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Add qec meeting results

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Andreas Tsouchlos
2026-03-28 10:35:43 +01:00
parent 631eeed5cd
commit 7db31aec85
3 changed files with 127 additions and 52 deletions
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160
src/qec-meeting-presentation/main.tex
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@@ -236,7 +236,7 @@ decorations.pathreplacing, calc}
\label{sec:Current Results}
\begin{frame}
\frametitle{An ``Upper Bound'' on the Performance}
\frametitle{An ``Upper Bound'' on the Performance Gain}
\begin{minipage}{0.65\textwidth}
\begin{figure}[H]
@@ -257,9 +257,10 @@ decorations.pathreplacing, calc}
xticklabel style={/pgf/number format/fixed},
xticklabel style={/pgf/number format/precision=4},
scaled x ticks=false,
grid,
grid=both,
xtick={0.001,0.0015,...,0.004},
xmin=0.001, xmax=0.004,
ymin=1e-2, ymax=1,
]
\addplot+[NavyBlue, mark=none, line width=1pt]
@@ -300,58 +301,117 @@ decorations.pathreplacing, calc}
\begin{frame}
\frametitle{Soft- vs. Hard-Information Decoding Behavior I}
\begin{minipage}{0.65\textwidth}
\begin{figure}[H]
% \centering
\hspace*{-8mm}
\begin{tikzpicture}
\begin{axis}[
width=10cm,
height=8cm,
ymode=log,
ylabel={LER},
xlabel={Physical error rate},
legend pos=south east,
legend style={
cells={anchor=west},
cells={align=left},
},
xticklabel style={/pgf/number format/fixed},
xticklabel style={/pgf/number format/precision=4},
scaled x ticks=false,
grid=both,
xtick={0.001,0.0015,...,0.004},
xmin=0.001, xmax=0.004,
ymin=1e-2, ymax=1,
]
\addplot+[BurntOrange, mark=none,
line width=1pt]
table[col sep=comma, x=p, y=LER_soft]
{res/hard_vs_soft_spa.csv};
\addlegendentry{Soft info - SPA}
\addplot+[BurntOrange, densely dashed, mark=none,
line width=1pt]
table[col sep=comma, x=p, y=LER_hard]
{res/hard_vs_soft_spa.csv};
\addlegendentry{Hard info - SPA}
\addplot+[NavyBlue, mark=none, line width=1pt]
table[col sep=comma, x=p, y=LER_soft]
{res/hard_vs_soft_min_sum.csv};
\addlegendentry{Soft info - Min-Sum}
\addplot+[NavyBlue, densely dashed, mark=none,
line width=1pt]
table[col sep=comma, x=p, y=LER_hard]
{res/hard_vs_soft_min_sum.csv};
\addlegendentry{Hard info - Min-Sum}
\end{axis}
\end{tikzpicture}
\end{figure}
\end{minipage}%
\begin{minipage}{0.35\textwidth}
\begin{itemize}
\item \red{Soft vs hard for min sum and spa (4 plots)}
\item \red{Different window sizes}
\item $[[144,12,12]]$ BB code
\item $n_\text{rounds} = 12$
\item $W=3$, $F=1$
\end{itemize}
\end{minipage}
% \begin{itemize}
% \item \red{Soft vs hard for min sum and spa (4 plots)}
% \item \red{Different window sizes}
% \end{itemize}
\end{frame}
\begin{frame}
\frametitle{Soft- vs. Hard-Information Decoding Behavior II}
\begin{itemize}
\item \red{Comparison of numbers of iterations for soft vs hard}
\item \red{Convergence analysis}
\end{itemize}
\end{frame}
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
\section{Future Work and Open Questions}
\label{sec:Future Work and Open Questions}
\begin{frame}
\frametitle{Future Work}
\vspace*{15mm}
\begin{itemize}
\item Look at behavior during iterations
\item Move from BP to BPGD
\vspace{15mm}
\item Q: Theoretically rigorous proof for the
``window-friendly'' structure of the detector error matrix?
\item Q: Min-sum seems to perform better than SPA? \red{Make
sure this question even makes sense}
\end{itemize}
\end{frame}
% TODOs
% - Whole vs windowed for min sum and spa
% - Basic implementation
% - Choose parameters (e.g., window sizes)
% - soft vs hard for min sum and spa (4 plots)
% - Basic implementation
% - Choose parameters (e.g., window sizes)
% - Comparison of numbers of iterations for soft vs hard
% - Basic implementation (more or less done)
% - Choose parameters
% - Convergence analysis
% - Basic implementation (more or less done)
% - Choose parameters
% - Make sure min sum vs spa question makes sense
% - Think of a few words for each slide (and take notes)
% \begin{frame}
% \frametitle{Soft- vs. Hard-Information Decoding Behavior II}
%
% \begin{itemize}
% \item \red{Comparison of numbers of iterations for soft vs hard}
% \item \red{Convergence analysis}
% \end{itemize}
% \end{frame}
%
% %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% \section{Future Work and Open Questions}
% \label{sec:Future Work and Open Questions}
%
% \begin{frame}
% \frametitle{Future Work}
%
% \vspace*{15mm}
%
% \begin{itemize}
% \item Look at behavior during iterations
% \item Move from BP to BPGD
%
% \vspace{15mm}
%
% \item Q: Theoretically rigorous proof for the
% ``window-friendly'' structure of the detector error matrix?
% \item Q: Min-sum seems to perform better than SPA? \red{Make
% sure this question even makes sense}
% \end{itemize}
% \end{frame}
%
% % TODOs
% % - Whole vs windowed for min sum and spa
% % - Basic implementation
% % - Choose parameters (e.g., window sizes)
% % - soft vs hard for min sum and spa (4 plots)
% % - Basic implementation
% % - Choose parameters (e.g., window sizes)
% % - Comparison of numbers of iterations for soft vs hard
% % - Basic implementation (more or less done)
% % - Choose parameters
% % - Convergence analysis
% % - Basic implementation (more or less done)
% % - Choose parameters
% % - Make sure min sum vs spa question makes sense
% % - Think of a few words for each slide (and take notes)
\end{document}

8
src/qec-meeting-presentation/res/hard_vs_soft_min_sum.csv Normal file
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@@ -0,0 +1,8 @@
p,LER_hard,LER_soft
0.001,0.08,0.028
0.0015,0.174,0.076
0.002,0.348,0.218
0.0025,0.54,0.38
0.003,0.716,0.564
0.0035,0.862,0.75
0.004,0.948,0.906
1 p LER_hard LER_soft
2 0.001 0.08 0.028
3 0.0015 0.174 0.076
4 0.002 0.348 0.218
5 0.0025 0.54 0.38
6 0.003 0.716 0.564
7 0.0035 0.862 0.75
8 0.004 0.948 0.906

7
src/qec-meeting-presentation/res/hard_vs_soft_spa.csv Normal file
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@@ -0,0 +1,7 @@
p,LER_hard,LER_soft
0.001,0.098,0.038
0.0015,0.174,0.11
0.002,0.394,0.268
0.0025,0.536,0.376
0.003,0.688,0.574
0.0035,0.822,0.744
1 p LER_hard LER_soft
2 0.001 0.098 0.038
3 0.0015 0.174 0.11
4 0.002 0.394 0.268
5 0.0025 0.536 0.376
6 0.003 0.688 0.574
7 0.0035 0.822 0.744