Switch order of challenges

.gitmodules

@@ -1,3 +1,9 @@
 [submodule "lib/cel-slides-template-2025"]
 	path = lib/cel-slides-template-2025
-	url = git@gitlab.kit.edu:kit/cel/misc/cel-slides-template-2025.git
+	url = ssh://git@100.123.176.93:2222/an.tsouchlos/cel-slides-template-2025.git
+[submodule "lib/cel-thesis"]
+	path = lib/cel-thesis
+	url = ssh://git@100.123.176.93:2222/an.tsouchlos/cel-thesis.git
+[submodule "lib/latex-common"]
+	path = lib/latex-common
+	url = ssh://git@100.123.176.93:2222/an.tsouchlos/latex-common.git

.tmux_session.sh

@@ -1,7 +1,6 @@
 #!/bin/bash
 SESSION=$1
 
-tmux send-keys -t "$SESSION:1" "cd ~/workspace/private/ma-thesis/" Enter
 tmux send-keys -t "$SESSION:1" "./.setup_local_env.sh" Enter
 # tmux send-keys -t "$SESSION:1" "export TEXINPUTS=./lib/cel-slides-template-2025:\$TEXINPUTS" C-m
 tmux send-keys -t "$SESSION:1" "trap './.clean_local_env.sh' EXIT" Enter

Makefile

@@ -1,11 +1,13 @@
-DOCUMENTS := $(patsubst src/%/main.tex,build/%.pdf,$(wildcard src/*/main.tex))
+DOCUMENTS := build/midterm_presentation.pdf build/thesis.pdf
+# DOCUMENTS := build/thesis.pdf
 
 .PHONY: all
 all: $(DOCUMENTS)
 
 build/%.pdf: src/%/main.tex build/prepared
-	latexmk $<
+	TEXINPUTS=./lib/cel-slides-template-2025:$(dir $<):$$TEXINPUTS \
-	mv build/main.pdf $@
+	latexmk -outdir=build/$* $<
+	mv build/thesis/main.pdf $@
 
 build/prepared:
 	mkdir -p build

src/final_presentation/MA.bib

@@ -783,8 +783,7 @@ TLDR: A recurrent, transformer-based neural network, called AlphaQubit, learns h
 	author = {Senior, Andrew W. and Edlich, Thomas and Heras, Francisco J. H. and Zhang, Lei M. and Higgott, Oscar and Spencer, James S. and Applebaum, Taylor and Blackwell, Sam and Ledford, Justin and Žemgulytė, Akvilė and Žídek, Augustin and Shutty, Noah and Cowie, Andrew and Li, Yin and Holland, George and Brooks, Peter and Beattie, Charlie and Newman, Michael and Davies, Alex and Jones, Cody and Boixo, Sergio and Neven, Hartmut and Kohli, Pushmeet and Bausch, Johannes},
 	month = dec,
 	year = {2025},
-	note = {arXiv:2512.07737 [quant-ph]
+	note = {arXiv:2512.07737 [quant-ph]},
-TLDR: AlphaQubit 2 is introduced, a neural-network decoder that achieves near-optimal logical error rates for both surface and colour codes at large scales under realistic noise and demonstrates real-time decoding faster than 1 microsecond per cycle up to distance 11 on current commercial accelerators with better accuracy than leading real-time decoders.},
 	keywords = {/unread, Computer Science - Machine Learning, Quantum Physics},
 	file = {Preprint PDF:/home/andreas/workspace/work/hiwi/Zotero/storage/9RIBP938/Senior et al. - 2025 - A scalable and real-time neural decoder for topological quantum codes.pdf:application/pdf;Snapshot:/home/andreas/workspace/work/hiwi/Zotero/storage/W3UIHVW5/2512.html:text/html},
 }
@@ -1383,54 +1382,3 @@ We study the performance of medium-length quantum LDPC (QLDPC) codes in the depo
 	pages = {2492--2519},
 	file = {Full Text PDF:/home/andreas/workspace/work/hiwi/Zotero/storage/TRAQVN6J/Babar et al. - 2015 - Fifteen Years of Quantum LDPC Coding and Improved Decoding Strategies.pdf:application/pdf;PDF:/home/andreas/workspace/work/hiwi/Zotero/storage/K753QNFF/Babar et al. - 2015 - Fifteen Years of Quantum LDPC Coding and Improved Decoding Strategies.pdf:application/pdf},
 }
-
-@misc{yao_belief_2024,
-	title = {Belief {Propagation} {Decoding} of {Quantum} {LDPC} {Codes} with {Guided} {Decimation}},
-	url = {http://arxiv.org/abs/2312.10950},
-	doi = {10.48550/arXiv.2312.10950},
-	abstract = {Quantum low-density parity-check (QLDPC) codes have emerged as a promising technique for quantum error correction. A variety of decoders have been proposed for QLDPC codes and many of them utilize belief propagation (BP) decoding in some fashion. However, the use of BP decoding for degenerate QLDPC codes is known to have issues with convergence. These issues are typically attributed to short cycles in the Tanner graph and code degeneracy (i.e. multiple error patterns with the same syndrome). Although various methods have been proposed to mitigate the non-convergence issue, such as BP with ordered statistics decoding (BP-OSD) and BP with stabilizer inactivation (BP-SI), achieving better performance with lower complexity remains an active area of research. In this work, we propose a decoder for QLDPC codes based on BP guided decimation (BPGD), which has been previously studied for constraint satisfaction and lossy compression problems. The decimation process is applicable to both binary and quaternary BP and it involves sequentially fixing the value of the most reliable qubits to encourage BP convergence. Despite its simplicity, We find that BPGD significantly reduces the BP failure rate due to non-convergence, achieving performance on par with BP with ordered statistics decoding and BP with stabilizer inactivation, without the need to solve systems of linear equations.},
-	urldate = {2026-03-04},
-	publisher = {arXiv},
-	author = {Yao, Hanwen and Laban, Waleed Abu and Häger, Christian and Amat, Alexandre Graell i and Pfister, Henry D.},
-	month = jun,
-	year = {2024},
-	note = {arXiv:2312.10950 [cs]},
-	keywords = {/unread, Computer Science - Information Theory, Quantum Physics},
-	file = {Preprint PDF:/home/andreas/workspace/work/hiwi/Zotero/storage/FS3SYGDZ/Yao et al. - 2024 - Belief Propagation Decoding of Quantum LDPC Codes with Guided Decimation.pdf:application/pdf},
-}
-
-@article{sharon_efficient_2007,
-	title = {Efficient {Serial} {Message}-{Passing} {Schedules} for {LDPC} {Decoding}},
-	volume = {53},
-	issn = {1557-9654},
-	url = {https://ieeexplore.ieee.org/document/4373433/;jsessionid=513F0F57B02F35538297208C3406719C},
-	doi = {10.1109/TIT.2007.907507},
-	abstract = {Conventionally, in each low-density parity-check (LDPC) decoding iteration all the variable nodes and subsequently all the check nodes send messages to their neighbors (flooding schedule). An alternative, more efficient, approach is to update the nodes' messages serially (serial schedule). A theoretical analysis of serial message passing decoding schedules is presented. In particular, the evolution of the computation tree under serial scheduling is analyzed. It shows that the tree grows twice as fast in comparison to the flooding schedule's one, indicating that the serial schedule propagates information twice as fast in the code's underlying graph. Furthermore, an asymptotic analysis of the serial schedule's convergence rate is done using the density evolution (DE) algorithm. Applied to various ensembles of LDPC codes, it shows that for long codes the serial schedule is expected to converge in half the number of iterations compared to the standard flooding schedule, when working near the ensemble's threshold. This observation is generally proved for the binary erasure channel (BEC) under some natural assumptions. Finally, an accompanying concentration theorem is proved.},
-	number = {11},
-	urldate = {2026-03-09},
-	journal = {IEEE Transactions on Information Theory},
-	author = {Sharon, Eran and Litsyn, Simon and Goldberger, Jacob},
-	month = nov,
-	year = {2007},
-	keywords = {/unread, Parity check codes, iterative decoding, Iterative decoding, Belief propagation, Algorithm design and analysis, Code standards, Convergence, density evolution, factor graph, Floods, low-density parity-check (LDPC) codes, Message passing, message-passing decoding, Processor scheduling, Scheduling algorithm, Tree graphs},
-	pages = {4076--4091},
-	file = {Submitted Version:/home/andreas/workspace/work/hiwi/Zotero/storage/PIDDUDIG/Sharon et al. - 2007 - Efficient Serial Message-Passing Schedules for LDPC Decoding.pdf:application/pdf},
-}
-
-@article{shannon_mathematical_1948,
-	title = {A mathematical theory of communication},
-	volume = {27},
-	issn = {0005-8580},
-	url = {https://ieeexplore.ieee.org/abstract/document/6773024},
-	doi = {10.1002/j.1538-7305.1948.tb01338.x},
-	abstract = {The recent development of various methods of modulation such as PCM and PPM which exchange bandwidth for signal-to-noise ratio has intensified the interest in a general theory of communication. A basis for such a theory is contained in the important papers of Nyquist1 and Hartley2 on this subject. In the present paper we will extend the theory to include a number of new factors, in particular the effect of noise in the channel, and the savings possible due to the statistical structure of the original message and due to the nature of the final destination of the information.},
-	number = {3},
-	urldate = {2026-03-19},
-	journal = {The Bell System Technical Journal},
-	author = {Shannon, C. E.},
-	month = jul,
-	year = {1948},
-	keywords = {/unread},
-	pages = {379--423},
-	file = {Full Text PDF:/home/andreas/workspace/work/hiwi/Zotero/storage/EQLCJ99K/Shannon - 1948 - A mathematical theory of communication.pdf:application/pdf},
-}

src/final_presentation/copy_sim_results.sh

@@ -0,0 +1,150 @@
+#!/bin/bash
+
+BASE_PATH="/home/andreas/workspace/private/ma-sw-results/outputs/"
+
+# Copy BP param exploration results
+
+function post_process_LERs() {
+    local filename="$1"
+
+    python3 -c "
+import pandas as pd
+import numpy as np
+
+df = pd.read_csv('${filename}')
+df['LER_per_round'] = 1 - (1 - df['LER'])**(1/12)
+df['num_errors'] = df['num_trials'] * df['LER']
+df.to_csv('${filename}', index=False)
+"       
+}
+
+i=1
+sp="/-\|"
+
+# echo "Copying BP param exploration results..."
+# echo -n ' '
+# for decoder in "WindowingSyndromeMinSumDecoder" "WindowingSyndromeSpaDecoder"; do
+#     for max_iter in 32 200 5000; do
+#         for pass_soft_info in "True" "False"; do
+#             for F in 1 2 3; do
+#                 for W in 3 4 5; do
+#                     SRC_PATH="${BASE_PATH}+rust_exp=soft_v_hard_bp,decoder.class_name=${decoder},decoder.max_iter=${max_iter},decoder.pass_soft_info=${pass_soft_info},system.F=${F},system.W=${W}/"
+#                     LATEST_RESULTS_DIR=$(ls -t ${SRC_PATH} | head -1)
+#                     SRC_FILE="${SRC_PATH}/${LATEST_RESULTS_DIR}/LERs.csv"
+#                     DEST_DIR="res/sim/WF/${decoder}/max_iter_${max_iter}/pass_soft_info_${pass_soft_info}/F_${F}/W_${W}/"
+#                     mkdir -p ${DEST_DIR}
+#                     DEST_FILE="${DEST_DIR}/LERs.csv"
+#                     cp ${SRC_FILE} ${DEST_FILE}
+#                     post_process_LERs ${DEST_FILE}
+#                     printf "\b${sp:i++%${#sp}:1}"
+#                 done
+#             done
+#         done
+#     done
+# done
+#
+# # Copy BPGD param exploration results
+#
+# echo -e "\rCopying BPGD param exploration results..."
+# echo -n ' '
+# for max_iter in 32 200 5000; do
+#     for pass_soft_info in "True" "False"; do
+#         for F in 1 2 3; do
+#             for W in 3 4 5; do
+#                 SRC_PATH="${BASE_PATH}/+rust_exp=soft_v_hard_bpgd,decoder.class_name=WindowingSyndromeSpaGdDecoder,decoder.max_iter=${max_iter},decoder.pass_soft_info=${pass_soft_info},system.F=${F},system.W=${W}/"
+#                 LATEST_RESULTS_DIR=$(ls -t ${SRC_PATH} | head -1)
+#                 SRC_FILE="${SRC_PATH}/${LATEST_RESULTS_DIR}/LERs.csv"
+#                 DEST_DIR="res/sim/WF/WindowingSyndromeSpaGdDecoder/max_iter_${max_iter}/pass_soft_info_${pass_soft_info}/F_${F}/W_${W}/"
+#                 mkdir -p ${DEST_DIR}
+#                 DEST_FILE="${DEST_DIR}/LERs.csv"
+#                 cp ${SRC_FILE} ${DEST_FILE}
+#                 post_process_LERs ${DEST_FILE}
+#                 printf "\b${sp:i++%${#sp}:1}"
+#             done
+#         done
+#     done
+# done
+#
+# # Copy BP over max iter. results
+#
+# echo -e "\rCopying BP over max. iter. results..."
+# echo -n ' '
+# for decoder in "WindowingSyndromeMinSumDecoder" "WindowingSyndromeSpaDecoder"; do
+#     for p in 0.001 0.0025 0.004; do
+#         for pass_soft_info in "True" "False"; do
+#             for F in 1 2 3; do
+#                 for W in 3 4 5; do
+#                     SRC_PATH="${BASE_PATH}+rust_exp=max_iter_bp,decoder.class_name=${decoder},decoder.pass_soft_info=${pass_soft_info},simulation.phy_err_rate=${p},system.F=${F},system.W=${W}/"
+#                     LATEST_RESULTS_DIR=$(ls -t ${SRC_PATH} | head -1)
+#                     SRC_FILE="${SRC_PATH}/${LATEST_RESULTS_DIR}/LERs.csv"
+#                     DEST_DIR="res/sim/max_iter/${decoder}/p_${p}/pass_soft_info_${pass_soft_info}/F_${F}/W_${W}"
+#                     mkdir -p ${DEST_DIR}
+#                     DEST_FILE="${DEST_DIR}/LERs.csv"
+#                     cp ${SRC_FILE} ${DEST_FILE}
+#                     post_process_LERs ${DEST_FILE}
+#                     printf "\b${sp:i++%${#sp}:1}"
+#                 done
+#             done
+#         done
+#     done
+# done
+#
+# # Copy BPGD over max iter. results
+#
+# echo -e "\rCopying BPGD over max. iter. results..."
+# echo -n ' '
+# for p in 0.001 0.0025 0.004; do
+#     for pass_soft_info in "True" "False"; do
+#         for F in 1 2 3; do
+#             for W in 3 4 5; do
+#                 SRC_PATH="${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}/"
+#                 LATEST_RESULTS_DIR=$(ls -t ${SRC_PATH} | head -1)
+#                 SRC_FILE="${SRC_PATH}/${LATEST_RESULTS_DIR}/LERs.csv"
+#                 DEST_DIR="res/sim/max_iter/WindowingSyndromeSpaGdDecoder/p_${p}/pass_soft_info_${pass_soft_info}/F_${F}/W_${W}"
+#                 mkdir -p ${DEST_DIR}
+#                 DEST_FILE="${DEST_DIR}/LERs.csv"
+#                 cp ${SRC_FILE} ${DEST_FILE}
+#                 post_process_LERs ${DEST_FILE}
+#                 printf "\b${sp:i++%${#sp}:1}"
+#             done
+#         done
+#     done
+# done
+#
+# # Copy BP over max iter. results
+#
+# echo -e "\rCopying one-shot simulation results..."
+# echo -n ' '
+# for decoder in "SyndromeMinSumDecoder" "SyndromeSpaDecoder" "SyndromeSpaGdDecoder"; do
+#     for max_iter in 32 200 5000; do
+#         SRC_PATH="${BASE_PATH}+rust_exp=whole_bp_bpgd,decoder.class_name=${decoder},decoder.max_iter=${max_iter},system.F=1,system.W=5/"
+#         LATEST_RESULTS_DIR=$(ls -t ${SRC_PATH} | head -1)
+#         SRC_FILE="${SRC_PATH}/${LATEST_RESULTS_DIR}/LERs.csv"
+#         DEST_DIR="res/sim/one-shot/${decoder}/max_iter_${max_iter}/"
+#         mkdir -p ${DEST_DIR}
+#         DEST_FILE="${DEST_DIR}/LERs.csv"
+#         cp ${SRC_FILE} ${DEST_FILE}
+#         post_process_LERs ${DEST_FILE}
+#         printf "\b${sp:i++%${#sp}:1}"
+#     done
+# done
+
+# Copy BPGD decimation passing
+
+echo -e "\rCopying BPGD param exploration results..."
+echo -n ' '
+for max_iter in 32 200 5000; do
+    for F in 1 2 3; do
+        for W in 3 4 5; do
+            SRC_PATH="${BASE_PATH}+rust_exp=soft_v_hard_bpgd_pass_channel,decoder.class_name=WindowingSyndromeSpaGdDecoder,decoder.max_iter=${max_iter},decoder.pass_soft_info=True,system.F=${F},system.W=${W}"
+            LATEST_RESULTS_DIR=$(ls -t ${SRC_PATH} | head -1)
+            SRC_FILE="${SRC_PATH}/${LATEST_RESULTS_DIR}/LERs.csv"
+            DEST_DIR="res/sim/WF/WindowingSyndromeSpaGdDecoderPassDecimation/max_iter_${max_iter}/pass_soft_info_True/F_${F}/W_${W}/"
+            mkdir -p ${DEST_DIR}
+            DEST_FILE="${DEST_DIR}/LERs.csv"
+            cp ${SRC_FILE} ${DEST_FILE}
+            post_process_LERs ${DEST_FILE}
+            printf "\b${sp:i++%${#sp}:1}"
+        done
+    done
+done

src/final_presentation/gen_sliding_window_overlap_image.py

@@ -0,0 +1,195 @@
+import warnings
+from typing import Sequence
+
+import numpy as np
+import matplotlib.pyplot as plt
+import matplotlib.patches as pt
+from scipy.sparse import csc_matrix
+
+from quits.decoder import spacetime
+from quits.decoder import detector_error_model_to_matrix
+
+from quits.qldpc_code import BbCode
+from quits import ErrorModel, CircuitBuildOptions
+
+
+def build_bb_circuit(N: int, num_rounds: int, p: float):
+    # fmt: off
+    if N == 72:
+        code = BbCode(l=6, m=6, A_x_pows=[3], A_y_pows=[1, 2], B_x_pows=[1, 2], B_y_pows=[3])
+    elif N == 90:
+        code = BbCode(l=15, m=3, A_x_pows=[9], A_y_pows=[1, 2], B_x_pows=[2, 7], B_y_pows=[0])
+    elif N == 108:
+        code = BbCode(l=9, m=6, A_x_pows=[3], A_y_pows=[1, 2], B_x_pows=[1, 2], B_y_pows=[3])
+    elif N == 144:
+        code = BbCode(l=12, m=6, A_x_pows=[3], A_y_pows=[1, 2], B_x_pows=[1, 2], B_y_pows=[3])
+    elif N == 288:
+        code = BbCode(l=12, m=12, A_x_pows=[3], A_y_pows=[2, 7], B_x_pows=[1, 2], B_y_pows=[3])
+    elif N == 360:
+        code = BbCode(l=30, m=6, A_x_pows=[9], A_y_pows=[1, 2], B_x_pows=[25, 26], B_y_pows=[3])
+    elif N == 756:
+        code = BbCode(l=21, m=18, A_x_pows=[3], A_y_pows=[10, 17], B_x_pows=[3, 19], B_y_pows=[5])
+    else:
+        assert False, "Unsupported code size"
+    # fmt: on
+
+    circuit = code.build_circuit(
+        error_model=ErrorModel(p, p, p, p),
+        num_rounds=num_rounds,
+        basis="Z",
+        circuit_build_options=CircuitBuildOptions(),
+        seed=1,
+    )
+
+    return code, circuit
+
+
+
+
+def compute_num_windows(num_rounds: int, W: int, F: int):
+    """
+    This was extracted from the function `sliding_window_circuit_mem()` of
+    `quits.decoder`.
+    """
+    if 2 + num_rounds - W >= 0:
+        # num_cor_rounds = num of windows before the last window
+        num_cor_rounds = (2 + num_rounds - W) // F
+
+        # we can slide one more window if the remaining rounds > W
+        if (2 + num_rounds - W) % F != 0:
+            num_cor_rounds += 1
+    else:
+        num_cor_rounds = 0
+        warnings.warn(
+            "Window size larger than the syndrome extraction rounds: Doing"
+            " whole history correction"
+        )
+
+    return num_cor_rounds + 1
+
+
+def get_overlap_info(
+    col_start_indices: Sequence, W: int, F: int, m: int, win_check_set: Sequence
+):
+    def i_B(k: int):
+        return col_start_indices[k]
+
+    def i_E(k: int):
+        return i_B(k) + win_check_set[k].shape[1]
+
+    def j_B(k: int):
+        return F * (k) * m
+
+    def j_E(k: int):
+        return (F * k + W) * m
+
+    num_windows = len(win_check_set)
+
+    overlap_begin_positions = []
+    for k in range(num_windows - 1):
+        overlap_begin_positions.append((j_B(k + 1) - j_B(k), i_B(k + 1) - i_B(k)))
+
+    overlap_end_positions = []
+    for k in range(1, num_windows):
+        overlap_end_positions.append((j_E(k - 1) - j_B(k), i_E(k - 1) - i_B(k)))
+
+    return overlap_begin_positions, overlap_end_positions
+
+
+def reconstruct_window_start_col_indices(win_observable_set: Sequence):
+    """
+    This function effectively just reconstructs the `col_min` values of each
+    window, from the `spacetime()` function of `quits.decoder`.
+    """
+    num_windows = len(win_observable_set)
+
+    col_mins = [0]
+
+    for k in range(num_windows - 1):
+        col_mins.append(col_mins[-1] + win_observable_set[k].shape[1])
+
+    return col_mins
+
+
+
+
+num_rounds = 12
+N = 72
+p = 0.005
+W = 5
+F = 3
+
+#
+# Get detector error matrix and split it into windows
+#
+
+code, circuit = build_bb_circuit(N, num_rounds, p)
+model = circuit.detector_error_model(decompose_errors=False)
+check_matrix, observable_matrix, priors = detector_error_model_to_matrix(model)
+
+num_windows = compute_num_windows(num_rounds, W, F)
+win_check_set, win_observable_set, win_priors_set, win_update = spacetime(
+    circuit, code.hz, W, F, num_windows - 1
+)
+
+col_start_indices = reconstruct_window_start_col_indices(win_observable_set)
+
+#
+# Paint rectangles
+#
+
+custom_colors = [
+    (162/255, 34/255, 35/255),
+    (223/255, 155/255, 27/255),
+    (70/255, 100/255, 170/255),
+    (163/255, 16/255, 124/255),
+]
+
+fig, ax = plt.subplots(1, 1, figsize=(10, 10))
+ax.spy(check_matrix.toarray())
+
+colors = [custom_colors[i % len(custom_colors)] for i in range(num_windows)]
+
+m = code.hz.shape[0]
+# for win_idx in range(num_windows):
+#     col_start_idx = col_start_indices[win_idx]
+#     row_start_idx = win_idx * F * m
+#
+#     ax.add_patch(
+#         pt.Rectangle(
+#             (col_start_idx, row_start_idx),
+#             win_check_set[win_idx].shape[1],
+#             win_check_set[win_idx].shape[0],
+#             fc="none",
+#             ec=colors[win_idx],
+#         )
+#     )
+
+# overlap_begin_positions, overlap_end_positions = get_overlap_info(
+#     col_start_indices, W, F, m, win_check_set
+# )
+
+# for k in range(len(win_check_set) - 1):
+#     ax.add_patch(
+#         pt.Rectangle(
+#             (
+#                 overlap_begin_positions[k][1] + col_start_indices[k],
+#                 overlap_begin_positions[k][0] + F * k * m,
+#             ),
+#             win_check_set[k].shape[1] - overlap_begin_positions[k][1],
+#             win_check_set[k].shape[0] - overlap_begin_positions[k][0],
+#             fc=colors[k],
+#             ec=colors[k],
+#             alpha=0.3,
+#         )
+#     )
+
+
+ax.set_xticks([])
+ax.set_yticks([])
+
+fig.savefig('72_bb_dem_no_windows.pdf', bbox_inches='tight')
+
+plt.show()
+
+

src/final_presentation/res/literature/yao_bp.csv

@@ -0,0 +1,8 @@
+p, FER
+0.040000, 0.043667
+0.049986, 0.087737
+0.059972, 0.148066
+0.069958, 0.255386
+0.079945, 0.460128
+0.089931, 0.759770
+0.100000, 0.965714

src/final_presentation/res/literature/yao_bpgd_1.csv

@@ -0,0 +1,8 @@
+p, FER
+0.040083, 0.000029
+0.049986, 0.000393
+0.059972, 0.006271
+0.069958, 0.055503
+0.080028, 0.244488
+0.090014, 0.559895
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src/final_presentation/res/literature/yao_bpgd_10.csv

@@ -0,0 +1,8 @@
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src/final_presentation/res/literature/yao_bpgd_100.csv

@@ -0,0 +1,8 @@
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src/final_presentation/res/literature/yao_bpgd_70.csv

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src/final_presentation/res/sim/WF/WindowingSyndromeMinSumDecoder/max_iter_200/pass_soft_info_False/F_1/W_3/LERs.csv

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src/final_presentation/res/sim/WF/WindowingSyndromeMinSumDecoder/max_iter_200/pass_soft_info_False/F_1/W_4/LERs.csv

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src/final_presentation/res/sim/WF/WindowingSyndromeMinSumDecoder/max_iter_200/pass_soft_info_False/F_1/W_5/LERs.csv

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src/final_presentation/res/sim/WF/WindowingSyndromeMinSumDecoder/max_iter_200/pass_soft_info_False/F_2/W_3/LERs.csv

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src/final_presentation/res/sim/WF/WindowingSyndromeMinSumDecoder/max_iter_200/pass_soft_info_False/F_2/W_4/LERs.csv

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src/final_presentation/res/sim/WF/WindowingSyndromeMinSumDecoder/max_iter_200/pass_soft_info_False/F_2/W_5/LERs.csv

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src/final_presentation/res/sim/WF/WindowingSyndromeMinSumDecoder/max_iter_200/pass_soft_info_False/F_3/W_3/LERs.csv

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src/final_presentation/res/sim/WF/WindowingSyndromeMinSumDecoder/max_iter_200/pass_soft_info_False/F_3/W_4/LERs.csv

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src/final_presentation/res/sim/WF/WindowingSyndromeMinSumDecoder/max_iter_200/pass_soft_info_False/F_3/W_5/LERs.csv

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src/final_presentation/res/sim/WF/WindowingSyndromeMinSumDecoder/max_iter_200/pass_soft_info_True/F_1/W_3/LERs.csv

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src/final_presentation/res/sim/WF/WindowingSyndromeMinSumDecoder/max_iter_200/pass_soft_info_True/F_1/W_4/LERs.csv

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src/final_presentation/res/sim/WF/WindowingSyndromeMinSumDecoder/max_iter_200/pass_soft_info_True/F_1/W_5/LERs.csv

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src/final_presentation/res/sim/WF/WindowingSyndromeMinSumDecoder/max_iter_200/pass_soft_info_True/F_2/W_3/LERs.csv

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src/final_presentation/res/sim/WF/WindowingSyndromeMinSumDecoder/max_iter_200/pass_soft_info_True/F_2/W_4/LERs.csv

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src/final_presentation/res/sim/WF/WindowingSyndromeMinSumDecoder/max_iter_200/pass_soft_info_True/F_2/W_5/LERs.csv

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src/final_presentation/res/sim/WF/WindowingSyndromeMinSumDecoder/max_iter_200/pass_soft_info_True/F_3/W_3/LERs.csv

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src/final_presentation/res/sim/WF/WindowingSyndromeMinSumDecoder/max_iter_200/pass_soft_info_True/F_3/W_4/LERs.csv

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src/final_presentation/res/sim/WF/WindowingSyndromeMinSumDecoder/max_iter_200/pass_soft_info_True/F_3/W_5/LERs.csv

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src/final_presentation/res/sim/WF/WindowingSyndromeMinSumDecoder/max_iter_32/pass_soft_info_False/F_1/W_3/LERs.csv

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src/final_presentation/res/sim/WF/WindowingSyndromeMinSumDecoder/max_iter_32/pass_soft_info_False/F_1/W_4/LERs.csv

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src/final_presentation/res/sim/WF/WindowingSyndromeMinSumDecoder/max_iter_32/pass_soft_info_False/F_1/W_5/LERs.csv

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src/final_presentation/res/sim/WF/WindowingSyndromeMinSumDecoder/max_iter_32/pass_soft_info_False/F_2/W_3/LERs.csv

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src/final_presentation/res/sim/WF/WindowingSyndromeMinSumDecoder/max_iter_32/pass_soft_info_True/F_1/W_4/LERs.csv

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src/final_presentation/res/sim/WF/WindowingSyndromeMinSumDecoder/max_iter_32/pass_soft_info_True/F_1/W_5/LERs.csv

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src/final_presentation/res/sim/WF/WindowingSyndromeMinSumDecoder/max_iter_32/pass_soft_info_True/F_2/W_3/LERs.csv

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src/final_presentation/res/sim/WF/WindowingSyndromeMinSumDecoder/max_iter_32/pass_soft_info_True/F_2/W_4/LERs.csv

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src/final_presentation/res/sim/WF/WindowingSyndromeMinSumDecoder/max_iter_32/pass_soft_info_True/F_2/W_5/LERs.csv

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src/final_presentation/res/sim/WF/WindowingSyndromeMinSumDecoder/max_iter_32/pass_soft_info_True/F_3/W_3/LERs.csv

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src/final_presentation/res/sim/WF/WindowingSyndromeMinSumDecoder/max_iter_32/pass_soft_info_True/F_3/W_4/LERs.csv

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src/final_presentation/res/sim/WF/WindowingSyndromeMinSumDecoder/max_iter_32/pass_soft_info_True/F_3/W_5/LERs.csv

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src/final_presentation/res/sim/WF/WindowingSyndromeMinSumDecoder/max_iter_5000/pass_soft_info_False/F_1/W_3/LERs.csv

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src/final_presentation/res/sim/WF/WindowingSyndromeMinSumDecoder/max_iter_5000/pass_soft_info_False/F_1/W_4/LERs.csv

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src/final_presentation/res/sim/WF/WindowingSyndromeMinSumDecoder/max_iter_5000/pass_soft_info_False/F_1/W_5/LERs.csv

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src/final_presentation/res/sim/WF/WindowingSyndromeMinSumDecoder/max_iter_5000/pass_soft_info_False/F_2/W_3/LERs.csv

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src/final_presentation/res/sim/WF/WindowingSyndromeMinSumDecoder/max_iter_5000/pass_soft_info_False/F_2/W_4/LERs.csv

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src/final_presentation/res/sim/WF/WindowingSyndromeMinSumDecoder/max_iter_5000/pass_soft_info_False/F_2/W_5/LERs.csv

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src/final_presentation/res/sim/WF/WindowingSyndromeMinSumDecoder/max_iter_5000/pass_soft_info_False/F_3/W_3/LERs.csv

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src/final_presentation/res/sim/WF/WindowingSyndromeMinSumDecoder/max_iter_5000/pass_soft_info_False/F_3/W_5/LERs.csv

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src/final_presentation/res/sim/WF/WindowingSyndromeMinSumDecoder/max_iter_5000/pass_soft_info_True/F_1/W_3/LERs.csv

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src/final_presentation/res/sim/WF/WindowingSyndromeMinSumDecoder/max_iter_5000/pass_soft_info_True/F_1/W_4/LERs.csv

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src/final_presentation/res/sim/WF/WindowingSyndromeMinSumDecoder/max_iter_5000/pass_soft_info_True/F_1/W_5/LERs.csv

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src/final_presentation/res/sim/WF/WindowingSyndromeMinSumDecoder/max_iter_5000/pass_soft_info_True/F_2/W_3/LERs.csv

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src/final_presentation/res/sim/WF/WindowingSyndromeMinSumDecoder/max_iter_5000/pass_soft_info_True/F_2/W_4/LERs.csv

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src/final_presentation/res/sim/WF/WindowingSyndromeMinSumDecoder/max_iter_5000/pass_soft_info_True/F_2/W_5/LERs.csv

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src/final_presentation/res/sim/WF/WindowingSyndromeSpaDecoder/max_iter_200/pass_soft_info_False/F_1/W_3/LERs.csv

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src/final_presentation/res/sim/WF/WindowingSyndromeSpaDecoder/max_iter_200/pass_soft_info_False/F_1/W_5/LERs.csv

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src/final_presentation/res/sim/WF/WindowingSyndromeSpaDecoder/max_iter_200/pass_soft_info_False/F_2/W_3/LERs.csv

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src/final_presentation/res/sim/WF/WindowingSyndromeSpaDecoder/max_iter_200/pass_soft_info_False/F_2/W_4/LERs.csv

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src/final_presentation/res/sim/WF/WindowingSyndromeSpaDecoder/max_iter_200/pass_soft_info_False/F_2/W_5/LERs.csv

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src/final_presentation/res/sim/WF/WindowingSyndromeSpaDecoder/max_iter_200/pass_soft_info_False/F_3/W_3/LERs.csv

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src/final_presentation/res/sim/WF/WindowingSyndromeSpaDecoder/max_iter_200/pass_soft_info_False/F_3/W_4/LERs.csv

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src/final_presentation/res/sim/WF/WindowingSyndromeSpaDecoder/max_iter_200/pass_soft_info_False/F_3/W_5/LERs.csv

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src/final_presentation/res/sim/WF/WindowingSyndromeSpaDecoder/max_iter_200/pass_soft_info_True/F_1/W_3/LERs.csv

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src/final_presentation/res/sim/WF/WindowingSyndromeSpaDecoder/max_iter_200/pass_soft_info_True/F_1/W_4/LERs.csv

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src/final_presentation/res/sim/WF/WindowingSyndromeSpaDecoder/max_iter_200/pass_soft_info_True/F_1/W_5/LERs.csv

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src/final_presentation/res/sim/WF/WindowingSyndromeSpaDecoder/max_iter_200/pass_soft_info_True/F_2/W_3/LERs.csv

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src/final_presentation/res/sim/WF/WindowingSyndromeSpaDecoder/max_iter_200/pass_soft_info_True/F_2/W_4/LERs.csv

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src/final_presentation/res/sim/WF/WindowingSyndromeSpaDecoder/max_iter_200/pass_soft_info_True/F_2/W_5/LERs.csv

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src/final_presentation/res/sim/WF/WindowingSyndromeSpaDecoder/max_iter_200/pass_soft_info_True/F_3/W_3/LERs.csv

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src/final_presentation/res/sim/WF/WindowingSyndromeSpaDecoder/max_iter_32/pass_soft_info_False/F_1/W_3/LERs.csv

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