Add draft abstract and conclusion.
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latex/images/youngs_double_slit.pdf
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latex/images/youngs_double_slit.pdf
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@ -8,6 +8,14 @@
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year = {2020}
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}
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@misc{mit:2004:physics,
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author = {Sen-ben Liao and Peter Dourmashkin and John W. Belcher},
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title = {Course notes in Physics 8.02 at MIT},
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year = {2004},
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url = {https://web.mit.edu/8.02t/www/802TEAL3D/visualizations/coursenotes/modules/guide14.pdf},
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urldate = {2023-12-22}
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}
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@misc{britannica:1999:light,
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author = {The Editors of Encyclopaedia Britannica},
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title = {Light},
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@ -88,7 +88,7 @@
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\noaffiliation % ignore this, but keep it.
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% Abstract
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% \subfile{sections/abstract}
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\subfile{sections/abstract}
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\maketitle
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@ -2,6 +2,17 @@
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\begin{document}
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\begin{abstract}
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We have simulated the two-dimensional time-dependent Schrödinger equation, to study
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variations of the double-slit experiment. To solve the partial differential equations
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we have applied the Crank-Nicolson scheme in 2+1 dimensions, to derive a discretized
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equation. In addition, we have used Dirichlet boundary conditions to express the
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equation in matrix form and solve it using the sparse matrix solver \verb|superlu|.
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Our implementation, and choice of solver method, resulted in conserved total
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probability $\sum_{\ivec, \jvec} p_{\ivec, \jvec}^{n}=1$ for both the single and
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double slit setup. To illustrate the time evolution of the probability function,
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we created colormap plots at time steps $t = [0, 0.001, 0.002]$. We also included
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separate plots for each time step of Re$(u_{\ivec, \jvec})$ and Im$(u_{\ivec, \jvec})$.
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In addition, we determined the normalized particle detection probability $p(y \ | \ x=0.8, t=0.002)$,
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for single-, double- and triple-slit.
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\end{abstract}
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\end{document}
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@ -2,6 +2,24 @@
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\begin{document}
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\section{Conclusion}\label{sec:conclusion}
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% Rewrite this section to differ from the abstract
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We have simulated the two-dimensional time-dependent Schrödinger equation, to study
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variations of the double-slit experiment. To solve the partial differential equations
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we have applied the Crank-Nicolson scheme in 2+1 dimensions, and derived a discretized
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equation. In addition, we have used Dirichlet boundary conditions to express the
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equation in matrix form and solve it using the sparse matrix solver \verb|superlu|.
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Our implementation, and choice of solver method, resulted in conserved total
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probability $\sum_{\ivec, \jvec} p_{\ivec, \jvec}^{n}=1$ for both the single and
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double slit setup.
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To illustrate the time evolution of the probability function $p_{\ivec, \jvec}^{n} = u_{\ivec, \jvec}^{n*} u_{\ivec, \jvec}^{n}$,
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we created colormap plots at time steps $t = [0, 0.001, 0.002]$. Since we are working
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with complex numbers, we included separate plots for each time step of Re$(u_{\ivec, \jvec})$
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and Im$(u_{\ivec, \jvec})$.
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% We observed something...
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In addition, we determined the normalized particle detection probability $p(y \ | \ x=0.8, t=0.002)$,
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for single-, double- and triple-slit.
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% We observed something here as well...
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\end{document}
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@ -85,9 +85,35 @@ can be found in Appendix \ref{ap:crank_nicolson}.
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\subsection{The double-slit experiment}\label{ssec:double_slit} %
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Thomas Young first performed the double-slit experiment in 1801 to demonstrate the
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principle of interference of light \cite{britannica:2023:young}, while postulating
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light as waves rather than particles. The double-slit experiment gives a diffraction
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pattern, where constructive interference of light result in bright spots, and destructive
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interference result in dark spots.
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light as waves rather than particles. The double-slit experiment result in a diffraction
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pattern on a detector screen, where constructive interference of light result in
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bright spots, and destructive interference result in dark spots as showed in Figure
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\ref{fig:youngs_double_slit}.
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\begin{figure}
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\centering
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\includegraphics[width=\linewidth]{images/youngs_double_slit.pdf}
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\caption{The setup of Thomas Young's double slit experiment, where $S_{0}$ denotes
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the light source, $S_{1}$ and $S_{2}$ denotes the slits in the wall.}
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\label{fig:youngs_double_slit}
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\end{figure}
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After the wave passes through the two slits, the pattern observed is determined by
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the path difference determined by
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\begin{align*}
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\delta = d \sin (\theta) = m \lambda \ ,
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\end{align*}
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where $\lambda$ is the wavelength and $m$ is called the order number. $d$ is the
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distance between the center of the two slits, assuming that the distance between
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the wall and the detector screen $L >> \delta$ \cite[p. 6]{mit:2004:physics}. In
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this case, we observe constructive interference when
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\begin{align*}
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\delta = m \lambda && m = 0, \pm 1, \pm 2 \dots \ ,
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\end{align*}
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and destructive interference when
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\begin{align*}
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\delta = (m + \frac{1}{2}) \lambda && m = 0, \pm 1, \pm 2 \dots \ ,
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\end{align*}
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% Something about Heisenberg uncertainty principle
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\subsection{Implementation}\label{ssec:implementation} %
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