Add draft abstract and conclusion.

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Janita Willumsen 2023-12-22 13:19:20 +01:00
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6 changed files with 68 additions and 5 deletions

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year = {2020}
}
@misc{mit:2004:physics,
author = {Sen-ben Liao and Peter Dourmashkin and John W. Belcher},
title = {Course notes in Physics 8.02 at MIT},
year = {2004},
url = {https://web.mit.edu/8.02t/www/802TEAL3D/visualizations/coursenotes/modules/guide14.pdf},
urldate = {2023-12-22}
}
@misc{britannica:1999:light,
author = {The Editors of Encyclopaedia Britannica},
title = {Light},

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@ -88,7 +88,7 @@
\noaffiliation % ignore this, but keep it.
% Abstract
% \subfile{sections/abstract}
\subfile{sections/abstract}
\maketitle

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\begin{document}
\begin{abstract}
We have simulated the two-dimensional time-dependent Schrödinger equation, to study
variations of the double-slit experiment. To solve the partial differential equations
we have applied the Crank-Nicolson scheme in 2+1 dimensions, to derive a discretized
equation. In addition, we have used Dirichlet boundary conditions to express the
equation in matrix form and solve it using the sparse matrix solver \verb|superlu|.
Our implementation, and choice of solver method, resulted in conserved total
probability $\sum_{\ivec, \jvec} p_{\ivec, \jvec}^{n}=1$ for both the single and
double slit setup. To illustrate the time evolution of the probability function,
we created colormap plots at time steps $t = [0, 0.001, 0.002]$. We also included
separate plots for each time step of Re$(u_{\ivec, \jvec})$ and Im$(u_{\ivec, \jvec})$.
In addition, we determined the normalized particle detection probability $p(y \ | \ x=0.8, t=0.002)$,
for single-, double- and triple-slit.
\end{abstract}
\end{document}

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@ -2,6 +2,24 @@
\begin{document}
\section{Conclusion}\label{sec:conclusion}
% Rewrite this section to differ from the abstract
We have simulated the two-dimensional time-dependent Schrödinger equation, to study
variations of the double-slit experiment. To solve the partial differential equations
we have applied the Crank-Nicolson scheme in 2+1 dimensions, and derived a discretized
equation. In addition, we have used Dirichlet boundary conditions to express the
equation in matrix form and solve it using the sparse matrix solver \verb|superlu|.
Our implementation, and choice of solver method, resulted in conserved total
probability $\sum_{\ivec, \jvec} p_{\ivec, \jvec}^{n}=1$ for both the single and
double slit setup.
To illustrate the time evolution of the probability function $p_{\ivec, \jvec}^{n} = u_{\ivec, \jvec}^{n*} u_{\ivec, \jvec}^{n}$,
we created colormap plots at time steps $t = [0, 0.001, 0.002]$. Since we are working
with complex numbers, we included separate plots for each time step of Re$(u_{\ivec, \jvec})$
and Im$(u_{\ivec, \jvec})$.
% We observed something...
In addition, we determined the normalized particle detection probability $p(y \ | \ x=0.8, t=0.002)$,
for single-, double- and triple-slit.
% We observed something here as well...
\end{document}

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@ -85,9 +85,35 @@ can be found in Appendix \ref{ap:crank_nicolson}.
\subsection{The double-slit experiment}\label{ssec:double_slit} %
Thomas Young first performed the double-slit experiment in 1801 to demonstrate the
principle of interference of light \cite{britannica:2023:young}, while postulating
light as waves rather than particles. The double-slit experiment gives a diffraction
pattern, where constructive interference of light result in bright spots, and destructive
interference result in dark spots.
light as waves rather than particles. The double-slit experiment result in a diffraction
pattern on a detector screen, where constructive interference of light result in
bright spots, and destructive interference result in dark spots as showed in Figure
\ref{fig:youngs_double_slit}.
\begin{figure}
\centering
\includegraphics[width=\linewidth]{images/youngs_double_slit.pdf}
\caption{The setup of Thomas Young's double slit experiment, where $S_{0}$ denotes
the light source, $S_{1}$ and $S_{2}$ denotes the slits in the wall.}
\label{fig:youngs_double_slit}
\end{figure}
After the wave passes through the two slits, the pattern observed is determined by
the path difference determined by
\begin{align*}
\delta = d \sin (\theta) = m \lambda \ ,
\end{align*}
where $\lambda$ is the wavelength and $m$ is called the order number. $d$ is the
distance between the center of the two slits, assuming that the distance between
the wall and the detector screen $L >> \delta$ \cite[p. 6]{mit:2004:physics}. In
this case, we observe constructive interference when
\begin{align*}
\delta = m \lambda && m = 0, \pm 1, \pm 2 \dots \ ,
\end{align*}
and destructive interference when
\begin{align*}
\delta = (m + \frac{1}{2}) \lambda && m = 0, \pm 1, \pm 2 \dots \ ,
\end{align*}
% Something about Heisenberg uncertainty principle
\subsection{Implementation}\label{ssec:implementation} %