Add one-shot results to res folder and annotate sliding window fig
This commit is contained in:
@@ -88,18 +88,39 @@ sp="/-\|"
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# done
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# done
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# done
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# done
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# done
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# done
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#
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# # Copy BPGD over max iter. results
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#
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# echo -e "\rCopying BPGD over max. iter. results..."
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# echo -n ' '
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# for p in 0.001 0.0025 0.004; do
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# for pass_soft_info in "True" "False"; do
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# for F in 1 2 3; do
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# for W in 3 4 5; do
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# SRC_PATH="${BASE_PATH}+rust_exp=max_iter_bpgd,decoder.class_name=WindowingSyndromeSpaGdDecoder,decoder.pass_soft_info=${pass_soft_info},simulation.phy_err_rate=${p},system.F=${F},system.W=${W}/"
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# LATEST_RESULTS_DIR=$(ls -t ${SRC_PATH} | head -1)
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# SRC_FILE="${SRC_PATH}/${LATEST_RESULTS_DIR}/LERs.csv"
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# DEST_DIR="res/sim/max_iter/WindowingSyndromeSpaGdDecoder/p_${p}/pass_soft_info_${pass_soft_info}/F_${F}/W_${W}"
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# mkdir -p ${DEST_DIR}
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# DEST_FILE="${DEST_DIR}/LERs.csv"
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# cp ${SRC_FILE} ${DEST_FILE}
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# post_process_LERs ${DEST_FILE}
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# printf "\b${sp:i++%${#sp}:1}"
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# done
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# done
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# done
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# done
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# Copy BPGD over max iter. results
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# Copy BP over max iter. results
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echo -e "\rCopying BPGD over max. iter. results..."
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echo -e "\rCopying one-shot simulation results..."
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echo -n ' '
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echo -n ' '
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for p in 0.001 0.0025 0.004; do
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for decoder in "SyndromeMinSumDecoder" "SyndromeSpaDecoder" "SyndromeSpaGdDecoder"; do
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for pass_soft_info in "True" "False"; do
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for max_iter in 32 200 5000; do
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for F in 1 2 3; do
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SRC_PATH="${BASE_PATH}+rust_exp=whole_bp_bpgd,decoder.class_name=${decoder},decoder.max_iter=${max_iter},system.F=1,system.W=5/"
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for W in 3 4 5; do
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SRC_PATH="${BASE_PATH}+rust_exp=max_iter_bpgd,decoder.class_name=WindowingSyndromeSpaGdDecoder,decoder.pass_soft_info=${pass_soft_info},simulation.phy_err_rate=${p},system.F=${F},system.W=${W}/"
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LATEST_RESULTS_DIR=$(ls -t ${SRC_PATH} | head -1)
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LATEST_RESULTS_DIR=$(ls -t ${SRC_PATH} | head -1)
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SRC_FILE="${SRC_PATH}/${LATEST_RESULTS_DIR}/LERs.csv"
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SRC_FILE="${SRC_PATH}/${LATEST_RESULTS_DIR}/LERs.csv"
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DEST_DIR="res/sim/max_iter/WindowingSyndromeSpaGdDecoder/p_${p}/pass_soft_info_${pass_soft_info}/F_${F}/W_${W}"
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DEST_DIR="res/sim/one-shot/${decoder}/max_iter_${max_iter}/"
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mkdir -p ${DEST_DIR}
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mkdir -p ${DEST_DIR}
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DEST_FILE="${DEST_DIR}/LERs.csv"
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DEST_FILE="${DEST_DIR}/LERs.csv"
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cp ${SRC_FILE} ${DEST_FILE}
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cp ${SRC_FILE} ${DEST_FILE}
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@@ -107,5 +128,3 @@ for p in 0.001 0.0025 0.004; do
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printf "\b${sp:i++%${#sp}:1}"
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printf "\b${sp:i++%${#sp}:1}"
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done
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done
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done
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done
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done
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done
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@@ -1709,7 +1709,7 @@
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\visible<3->{
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\visible<3->{
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\hspace*{21mm}%
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\hspace*{21mm}%
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\begin{tikzpicture}
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\begin{tikzpicture}
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\draw[decorate, decoration={brace, amplitude=10pt}]
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\draw[decorate, decoration={brace, amplitude=10pt}, line width=1pt]
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(0,0) -- (6,0) node[midway, above=4mm] {Commit region};
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(0,0) -- (6,0) node[midway, above=4mm] {Commit region};
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\end{tikzpicture}
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\end{tikzpicture}
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}
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}
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@@ -1730,6 +1730,24 @@
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\end{figure}
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\end{figure}
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}
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}
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\vspace*{-50.85mm}
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\visible<4->{
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\hspace*{-8mm}%
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\begin{tikzpicture}
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\draw[{Latex}-{Latex}, line width=1pt] (0,0) -- (0,1);
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\draw[line width=1pt] (-1mm,0) -- (3mm,0);
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\draw[line width=1pt] (-1mm,1) -- (3mm,1);
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\node[left] at (-2mm,0.5) {$\sim W$};
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\draw[{Latex}-{Latex}, line width=1pt] (11.5cm,0.4) -- (11.5cm,1);
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\draw[line width=1pt] (11.5cm,0.98) -- (11.5cm,1.5);
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\node[above] at (11.5cm,1.5) {$\sim F$};
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\end{tikzpicture}
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}
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\vspace*{27mm}
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\begin{itemize}
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\begin{itemize}
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\visible<2->{
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\visible<2->{
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\item Split \ac{dem} into \schlagwort{overlapping
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\item Split \ac{dem} into \schlagwort{overlapping
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@@ -1839,6 +1857,14 @@
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}
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}
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\temp
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\temp
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}
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}
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\addplot+[mark=x, line width=2pt,
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densely dashed, black]
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table[
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col sep=comma, x=physical_p,
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y=LER_per_round,
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]
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{res/sim/one-shot/SyndromeMinSumDecoder/max_iter_32/LERs.csv};
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\end{axis}
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\end{axis}
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\end{tikzpicture}
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\end{tikzpicture}
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\end{figure}
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\end{figure}
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@@ -1906,7 +1932,8 @@
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{3/kit-red,4/kit-blue,5/kit-orange} {
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{3/kit-red,4/kit-blue,5/kit-orange} {
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\edef\temp{\noexpand
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\edef\temp{\noexpand
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\addplot+[mark=o, line width=2pt,
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\addplot+[mark=o, line width=2pt,
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densely dashed, gray, opacity=0.4, forget plot]
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densely dashed, gray, opacity=0.4,
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forget plot]
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table[
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table[
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col sep=comma, x=physical_p,
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col sep=comma, x=physical_p,
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y=LER_per_round,
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y=LER_per_round,
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@@ -2041,7 +2068,8 @@
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{3/kit-red,4/kit-blue,5/kit-orange} {
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{3/kit-red,4/kit-blue,5/kit-orange} {
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\edef\temp{\noexpand
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\edef\temp{\noexpand
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\addplot+[mark=o, line width=2pt,
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\addplot+[mark=o, line width=2pt,
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densely dashed, gray, opacity=0.4, forget plot]
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densely dashed, gray, opacity=0.4,
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forget plot]
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table[
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table[
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col sep=comma, x=physical_p,
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col sep=comma, x=physical_p,
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y=LER_per_round,
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y=LER_per_round,
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@@ -2326,7 +2354,8 @@
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\edef\temp{\noexpand
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\edef\temp{\noexpand
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\addplot+[mark=o, line width=2pt,
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\addplot+[mark=o, line width=2pt,
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forget plot, densely dashed, gray, opacity=0.4]
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forget plot, densely dashed, gray,
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opacity=0.4]
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table[
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table[
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col sep=comma, x=physical_p,
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col sep=comma, x=physical_p,
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y=LER_per_round,
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y=LER_per_round,
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@@ -2429,7 +2458,8 @@
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\edef\temp{\noexpand
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\edef\temp{\noexpand
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\addplot+[mark=o, line width=2pt,
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\addplot+[mark=o, line width=2pt,
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forget plot, densely dashed, gray, opacity=0.4]
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forget plot, densely dashed, gray,
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opacity=0.4]
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table[
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table[
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col sep=comma, x=physical_p,
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col sep=comma, x=physical_p,
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y=LER_per_round,
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y=LER_per_round,
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@@ -2767,7 +2797,8 @@
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{3/kit-red,4/kit-blue,5/kit-orange} {
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{3/kit-red,4/kit-blue,5/kit-orange} {
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\edef\temp{\noexpand
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\edef\temp{\noexpand
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\addplot+[mark=o, line width=2pt,
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\addplot+[mark=o, line width=2pt,
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densely dashed, gray, opacity=0.4, forget plot]
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densely dashed, gray, opacity=0.4,
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forget plot]
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table[
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table[
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col sep=comma, x=physical_p,
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col sep=comma, x=physical_p,
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y=LER_per_round,
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y=LER_per_round,
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@@ -2902,7 +2933,8 @@
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{3/kit-red,4/kit-blue,5/kit-orange} {
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{3/kit-red,4/kit-blue,5/kit-orange} {
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\edef\temp{\noexpand
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\edef\temp{\noexpand
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\addplot+[mark=o, line width=2pt,
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\addplot+[mark=o, line width=2pt,
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densely dashed, gray, opacity=0.4, forget plot]
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densely dashed, gray, opacity=0.4,
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forget plot]
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table[
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table[
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col sep=comma, x=physical_p,
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col sep=comma, x=physical_p,
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y=LER_per_round,
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y=LER_per_round,
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@@ -3187,7 +3219,8 @@
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\edef\temp{\noexpand
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\edef\temp{\noexpand
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\addplot+[mark=o, line width=2pt,
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\addplot+[mark=o, line width=2pt,
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forget plot, densely dashed, gray, opacity=0.4]
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forget plot, densely dashed, gray,
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opacity=0.4]
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table[
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table[
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col sep=comma, x=physical_p,
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col sep=comma, x=physical_p,
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y=LER_per_round,
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y=LER_per_round,
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@@ -3290,7 +3323,8 @@
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\edef\temp{\noexpand
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\edef\temp{\noexpand
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\addplot+[mark=o, line width=2pt,
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\addplot+[mark=o, line width=2pt,
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forget plot, densely dashed, gray, opacity=0.4]
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forget plot, densely dashed, gray,
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opacity=0.4]
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table[
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table[
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col sep=comma, x=physical_p,
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col sep=comma, x=physical_p,
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y=LER_per_round,
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y=LER_per_round,
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@@ -0,0 +1,8 @@
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physical_p,num_trials,LER,LER_per_round,num_errors
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0.001,88000,0.0022840909090909,0.00019054046349609166,200.9999999999992
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0.0015,22000,0.0091363636363636,0.0007645705814327552,200.9999999999992
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0.002,8000,0.02975,0.002513627927773654,238.0
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0.0025,4000,0.086,0.007465717670425587,344.0
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0.003,2000,0.1925,0.017659888947245128,385.0
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0.0035,2000,0.3585,0.03631953572181035,717.0
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0.004,2000,0.5395,0.06257657262550698,1079.0
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@@ -0,0 +1,8 @@
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physical_p,num_trials,LER,LER_per_round,num_errors
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0.001,6000,0.0346666666666666,0.002935833167148738,207.9999999999996
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0.0015,4000,0.09375,0.008169783831040611,375.0
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0.002,2000,0.187,0.01710405023748829,374.0
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0.0025,2000,0.3655,0.0372002499227132,731.0
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0.003,2000,0.5415,0.06291652725715624,1083.0
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0.0035,2000,0.7265,0.10240633752398864,1453.0
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0.004,2000,0.852,0.14718438639465958,1704.0
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@@ -0,0 +1,8 @@
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physical_p,num_trials,LER,LER_per_round,num_errors
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0.001,100000,0.00045,3.750773659938478e-05,45.0
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0.0015,86000,0.0023372093023255,0.00019497639289589586,200.999999999993
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0.002,22000,0.0092727272727272,0.0007760309518972663,203.9999999999984
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0.0025,6000,0.0376666666666666,0.003194419283278793,225.9999999999996
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0.003,4000,0.08425,0.007307492597147025,337.0
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0.0035,2000,0.2025,0.018679455867679495,405.0
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0.004,2000,0.345,0.034645612003118,690.0
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@@ -0,0 +1,8 @@
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physical_p,num_trials,LER,LER_per_round,num_errors
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0.001,8000,0.02875,0.0024279957468343882,230.0
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0.0015,4000,0.053,0.004527734248755855,212.0
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0.002,2000,0.1155,0.010175605072917149,231.0
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0.0025,2000,0.2185,0.02033539996612399,437.0
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0.003,2000,0.352,0.03550958250051006,704.0
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0.0035,2000,0.5315,0.06123015042661217,1063.0
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0.004,2000,0.7015,0.0958398514873553,1403.0
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@@ -0,0 +1,8 @@
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physical_p,num_trials,LER,LER_per_round,num_errors
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0.001,4000,0.0685,0.005895808515312573,274.0
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0.0015,2000,0.135,0.012012744890476657,270.0
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0.002,2000,0.2305,0.021597879347753368,461.0
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0.0025,2000,0.3925,0.04068289056153884,785.0
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0.003,2000,0.5265,0.06039929937035626,1053.0
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0.0035,2000,0.705,0.09672809706528085,1410.0
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0.004,2000,0.8195,0.1329587352216164,1639.0
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@@ -0,0 +1,8 @@
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physical_p,num_trials,LER,LER_per_round,num_errors
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0.001,10000,0.0232,0.001954201073267048,231.99999999999997
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0.0015,6000,0.0433333333333333,0.003684882338012896,259.9999999999998
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0.002,4000,0.08975,0.007805708651284715,359.0
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0.0025,2000,0.1795,0.016351617556473186,359.0
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0.003,2000,0.296,0.02882449163140266,592.0
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0.0035,2000,0.4835,0.05356848392991931,967.0
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0.004,2000,0.6535,0.08453459623940363,1307.0
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@@ -0,0 +1,8 @@
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physical_p,num_trials,LER,LER_per_round,num_errors
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0.001,8000,0.029125,0.0024600983395249854,233.0
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0.0015,4000,0.051,0.004352706093600722,204.0
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0.002,2000,0.105,0.009201699575916766,210.0
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|
0.0025,2000,0.2055,0.018987611527110704,411.0
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0.003,2000,0.348,0.035014843623407566,696.0
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0.0035,2000,0.527,0.06048202163011074,1054.0
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0.004,2000,0.7015,0.0958398514873553,1403.0
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@@ -0,0 +1,8 @@
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physical_p,num_trials,LER,LER_per_round,num_errors
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0.001,4000,0.06925,0.0059625336383020144,277.0
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0.0015,2000,0.122,0.010783823589648356,244.0
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0.002,2000,0.2125,0.019710810011481006,425.0
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0.0025,2000,0.369,0.037643952171725004,738.0
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0.003,2000,0.5215,0.059576452112257594,1043.0
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0.0035,2000,0.674,0.08917529877700736,1348.0
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0.004,2000,0.814,0.13078726888434444,1628.0
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@@ -0,0 +1,8 @@
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physical_p,num_trials,LER,LER_per_round,num_errors
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0.001,10000,0.0234,0.0019712318450325617,234.0
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0.0015,6000,0.0416666666666666,0.0035403526553423603,249.9999999999996
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0.002,4000,0.0815,0.0070594123157259325,326.0
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0.0025,2000,0.173,0.015704591731957374,346.0
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0.003,2000,0.2955,0.028767030722673725,591.0
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0.0035,2000,0.4755,0.052355475239581395,951.0
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0.004,2000,0.6535,0.08453459623940363,1307.0
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