathbf{r}).
\] \]
Now, if we replace the time variable $t$ by an imaginary time variable Now, if we replace the time variable $t$ by an imaginary time variable
$\tau=i\,t$, we obtain $\tau=i\,t$, we obtain
\[ \[
-\frac{\partial \psi(\mathbf{r}, \tau)}{\partial \tau} = \hat{H} \psi(\mathbf{r}, \tau) -\frac{\partial \psi(\mathbf{r}, \tau)}{\partial \tau} = (\hat{H} -E_T) \psi(\mathbf{r}, \tau)
\] \]
where $\psi(\mathbf{r},\tau) = \Psi(\mathbf{r},-i\,)$ where $\psi(\mathbf{r},\tau) = \Psi(\mathbf{r},-i\,)$
and and
\[ \begin{eqnarray*}
\psi(\mathbf{r},\tau) = \sum_k a_k \exp( -E_k\, \tau) \phi_k(\mathbf{r}). \psi(\mathbf{r},\tau) &=& \sum_k a_k \exp( -E_k\, \tau) \phi_k(\mathbf{r})\\
\] &=& \exp(-(E_0-E_T)\, \tau)\sum_k a_k \exp( -(E_k-E_0)\, \tau) \phi_k(\mathbf{r})\,.
\begin{eqnarray*}
For large positive values of $\tau$, $\psi$ is dominated by the For large positive values of $\tau$, $\psi$ is dominated by the
$k=0$ term, namely the lowest eigenstate. $k=0$ term, namely, the lowest eigenstate. If we adjust $E_T$ to the running estimate of $E_0$,
So we can expect that simulating the differetial equation in we can expect that simulating the differetial equation in
imaginary time will converge to the exact ground state of the imaginary time will converge to the exact ground state of the
system. system.
** Diffusion and branching ** Diffusion and branching
The [[https://en.wikipedia.org/wiki/Diffusion_equation][diffusion equation]] of particles is given by The imaginary-time Schrödinger equation can be explicitly written in terms of the kinetic and
potential energies as
\[
\frac{\partial \psi(\mathbf{r}, \tau)}{\partial \tau} = \left(\frac{1}{2}\Delta - [V(\mathbf{r}) -E_T]\right) \psi(\mathbf{r}, \tau)\,.
\]
We can simulate this differential equation as a diffusion-branching process.
To this this, recall that the [[https://en.wikipedia.org/wiki/Diffusion_equation][diffusion equation]] of particles is given by
\[ \[
\frac{\partial \phi(\mathbf{r},t)}{\partial t} = D\, \Delta \phi(\mathbf{r},t). \frac{\partial \phi(\mathbf{r},t)}{\partial t} = D\, \Delta \phi(\mathbf{r},t).
\] \]
The [[https://en.wikipedia.org/wiki/Reaction_rate][rate of reaction]] $v$ is the speed at which a chemical reaction Furthermore, the [[https://en.wikipedia.org/wiki/Reaction_rate][rate of reaction]] $v$ is the speed at which a chemical reaction
takes place. In a solution, the rate is given as a function of the takes place. In a solution, the rate is given as a function of the
concentration $[A]$ by concentration $[A]$ by
@ -2139,7 +2156,9 @@ gfortran hydrogen.f90 qmc_stats.f90 vmc_metropolis.f90 -o vmc_metropolis
- a rate equation for the potential. - a rate equation for the potential.
The diffusion equation can be simulated by a Brownian motion: The diffusion equation can be simulated by a Brownian motion:
\[ \mathbf{r}_{n+1} = \mathbf{r}_{n} + \sqrt{\delta t}\, \chi \] \[ \mathbf{r}_{n+1} = \mathbf{r}_{n} + \sqrt{\delta t}\, \chi \]
where $\chi$ is a Gaussian random variable, and the rate equation where $\chi$ is a Gaussian random variable, and the rate equation
can be simulated by creating or destroying particles over time (a can be simulated by creating or destroying particles over time (a
so-called branching process). so-called branching process).
@ -2150,7 +2169,7 @@ gfortran hydrogen.f90 qmc_stats.f90 vmc_metropolis.f90 -o vmc_metropolis
** Importance sampling ** Importance sampling
In a molecular system, the potential is far from being constant, In a molecular system, the potential is far from being constant
and diverges at inter-particle coalescence points. Hence, when the and diverges at inter-particle coalescence points. Hence, when the
rate equation is simulated, it results in very large fluctuations rate equation is simulated, it results in very large fluctuations
in the numbers of particles, making the calculations impossible in in the numbers of particles, making the calculations impossible in