141 Commits

Author SHA1 Message Date
17191382cf Incorporate Lia's corrections to QM and QEC fundamentals 2026-05-04 13:01:54 +02:00
aa907ef4a3 Incorporate Lia's corrections to classical fundamentals 2026-05-04 12:12:10 +02:00
12036caa91 Fix bibliography titlecase (in clean_bibliography.sh) and a few things in the bibliography itself 2026-05-04 10:53:50 +02:00
4c206ae9c4 Rephrase first sentence of abstract 2026-05-04 10:34:53 +02:00
01a754e5da Reset acronyms after abstract 2026-05-04 10:31:54 +02:00
81292a2644 Add abstract 2026-05-04 10:28:46 +02:00
73958d7850 Check out version of cel thesis template with option for signature 2026-05-04 02:08:32 +02:00
18e3683502 Add signature 2026-05-04 02:06:58 +02:00
1eb4db289e Make main.tex work with signature modification 2026-05-04 02:06:39 +02:00
f56cd05890 Fix bibtex definition for arxiv papers 2026-05-04 01:45:46 +02:00
e9d996155d Write conclusion 2026-05-04 01:21:26 +02:00
5e26179154 Finish intro 2026-05-03 20:51:32 +02:00
9ae98e07d7 Write most of Introduction; Fix citing Intro. 2026-05-03 19:09:29 +02:00
728c8560c7 Fix N_C/N_V notation 2026-05-03 14:07:04 +02:00
dd30b4fc0d Write captions 2026-05-03 04:26:58 +02:00
6e53ed5d1b Complete results chapter text 2026-05-03 04:00:05 +02:00
0016df0004 Add text for second BPGD plot 2026-05-03 03:10:21 +02:00
9ca2698d38 Add text for first BPGD figure 2026-05-03 02:16:22 +02:00
72461fe555 Complete first draft of warm-start sliding-window decoding section 2026-05-03 01:11:22 +02:00
5fabe2e146 Finish first draft of BP warm start subsection 2026-05-02 23:40:29 +02:00
a90458dd8a Write conclusion to BP investigation. BP investigation now done 2026-05-02 19:16:26 +02:00
d2960b8f0e Write text for figure 4.10 2026-05-02 17:59:44 +02:00
6b1821fd6b Add TODOs; Add magnified plot to other figure 2026-05-02 17:28:20 +02:00
5687499b5b Add paragraphs exp. params, description, and interpretation for fig. 4.9 2026-05-02 16:58:02 +02:00
f4718b67e7 Complete text for first two figures 2026-05-02 14:38:50 +02:00
0848e5dea6 Move order of figures 2026-05-02 11:38:04 +02:00
7e18985b86 Add whole decoding line to max_iter plot 2026-05-02 11:22:25 +02:00
152e784546 Refactor the intro to numerical results 2026-05-02 10:38:51 +02:00
15190ccf48 Include claude corrections for first 5 pages of decoding chapter 2026-05-02 09:01:19 +02:00
606d68e2c1 Rephrase to remove 'gate schedule' 2026-05-01 21:56:03 +02:00
47493a6beb Write numerical results intro 2026-05-01 21:51:48 +02:00
76a91c7d32 Add H_overlap to figure 2026-05-01 19:33:37 +02:00
1632f19c47 Add syndrome update equation 2026-05-01 19:31:18 +02:00
3d3556689e Add node set Visualization figure 2026-05-01 19:13:22 +02:00
4555570665 Finish index definitions 2026-05-01 18:08:57 +02:00
3b7618e1d1 Start VN and CN indexing from zero 2026-05-01 17:30:14 +02:00
635c0aab18 Rewrite VN and CN set definition text; Fix earlier TODOs 2026-05-01 16:43:16 +02:00
c555151b9d Wwrite a few paragraphs on the window generation/decoding 2026-05-01 11:47:21 +02:00
05348579f0 Switch figures 2026-05-01 10:50:07 +02:00
1059b4d98f Add QUITS paper to review 2026-05-01 10:41:54 +02:00
682eeb644e Add literature overview figure 2026-04-30 19:59:21 +02:00
27f13c1db0 Write chapter 4 intro 2026-04-30 14:05:32 +02:00
8071c9f485 Fix typos 2026-04-29 21:03:26 +02:00
94e4c9f8c9 Replace autoref by cref 2026-04-29 20:56:41 +02:00
64cf0e2269 Introduce LER 2026-04-29 20:31:41 +02:00
76270695b9 Fix notation 2026-04-29 20:22:26 +02:00
62b4d4838b Write stim subsection 2026-04-29 18:24:21 +02:00
0aa425ae41 Polish per-round logical error rate subsection 2026-04-29 17:40:37 +02:00
b73a66649c Rewrite DEM subsection; Write first draft of practical considerations 2026-04-29 16:12:25 +02:00
d7f05dc5b9 Rework detector matrix and detector error matrix sections 2026-04-29 13:26:35 +02:00
11178436b6 Rewrite parts of measurement syndrome matrix subsection 2026-04-29 09:26:41 +02:00
dc283012ba Move figures in chapter 3 inbetween text 2026-04-28 23:45:44 +02:00
87e48b5ac6 Move 3-qubit repetition code check matrix; Rewrite DEM intro 2026-04-28 18:58:16 +02:00
42a689d811 Polish second paragraphs of noise model subsecions 2026-04-28 18:12:21 +02:00
b46df8120b Rewrite intro to chapter 3; Add subsections for each noise model 2026-04-28 16:22:03 +02:00
5ced7b152e Write first couple of pages of chapter 3 2026-04-28 01:59:52 +02:00
3953320216 Write mathematical fault tolerance definition 2026-04-27 18:03:28 +02:00
4aa4799969 Fix wrong sim results; Add bpgd with decimation info passing over max iter plots 2026-04-27 16:05:54 +02:00
f899942029 Add TODOs 2026-04-27 00:26:08 +02:00
a68e22d7f5 Add simulation results for all investigations 2026-04-27 00:21:59 +02:00
0955cdd14e Add vanilla BP figures 2026-04-26 19:28:03 +02:00
7015f9d644 Add TODOs to fault tolerance chapter 2026-04-25 21:58:00 +02:00
b50308d014 Add a bunch of content TODOs 2026-04-25 19:35:53 +02:00
93f310d843 Add bit-flip noise and modify phenomenological and circuit-level noise figures 2026-04-25 18:49:03 +02:00
163ef926e7 Move figures to next chapter 2026-04-25 17:40:43 +02:00
4da37dbddc Add three-qubit rep. code syndrome extraction circuit under bit-flip noise 2026-04-25 17:28:17 +02:00
6de9cec27e Add Tanner graph windowing figures with highlighted passed information 2026-04-25 17:09:04 +02:00
474b1d21da Add Tanner graph windowing figure 2026-04-25 16:00:19 +02:00
5483a972f9 Add windowing figure 2026-04-25 15:38:32 +02:00
5d104fbf28 Add detector construction figure 2026-04-25 15:13:02 +02:00
50a10ccb4f Add repeated syndrome extraction circuit figures for bit-flip and phenomenological noise 2026-04-25 14:59:26 +02:00
569df381ee Add clean_bibliography.sh; Incorporate LLM corrections 2026-04-25 14:14:58 +02:00
85771405db Add noise model figures 2026-04-25 14:14:41 +02:00
5875066581 Remove TODOs, formatting, minor changes 2026-04-24 17:58:30 +02:00
494a639329 Finish first draft of text for fundamentals 2026-04-24 17:44:16 +02:00
e59120b683 Fix unicode character in bib file 2026-04-24 14:16:18 +02:00
267d431542 Write BB code paragraph 2026-04-24 14:16:02 +02:00
4e1bd62504 Write CSS codes section 2026-04-24 11:04:57 +02:00
ada6e43be3 Finish writing stabilizer codes 2026-04-24 10:36:59 +02:00
6ea151ffeb Add backlog problem explanation 2026-04-24 09:25:55 +02:00
6e2cf5b8ba Add general syndrome extraction circuit 2026-04-24 00:36:34 +02:00
e792141afd Switch order of challenges 2026-04-23 13:06:01 +02:00
1810ec8632 Fix {ll,rr}bracket; Introduce Pauli group 2026-04-22 23:02:12 +02:00
513eb7579f Finish quantum circuits subsection 2026-04-22 22:48:08 +02:00
47c725e1fa Add Mai Anh's corrections 2026-04-22 22:19:15 +02:00
7d92b54deb Add Jonathan's corrections; n->3600 2026-04-22 20:41:09 +02:00
823c6ecc12 Remove Sisi's paper's figure 2026-04-22 16:23:14 +02:00
0bfa6a7733 Add Tanner graph slides 2026-04-22 16:03:18 +02:00
ecc6b89cb2 Fix BPGD plots 2026-04-22 15:32:31 +02:00
2d53071223 Add corrections to BPGD slide 2026-04-22 14:31:13 +02:00
8196702b73 Add step size corrections 2026-04-22 14:07:17 +02:00
3a0138060e Add window size visualization corrections 2026-04-22 13:35:46 +02:00
ba951c7006 Implement corrections up to slide 17 2026-04-22 10:25:35 +02:00
a6092a5183 Finish first draft of stabilizer measurement section 2026-04-20 22:49:30 +02:00
60e457f21b Add TODO 2026-04-20 18:59:27 +02:00
3aa1518455 Finish QEC intro, most of stabilizer measurements, add outline for rest 2026-04-20 18:58:55 +02:00
2377b02974 Add simulation results with more points for W=5 2026-04-20 16:52:23 +02:00
e9c97516be Add parts of BPGD max_iter results with more datapoints 2026-04-20 10:13:42 +02:00
2b1c5aacce [thesis] modify comments, phrasing, red outline 2026-04-20 00:30:49 +02:00
50401a5169 [final_pres] Fix typo and change phrasing 2026-04-20 00:30:13 +02:00
cce965bd20 Clean up qubits and multi-qubit systems section 2026-04-19 20:15:55 +02:00
9ec70050ef Add dirty version of qubits and multi-qubit states 2026-04-19 19:07:26 +02:00
6483eaa781 Clean up projective measurements section 2026-04-18 21:22:27 +02:00
b28c482e13 Clean up observables section 2026-04-18 20:33:38 +02:00
3407aab2de Add first draft of projective measurements 2026-04-18 17:51:13 +02:00
91fdded3de Write first draft of core concepts and observables subsections 2026-04-18 12:19:32 +02:00
1fbcf0d2e6 Fix DEM explanation E_X offset 2026-04-17 23:36:06 +02:00
4763f6189c Change numerical results bullet points 2026-04-17 23:17:24 +02:00
6afa41ae0a Add edge annotations to workflow overview figure 2026-04-17 23:05:31 +02:00
2aa4bdc1b5 Add sliding window Tanner graph and BPGD slides 2026-04-17 15:02:21 +02:00
9b60bfc4ee Add one-shot results to res folder and annotate sliding window fig 2026-04-17 11:28:09 +02:00
24c574d120 Add rest of BPGD results 2026-04-17 10:26:20 +02:00
817859d09e Add BP sim results; Add some BPGD sim results 2026-04-16 14:32:15 +02:00
4250f2a903 Add sliding-window decoding slide 2026-04-15 18:40:29 +02:00
e940e7ab9f Copy midterm presentation to final presentation 2026-04-15 13:54:21 +02:00
82f27fbede Modify .tmux_session.sh 2026-04-14 13:26:41 +02:00
a7785f6c75 Remove TODOs 2026-04-10 10:51:39 +02:00
9edd80cf28 LLM review 2026-04-10 09:05:24 +02:00
fc9dcbe11e Finish first draft of classical fundamentals 2026-04-10 08:45:36 +02:00
5c4bad30e2 Add SC-LDPC Tanner Graph, fix qualitative LDPC plot, add decoding paragraph 2026-04-08 23:58:34 +02:00
1d822dac8b Enable externalization; Finish writing SC-LDPC section; Add (unfinished) Tanner graph figure 2026-04-07 18:35:57 +02:00
7fc66a2c68 [results] Add LER/p plots for n_iter_sw = 200, n_iter_whole=1536 2026-04-02 09:10:32 +02:00
9ee3eb64e9 Fix typo: 2->1 2026-04-01 18:00:54 +02:00
2246915be9 Add whole v. windowed plot for constant num. of total iterations 2026-04-01 17:51:24 +02:00
5480f2ed7b Fix plotting W instead of F in figure 2026-04-01 15:18:54 +02:00
f21563251b Add soft v. hard over max num iterations plots 2026-04-01 15:16:35 +02:00
4ae8f66603 [thesis] Add BP text and error floor figure 2026-03-30 23:19:11 +02:00
1e3af6c69e [results] Plot simulation results for max_bp_iter=200 2026-03-30 22:34:57 +02:00
942f33582f [thesis] Top-align figures; add content outline; write sc intro 2026-03-30 17:49:43 +02:00
9f3bef606a Change results structure 2026-03-30 10:53:31 +02:00
3dd0863aae Make plots show per-round-LER; Add windowed soft info decoding vs whole decoding comparison 2026-03-30 10:49:20 +02:00
b60b1a2aed Add param-exploration.tex 2026-03-30 03:56:17 +02:00
7db31aec85 Add qec meeting results 2026-03-28 10:35:43 +01:00
631eeed5cd Add windowed vs whole plot 2026-03-27 11:20:50 +01:00
733577fbfb Add resources 2026-03-27 00:29:33 +01:00
6e819d650f Add outline and main content points for QEC Meeting presentation 2026-03-27 00:29:06 +01:00
1aa45bd741 Update bibliography, phrasing, add outlines for sections 2026-03-27 00:15:39 +01:00
168688e9a0 Add qec-meeting-presentation outline 2026-03-26 10:51:08 +01:00
0949255d78 Add latex-common as submodule 2026-03-26 10:50:54 +01:00
12dc737537 Fix build system 2026-03-24 16:24:04 +01:00
082666a8e2 Write ldpc section 2026-03-24 16:23:42 +01:00
844 changed files with 22590 additions and 813 deletions

3
.gitmodules vendored
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@@ -4,3 +4,6 @@
[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

View File

@@ -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

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@@ -1,4 +1,5 @@
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)
@@ -6,7 +7,7 @@ all: $(DOCUMENTS)
build/%.pdf: src/%/main.tex build/prepared
TEXINPUTS=./lib/cel-slides-template-2025:$(dir $<):$$TEXINPUTS \
latexmk -outdir=build/$* $<
mv build/main.pdf $@
mv build/thesis/main.pdf $@
build/prepared:
mkdir -p build

1
lib/latex-common Submodule

Submodule lib/latex-common added at bded242752

File diff suppressed because it is too large Load Diff

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@@ -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

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@@ -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()

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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
1 p FER
2 0.040000 0.043667
3 0.049986 0.087737
4 0.059972 0.148066
5 0.069958 0.255386
6 0.079945 0.460128
7 0.089931 0.759770
8 0.100000 0.965714

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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
0.100000, 0.904565
1 p FER
2 0.040083 0.000029
3 0.049986 0.000393
4 0.059972 0.006271
5 0.069958 0.055503
6 0.080028 0.244488
7 0.090014 0.559895
8 0.100000 0.904565

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p, FER
0.039917, 0.000006
0.049986, 0.000179
0.059972, 0.003882
0.070042, 0.038312
0.080028, 0.229007
0.090014, 0.610921
0.100083, 0.885054
1 p FER
2 0.039917 0.000006
3 0.049986 0.000179
4 0.059972 0.003882
5 0.070042 0.038312
6 0.080028 0.229007
7 0.090014 0.610921
8 0.100083 0.885054

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p, FER
0.040083, 0.000001
0.050153, 0.000095
0.060139, 0.003121
0.070125, 0.036677
0.079945, 0.255386
0.090014, 0.513130
0.100000, 0.847287
1 p FER
2 0.040083 0.000001
3 0.050153 0.000095
4 0.060139 0.003121
5 0.070125 0.036677
6 0.079945 0.255386
7 0.090014 0.513130
8 0.100000 0.847287

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p, FER
0.040000, 0.000002
0.049986, 0.000119
0.060055, 0.003716
0.069958, 0.042725
0.080111, 0.224068
0.090014, 0.572237
0.100000, 0.904565
1 p FER
2 0.040000 0.000002
3 0.049986 0.000119
4 0.060055 0.003716
5 0.069958 0.042725
6 0.080111 0.224068
7 0.090014 0.572237
8 0.100000 0.904565

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physical_p,num_trials,LER,LER_per_round,num_errors
0.001,12000,0.01675,0.0014066653566989773,201.0
0.0015,6000,0.048,0.004090796817048492,288.0
0.002,2000,0.124,0.010971798240880681,248.0
0.0025,2000,0.258,0.024560528611376475,516.0
0.003,2000,0.441,0.04731136584915907,882.0
0.0035,2000,0.6485,0.08344096230884013,1297.0
0.004,2000,0.8085,0.1286738833656923,1617.0
1 physical_p num_trials LER LER_per_round num_errors
2 0.001 12000 0.01675 0.0014066653566989773 201.0
3 0.0015 6000 0.048 0.004090796817048492 288.0
4 0.002 2000 0.124 0.010971798240880681 248.0
5 0.0025 2000 0.258 0.024560528611376475 516.0
6 0.003 2000 0.441 0.04731136584915907 882.0
7 0.0035 2000 0.6485 0.08344096230884013 1297.0
8 0.004 2000 0.8085 0.1286738833656923 1617.0

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physical_p,num_trials,LER,LER_per_round,num_errors
0.001,50000,0.004,0.0003339460107422143,200.0
0.0015,14000,0.016,0.0013432122426282334,224.0
0.002,6000,0.0538333333333333,0.004600762670813663,322.99999999999983
0.0025,2000,0.1515,0.01359714508496701,303.0
0.003,2000,0.29,0.028137416075114108,580.0
0.0035,2000,0.485,0.05379783863208576,970.0
0.004,2000,0.657,0.08530878077130555,1314.0
1 physical_p num_trials LER LER_per_round num_errors
2 0.001 50000 0.004 0.0003339460107422143 200.0
3 0.0015 14000 0.016 0.0013432122426282334 224.0
4 0.002 6000 0.0538333333333333 0.004600762670813663 322.99999999999983
5 0.0025 2000 0.1515 0.01359714508496701 303.0
6 0.003 2000 0.29 0.028137416075114108 580.0
7 0.0035 2000 0.485 0.05379783863208576 970.0
8 0.004 2000 0.657 0.08530878077130555 1314.0

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physical_p,num_trials,LER,LER_per_round,num_errors
0.001,74000,0.0027837837837837,0.000232278495492233,205.9999999999938
0.0015,20000,0.01065,0.0008918618165982828,213.0
0.002,6000,0.0386666666666666,0.003280778882142177,231.9999999999996
0.0025,2000,0.1005,0.008787514236290539,201.0
0.003,2000,0.2145,0.019918520513549032,429.0
0.0035,2000,0.3975,0.041343353576980935,795.0
0.004,2000,0.5975,0.07303396011007879,1195.0
1 physical_p num_trials LER LER_per_round num_errors
2 0.001 74000 0.0027837837837837 0.000232278495492233 205.9999999999938
3 0.0015 20000 0.01065 0.0008918618165982828 213.0
4 0.002 6000 0.0386666666666666 0.003280778882142177 231.9999999999996
5 0.0025 2000 0.1005 0.008787514236290539 201.0
6 0.003 2000 0.2145 0.019918520513549032 429.0
7 0.0035 2000 0.3975 0.041343353576980935 795.0
8 0.004 2000 0.5975 0.07303396011007879 1195.0

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physical_p,num_trials,LER,LER_per_round,num_errors
0.001,4000,0.05975,0.005120966383739489,239.0
0.0015,2000,0.12,0.010596241035318976,240.0
0.002,2000,0.2925,0.02842304828215303,585.0
0.0025,2000,0.457,0.049614097064849094,914.0
0.003,2000,0.6565,0.08519774084658893,1313.0
0.0035,2000,0.807,0.12810716433630664,1614.0
0.004,2000,0.927,0.19596138832598886,1854.0
1 physical_p num_trials LER LER_per_round num_errors
2 0.001 4000 0.05975 0.005120966383739489 239.0
3 0.0015 2000 0.12 0.010596241035318976 240.0
4 0.002 2000 0.2925 0.02842304828215303 585.0
5 0.0025 2000 0.457 0.049614097064849094 914.0
6 0.003 2000 0.6565 0.08519774084658893 1313.0
7 0.0035 2000 0.807 0.12810716433630664 1614.0
8 0.004 2000 0.927 0.19596138832598886 1854.0

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physical_p,num_trials,LER,LER_per_round,num_errors
0.001,30000,0.0074,0.0006187681363896136,222.0
0.0015,8000,0.027375,0.002310383366790014,219.0
0.002,4000,0.081,0.007014379974311313,324.0
0.0025,2000,0.1935,0.01776132322220747,387.0
0.003,2000,0.3505,0.03532372820929974,701.0
0.0035,2000,0.549,0.06420358199217457,1098.0
0.004,2000,0.736,0.10504679589131227,1472.0
1 physical_p num_trials LER LER_per_round num_errors
2 0.001 30000 0.0074 0.0006187681363896136 222.0
3 0.0015 8000 0.027375 0.002310383366790014 219.0
4 0.002 4000 0.081 0.007014379974311313 324.0
5 0.0025 2000 0.1935 0.01776132322220747 387.0
6 0.003 2000 0.3505 0.03532372820929974 701.0
7 0.0035 2000 0.549 0.06420358199217457 1098.0
8 0.004 2000 0.736 0.10504679589131227 1472.0

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physical_p,num_trials,LER,LER_per_round,num_errors
0.001,56000,0.0035892857142857,0.0002996003321397156,200.99999999999918
0.0015,16000,0.0141875,0.001190050056010028,227.0
0.002,6000,0.0458333333333333,0.003902110220303623,274.99999999999983
0.0025,2000,0.127,0.011254499159800035,254.0
0.003,2000,0.255,0.024232483954962025,510.0
0.0035,2000,0.455,0.049322879977013234,910.0
0.004,2000,0.629,0.07930773938046853,1258.0
1 physical_p num_trials LER LER_per_round num_errors
2 0.001 56000 0.0035892857142857 0.0002996003321397156 200.99999999999918
3 0.0015 16000 0.0141875 0.001190050056010028 227.0
4 0.002 6000 0.0458333333333333 0.003902110220303623 274.99999999999983
5 0.0025 2000 0.127 0.011254499159800035 254.0
6 0.003 2000 0.255 0.024232483954962025 510.0
7 0.0035 2000 0.455 0.049322879977013234 910.0
8 0.004 2000 0.629 0.07930773938046853 1258.0

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physical_p,num_trials,LER,LER_per_round,num_errors
0.001,2000,0.632,0.07993046327730713,1264.0
0.0015,2000,0.7685,0.11479080536457342,1537.0
0.002,2000,0.8905,0.16832973055592892,1781.0
0.0025,2000,0.9405,0.2095463416012857,1881.0
0.003,2000,0.9765,0.26843039175484296,1953.0
0.0035,2000,0.993,0.33865993052589327,1986.0
0.004,2000,0.995,0.3569459165824279,1990.0
1 physical_p num_trials LER LER_per_round num_errors
2 0.001 2000 0.632 0.07993046327730713 1264.0
3 0.0015 2000 0.7685 0.11479080536457342 1537.0
4 0.002 2000 0.8905 0.16832973055592892 1781.0
5 0.0025 2000 0.9405 0.2095463416012857 1881.0
6 0.003 2000 0.9765 0.26843039175484296 1953.0
7 0.0035 2000 0.993 0.33865993052589327 1986.0
8 0.004 2000 0.995 0.3569459165824279 1990.0

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physical_p,num_trials,LER,LER_per_round,num_errors
0.001,6000,0.0361666666666666,0.003065034000747535,216.99999999999957
0.0015,4000,0.08675,0.007533613442062825,347.0
0.002,2000,0.183,0.01670196477645869,366.0
0.0025,2000,0.3605,0.036570265848455796,721.0
0.003,2000,0.5385,0.062407102537387016,1077.0
0.0035,2000,0.7385,0.10575612450061989,1477.0
0.004,2000,0.8635,0.15291357705621333,1727.0
1 physical_p num_trials LER LER_per_round num_errors
2 0.001 6000 0.0361666666666666 0.003065034000747535 216.99999999999957
3 0.0015 4000 0.08675 0.007533613442062825 347.0
4 0.002 2000 0.183 0.01670196477645869 366.0
5 0.0025 2000 0.3605 0.036570265848455796 721.0
6 0.003 2000 0.5385 0.062407102537387016 1077.0
7 0.0035 2000 0.7385 0.10575612450061989 1477.0
8 0.004 2000 0.8635 0.15291357705621333 1727.0

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physical_p,num_trials,LER,LER_per_round,num_errors
0.001,32000,0.0065,0.0005432871152698526,208.0
0.0015,10000,0.0211,0.0017755706988360487,211.0
0.002,4000,0.067,0.005762505879780444,268.0
0.0025,2000,0.1555,0.013985493383097625,311.0
0.003,2000,0.2855,0.02762559348483462,571.0
0.0035,2000,0.4885,0.05433539011619826,977.0
0.004,2000,0.678,0.09011189125403751,1356.0
1 physical_p num_trials LER LER_per_round num_errors
2 0.001 32000 0.0065 0.0005432871152698526 208.0
3 0.0015 10000 0.0211 0.0017755706988360487 211.0
4 0.002 4000 0.067 0.005762505879780444 268.0
5 0.0025 2000 0.1555 0.013985493383097625 311.0
6 0.003 2000 0.2855 0.02762559348483462 571.0
7 0.0035 2000 0.4885 0.05433539011619826 977.0
8 0.004 2000 0.678 0.09011189125403751 1356.0

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physical_p,num_trials,LER,LER_per_round,num_errors
0.001,16000,0.01375,0.0011531185491073792,220.0
0.0015,6000,0.0416666666666666,0.0035403526553423603,249.9999999999996
0.002,2000,0.11,0.009664150391878956,220.0
0.0025,2000,0.2535,0.024068915462335805,507.0
0.003,2000,0.4185,0.04417333224775788,837.0
0.0035,2000,0.62,0.0774668808446417,1240.0
0.004,2000,0.792,0.12265189055421477,1584.0
1 physical_p num_trials LER LER_per_round num_errors
2 0.001 16000 0.01375 0.0011531185491073792 220.0
3 0.0015 6000 0.0416666666666666 0.0035403526553423603 249.9999999999996
4 0.002 2000 0.11 0.009664150391878956 220.0
5 0.0025 2000 0.2535 0.024068915462335805 507.0
6 0.003 2000 0.4185 0.04417333224775788 837.0
7 0.0035 2000 0.62 0.0774668808446417 1240.0
8 0.004 2000 0.792 0.12265189055421477 1584.0

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physical_p,num_trials,LER,LER_per_round,num_errors
0.001,62000,0.0032903225806451,0.0002746079212814223,203.99999999999622
0.0015,16000,0.0134375,0.0011267480946226538,215.0
0.002,6000,0.0453333333333333,0.0038586229394146354,271.99999999999983
0.0025,2000,0.1265,0.011207320558933254,253.0
0.003,2000,0.252,0.02390564797425576,504.0
0.0035,2000,0.453,0.04903264087587211,906.0
0.004,2000,0.6265,0.07879231884746019,1253.0
1 physical_p num_trials LER LER_per_round num_errors
2 0.001 62000 0.0032903225806451 0.0002746079212814223 203.99999999999622
3 0.0015 16000 0.0134375 0.0011267480946226538 215.0
4 0.002 6000 0.0453333333333333 0.0038586229394146354 271.99999999999983
5 0.0025 2000 0.1265 0.011207320558933254 253.0
6 0.003 2000 0.252 0.02390564797425576 504.0
7 0.0035 2000 0.453 0.04903264087587211 906.0
8 0.004 2000 0.6265 0.07879231884746019 1253.0

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@@ -0,0 +1,8 @@
physical_p,num_trials,LER,LER_per_round,num_errors
0.001,100000,0.00162,0.00013510034136854365,162.0
0.0015,26000,0.0079615384615384,0.00066589492156377,206.9999999999984
0.002,8000,0.027,0.0022783337152086913,216.0
0.0025,4000,0.0855,0.0074204821894011674,342.0
0.003,2000,0.1795,0.016351617556473186,359.0
0.0035,2000,0.345,0.034645612003118,690.0
0.004,2000,0.5415,0.06291652725715624,1083.0
1 physical_p num_trials LER LER_per_round num_errors
2 0.001 100000 0.00162 0.00013510034136854365 162.0
3 0.0015 26000 0.0079615384615384 0.00066589492156377 206.9999999999984
4 0.002 8000 0.027 0.0022783337152086913 216.0
5 0.0025 4000 0.0855 0.0074204821894011674 342.0
6 0.003 2000 0.1795 0.016351617556473186 359.0
7 0.0035 2000 0.345 0.034645612003118 690.0
8 0.004 2000 0.5415 0.06291652725715624 1083.0

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physical_p,num_trials,LER,LER_per_round,num_errors
0.001,4000,0.057,0.004878809452940613,228.0
0.0015,2000,0.1345,0.011965166585961362,269.0
0.002,2000,0.2835,0.02739906464725228,567.0
0.0025,2000,0.4645,0.050714990274915994,929.0
0.003,2000,0.649,0.08354968174320077,1298.0
0.0035,2000,0.799,0.125151191269673,1598.0
0.004,2000,0.923,0.19237907929568254,1846.0
1 physical_p num_trials LER LER_per_round num_errors
2 0.001 4000 0.057 0.004878809452940613 228.0
3 0.0015 2000 0.1345 0.011965166585961362 269.0
4 0.002 2000 0.2835 0.02739906464725228 567.0
5 0.0025 2000 0.4645 0.050714990274915994 929.0
6 0.003 2000 0.649 0.08354968174320077 1298.0
7 0.0035 2000 0.799 0.125151191269673 1598.0
8 0.004 2000 0.923 0.19237907929568254 1846.0

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physical_p,num_trials,LER,LER_per_round,num_errors
0.001,28000,0.0072857142857142,0.0006091797682086231,203.9999999999976
0.0015,8000,0.026875,0.0022676530141574336,215.0
0.002,4000,0.07125,0.006140708552619056,285.0
0.0025,2000,0.181,0.016501598292156028,362.0
0.003,2000,0.343,0.0344003178522726,686.0
0.0035,2000,0.539,0.06249179545899253,1078.0
0.004,2000,0.734,0.10448375252924946,1468.0
1 physical_p num_trials LER LER_per_round num_errors
2 0.001 28000 0.0072857142857142 0.0006091797682086231 203.9999999999976
3 0.0015 8000 0.026875 0.0022676530141574336 215.0
4 0.002 4000 0.07125 0.006140708552619056 285.0
5 0.0025 2000 0.181 0.016501598292156028 362.0
6 0.003 2000 0.343 0.0344003178522726 686.0
7 0.0035 2000 0.539 0.06249179545899253 1078.0
8 0.004 2000 0.734 0.10448375252924946 1468.0

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@@ -0,0 +1,8 @@
physical_p,num_trials,LER,LER_per_round,num_errors
0.001,66000,0.0031060606060606,0.0002592076019299894,204.9999999999996
0.0015,16000,0.0130625,0.0010951136545078732,209.0
0.002,6000,0.0398333333333333,0.003381635886214096,238.99999999999977
0.0025,2000,0.108,0.009478884979367552,216.0
0.003,2000,0.241,0.022717441549556572,482.0
0.0035,2000,0.427,0.04534551221126004,854.0
0.004,2000,0.616,0.07666151943586219,1232.0
1 physical_p num_trials LER LER_per_round num_errors
2 0.001 66000 0.0031060606060606 0.0002592076019299894 204.9999999999996
3 0.0015 16000 0.0130625 0.0010951136545078732 209.0
4 0.002 6000 0.0398333333333333 0.003381635886214096 238.99999999999977
5 0.0025 2000 0.108 0.009478884979367552 216.0
6 0.003 2000 0.241 0.022717441549556572 482.0
7 0.0035 2000 0.427 0.04534551221126004 854.0
8 0.004 2000 0.616 0.07666151943586219 1232.0

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@@ -0,0 +1,8 @@
physical_p,num_trials,LER,LER_per_round,num_errors
0.001,2000,0.632,0.07993046327730713,1264.0
0.0015,2000,0.7685,0.11479080536457342,1537.0
0.002,2000,0.8905,0.16832973055592892,1781.0
0.0025,2000,0.9405,0.2095463416012857,1881.0
0.003,2000,0.9765,0.26843039175484296,1953.0
0.0035,2000,0.993,0.33865993052589327,1986.0
0.004,2000,0.995,0.3569459165824279,1990.0
1 physical_p num_trials LER LER_per_round num_errors
2 0.001 2000 0.632 0.07993046327730713 1264.0
3 0.0015 2000 0.7685 0.11479080536457342 1537.0
4 0.002 2000 0.8905 0.16832973055592892 1781.0
5 0.0025 2000 0.9405 0.2095463416012857 1881.0
6 0.003 2000 0.9765 0.26843039175484296 1953.0
7 0.0035 2000 0.993 0.33865993052589327 1986.0
8 0.004 2000 0.995 0.3569459165824279 1990.0

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@@ -0,0 +1,8 @@
physical_p,num_trials,LER,LER_per_round,num_errors
0.001,6000,0.0343333333333333,0.0029071468641445053,205.9999999999998
0.0015,4000,0.09775,0.008535335041573222,391.0
0.002,2000,0.2005,0.018474608554528427,401.0
0.0025,2000,0.347,0.03489159369123396,694.0
0.003,2000,0.559,0.06595052116772404,1118.0
0.0035,2000,0.735,0.1047647873005133,1470.0
0.004,2000,0.867,0.15474521742325598,1734.0
1 physical_p num_trials LER LER_per_round num_errors
2 0.001 6000 0.0343333333333333 0.0029071468641445053 205.9999999999998
3 0.0015 4000 0.09775 0.008535335041573222 391.0
4 0.002 2000 0.2005 0.018474608554528427 401.0
5 0.0025 2000 0.347 0.03489159369123396 694.0
6 0.003 2000 0.559 0.06595052116772404 1118.0
7 0.0035 2000 0.735 0.1047647873005133 1470.0
8 0.004 2000 0.867 0.15474521742325598 1734.0

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@@ -0,0 +1,8 @@
physical_p,num_trials,LER,LER_per_round,num_errors
0.001,34000,0.0061176470588235,0.0005112389838239917,207.999999999999
0.0015,12000,0.0199166666666666,0.0016750685805796417,238.9999999999992
0.002,4000,0.05925,0.005076889602981138,237.0
0.0025,2000,0.1465,0.013114062821618089,293.0
0.003,2000,0.297,0.028939525764745788,594.0
0.0035,2000,0.4765,0.05250617012872005,953.0
0.004,2000,0.664,0.08687912132657749,1328.0
1 physical_p num_trials LER LER_per_round num_errors
2 0.001 34000 0.0061176470588235 0.0005112389838239917 207.999999999999
3 0.0015 12000 0.0199166666666666 0.0016750685805796417 238.9999999999992
4 0.002 4000 0.05925 0.005076889602981138 237.0
5 0.0025 2000 0.1465 0.013114062821618089 293.0
6 0.003 2000 0.297 0.028939525764745788 594.0
7 0.0035 2000 0.4765 0.05250617012872005 953.0
8 0.004 2000 0.664 0.08687912132657749 1328.0

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@@ -0,0 +1,8 @@
physical_p,num_trials,LER,LER_per_round,num_errors
0.001,4000,0.08375,0.0072623363421430165,335.0
0.0015,2000,0.17,0.015407535303274322,340.0
0.002,2000,0.333,0.03318402118027908,666.0
0.0025,2000,0.5225,0.05974038898813494,1045.0
0.003,2000,0.7125,0.09866447739264284,1425.0
0.0035,2000,0.8475,0.14505307692276814,1695.0
0.004,2000,0.936,0.20472927123294937,1872.0
1 physical_p num_trials LER LER_per_round num_errors
2 0.001 4000 0.08375 0.0072623363421430165 335.0
3 0.0015 2000 0.17 0.015407535303274322 340.0
4 0.002 2000 0.333 0.03318402118027908 666.0
5 0.0025 2000 0.5225 0.05974038898813494 1045.0
6 0.003 2000 0.7125 0.09866447739264284 1425.0
7 0.0035 2000 0.8475 0.14505307692276814 1695.0
8 0.004 2000 0.936 0.20472927123294937 1872.0

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@@ -0,0 +1,8 @@
physical_p,num_trials,LER,LER_per_round,num_errors
0.001,4000,0.05375,0.00459345717599724,215.0
0.0015,2000,0.137,0.012203310556051061,274.0
0.002,2000,0.248,0.023471730814805247,496.0
0.0025,2000,0.424,0.044929992453897394,848.0
0.003,2000,0.6005,0.07361169169753423,1201.0
0.0035,2000,0.7845,0.12005821823758633,1569.0
0.004,2000,0.9005,0.1749405238157723,1801.0
1 physical_p num_trials LER LER_per_round num_errors
2 0.001 4000 0.05375 0.00459345717599724 215.0
3 0.0015 2000 0.137 0.012203310556051061 274.0
4 0.002 2000 0.248 0.023471730814805247 496.0
5 0.0025 2000 0.424 0.044929992453897394 848.0
6 0.003 2000 0.6005 0.07361169169753423 1201.0
7 0.0035 2000 0.7845 0.12005821823758633 1569.0
8 0.004 2000 0.9005 0.1749405238157723 1801.0

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@@ -0,0 +1,8 @@
physical_p,num_trials,LER,LER_per_round,num_errors
0.001,4000,0.0555,0.004746996564855888,222.0
0.0015,2000,0.122,0.010783823589648356,244.0
0.002,2000,0.228,0.02133338177466315,456.0
0.0025,2000,0.3975,0.041343353576980935,795.0
0.003,2000,0.577,0.06918859214518802,1154.0
0.0035,2000,0.7605,0.11228111333332969,1521.0
0.004,2000,0.8835,0.16402396604923497,1767.0
1 physical_p num_trials LER LER_per_round num_errors
2 0.001 4000 0.0555 0.004746996564855888 222.0
3 0.0015 2000 0.122 0.010783823589648356 244.0
4 0.002 2000 0.228 0.02133338177466315 456.0
5 0.0025 2000 0.3975 0.041343353576980935 795.0
6 0.003 2000 0.577 0.06918859214518802 1154.0
7 0.0035 2000 0.7605 0.11228111333332969 1521.0
8 0.004 2000 0.8835 0.16402396604923497 1767.0

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@@ -0,0 +1,8 @@
physical_p,num_trials,LER,LER_per_round,num_errors
0.001,2000,0.1275,0.011301702536387737,255.0
0.0015,2000,0.2445,0.023093785381261167,489.0
0.002,2000,0.471,0.05168059078836085,942.0
0.0025,2000,0.6925,0.09359889423026135,1385.0
0.003,2000,0.83,0.13727825732341103,1660.0
0.0035,2000,0.927,0.19596138832598886,1854.0
0.004,2000,0.9745,0.2634339765587691,1949.0
1 physical_p num_trials LER LER_per_round num_errors
2 0.001 2000 0.1275 0.011301702536387737 255.0
3 0.0015 2000 0.2445 0.023093785381261167 489.0
4 0.002 2000 0.471 0.05168059078836085 942.0
5 0.0025 2000 0.6925 0.09359889423026135 1385.0
6 0.003 2000 0.83 0.13727825732341103 1660.0
7 0.0035 2000 0.927 0.19596138832598886 1854.0
8 0.004 2000 0.9745 0.2634339765587691 1949.0

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@@ -0,0 +1,8 @@
physical_p,num_trials,LER,LER_per_round,num_errors
0.001,4000,0.05525,0.004725046408614819,221.0
0.0015,2000,0.133,0.011822582694107964,266.0
0.002,2000,0.2755,0.026498707449347236,551.0
0.0025,2000,0.462,0.050346464045528894,924.0
0.003,2000,0.641,0.08182695829978004,1282.0
0.0035,2000,0.8035,0.12680036354194668,1607.0
0.004,2000,0.9095,0.18143334698302127,1819.0
1 physical_p num_trials LER LER_per_round num_errors
2 0.001 4000 0.05525 0.004725046408614819 221.0
3 0.0015 2000 0.133 0.011822582694107964 266.0
4 0.002 2000 0.2755 0.026498707449347236 551.0
5 0.0025 2000 0.462 0.050346464045528894 924.0
6 0.003 2000 0.641 0.08182695829978004 1282.0
7 0.0035 2000 0.8035 0.12680036354194668 1607.0
8 0.004 2000 0.9095 0.18143334698302127 1819.0

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@@ -0,0 +1,8 @@
physical_p,num_trials,LER,LER_per_round,num_errors
0.001,6000,0.048,0.004090796817048492,288.0
0.0015,2000,0.115,0.010128988904076097,230.0
0.002,2000,0.2155,0.02002255762528382,431.0
0.0025,2000,0.402,0.04194208019539358,804.0
0.003,2000,0.577,0.06918859214518802,1154.0
0.0035,2000,0.764,0.11336949998487811,1528.0
0.004,2000,0.897,0.17256014533992214,1794.0
1 physical_p num_trials LER LER_per_round num_errors
2 0.001 6000 0.048 0.004090796817048492 288.0
3 0.0015 2000 0.115 0.010128988904076097 230.0
4 0.002 2000 0.2155 0.02002255762528382 431.0
5 0.0025 2000 0.402 0.04194208019539358 804.0
6 0.003 2000 0.577 0.06918859214518802 1154.0
7 0.0035 2000 0.764 0.11336949998487811 1528.0
8 0.004 2000 0.897 0.17256014533992214 1794.0

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@@ -0,0 +1,8 @@
physical_p,num_trials,LER,LER_per_round,num_errors
0.001,2000,0.6955,0.09433912151694923,1391.0
0.0015,2000,0.816,0.13156999840650407,1632.0
0.002,2000,0.9215,0.19107956872744314,1843.0
0.0025,2000,0.9595,0.2344834483240309,1919.0
0.003,2000,0.9895,0.31593226271987895,1979.0
0.0035,2000,0.997,0.3837454986270925,1994.0
0.004,2000,0.999,0.4376586748096508,1998.0
1 physical_p num_trials LER LER_per_round num_errors
2 0.001 2000 0.6955 0.09433912151694923 1391.0
3 0.0015 2000 0.816 0.13156999840650407 1632.0
4 0.002 2000 0.9215 0.19107956872744314 1843.0
5 0.0025 2000 0.9595 0.2344834483240309 1919.0
6 0.003 2000 0.9895 0.31593226271987895 1979.0
7 0.0035 2000 0.997 0.3837454986270925 1994.0
8 0.004 2000 0.999 0.4376586748096508 1998.0

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@@ -0,0 +1,8 @@
physical_p,num_trials,LER,LER_per_round,num_errors
0.001,4000,0.09425,0.0082153967557419,377.0
0.0015,2000,0.206,0.019039074473767514,412.0
0.002,2000,0.371,0.03789851025936897,742.0
0.0025,2000,0.5865,0.07094884804525436,1173.0
0.003,2000,0.7685,0.11479080536457342,1537.0
0.0035,2000,0.8965,0.17222616291377513,1793.0
0.004,2000,0.9575,0.2314023053376273,1915.0
1 physical_p num_trials LER LER_per_round num_errors
2 0.001 4000 0.09425 0.0082153967557419 377.0
3 0.0015 2000 0.206 0.019039074473767514 412.0
4 0.002 2000 0.371 0.03789851025936897 742.0
5 0.0025 2000 0.5865 0.07094884804525436 1173.0
6 0.003 2000 0.7685 0.11479080536457342 1537.0
7 0.0035 2000 0.8965 0.17222616291377513 1793.0
8 0.004 2000 0.9575 0.2314023053376273 1915.0

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@@ -0,0 +1,8 @@
physical_p,num_trials,LER,LER_per_round,num_errors
0.001,6000,0.0488333333333333,0.004163473418041463,292.9999999999998
0.0015,2000,0.1225,0.01083078042647323,245.0
0.002,2000,0.2435,0.022986095764761516,487.0
0.0025,2000,0.4055,0.042410618607193085,811.0
0.003,2000,0.5965,0.07284225986971693,1193.0
0.0035,2000,0.7945,0.12353552306518623,1589.0
0.004,2000,0.9,0.1745958147319816,1800.0
1 physical_p num_trials LER LER_per_round num_errors
2 0.001 6000 0.0488333333333333 0.004163473418041463 292.9999999999998
3 0.0015 2000 0.1225 0.01083078042647323 245.0
4 0.002 2000 0.2435 0.022986095764761516 487.0
5 0.0025 2000 0.4055 0.042410618607193085 811.0
6 0.003 2000 0.5965 0.07284225986971693 1193.0
7 0.0035 2000 0.7945 0.12353552306518623 1589.0
8 0.004 2000 0.9 0.1745958147319816 1800.0

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@@ -0,0 +1,8 @@
physical_p,num_trials,LER,LER_per_round,num_errors
0.001,8000,0.033,0.0027924923467828044,264.0
0.0015,4000,0.0885,0.0076922358935922475,354.0
0.002,2000,0.189,0.01730577346851303,378.0
0.0025,2000,0.386,0.039831698576282215,772.0
0.003,2000,0.5745,0.06873139184884758,1149.0
0.0035,2000,0.7675,0.11447278468704636,1535.0
0.004,2000,0.8925,0.16960631326972486,1785.0
1 physical_p num_trials LER LER_per_round num_errors
2 0.001 8000 0.033 0.0027924923467828044 264.0
3 0.0015 4000 0.0885 0.0076922358935922475 354.0
4 0.002 2000 0.189 0.01730577346851303 378.0
5 0.0025 2000 0.386 0.039831698576282215 772.0
6 0.003 2000 0.5745 0.06873139184884758 1149.0
7 0.0035 2000 0.7675 0.11447278468704636 1535.0
8 0.004 2000 0.8925 0.16960631326972486 1785.0

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@@ -0,0 +1,8 @@
physical_p,num_trials,LER,LER_per_round,num_errors
0.001,16000,0.013375,0.0011214749225721965,214.0
0.0015,6000,0.0436666666666666,0.0037138159693325123,261.9999999999996
0.002,2000,0.1125,0.009896269575755956,225.0
0.0025,2000,0.2375,0.022342685193895928,475.0
0.003,2000,0.4105,0.04308436449639608,821.0
0.0035,2000,0.621,0.07766943516436708,1242.0
0.004,2000,0.799,0.125151191269673,1598.0
1 physical_p num_trials LER LER_per_round num_errors
2 0.001 16000 0.013375 0.0011214749225721965 214.0
3 0.0015 6000 0.0436666666666666 0.0037138159693325123 261.9999999999996
4 0.002 2000 0.1125 0.009896269575755956 225.0
5 0.0025 2000 0.2375 0.022342685193895928 475.0
6 0.003 2000 0.4105 0.04308436449639608 821.0
7 0.0035 2000 0.621 0.07766943516436708 1242.0
8 0.004 2000 0.799 0.125151191269673 1598.0

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@@ -0,0 +1,8 @@
physical_p,num_trials,LER,LER_per_round,num_errors
0.001,20000,0.01,0.0008371773591205889,200.0
0.0015,8000,0.02975,0.002513627927773654,238.0
0.002,4000,0.08025,0.0069468735550100025,321.0
0.0025,2000,0.2055,0.018987611527110704,411.0
0.003,2000,0.3465,0.03483003359216841,693.0
0.0035,2000,0.556,0.06542265847616091,1112.0
0.004,2000,0.738,0.1056137629395989,1476.0
1 physical_p num_trials LER LER_per_round num_errors
2 0.001 20000 0.01 0.0008371773591205889 200.0
3 0.0015 8000 0.02975 0.002513627927773654 238.0
4 0.002 4000 0.08025 0.0069468735550100025 321.0
5 0.0025 2000 0.2055 0.018987611527110704 411.0
6 0.003 2000 0.3465 0.03483003359216841 693.0
7 0.0035 2000 0.556 0.06542265847616091 1112.0
8 0.004 2000 0.738 0.1056137629395989 1476.0

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@@ -0,0 +1,8 @@
physical_p,num_trials,LER,LER_per_round,num_errors
0.001,4000,0.102,0.008925364554660087,408.0
0.0015,2000,0.234,0.02196950237720341,468.0
0.002,2000,0.433,0.04618256897389805,866.0
0.0025,2000,0.6455,0.08279160735454238,1291.0
0.003,2000,0.82,0.13315913781420163,1640.0
0.0035,2000,0.922,0.19151019058730434,1844.0
0.004,2000,0.9805,0.2797174651647023,1961.0
1 physical_p num_trials LER LER_per_round num_errors
2 0.001 4000 0.102 0.008925364554660087 408.0
3 0.0015 2000 0.234 0.02196950237720341 468.0
4 0.002 2000 0.433 0.04618256897389805 866.0
5 0.0025 2000 0.6455 0.08279160735454238 1291.0
6 0.003 2000 0.82 0.13315913781420163 1640.0
7 0.0035 2000 0.922 0.19151019058730434 1844.0
8 0.004 2000 0.9805 0.2797174651647023 1961.0

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@@ -0,0 +1,8 @@
physical_p,num_trials,LER,LER_per_round,num_errors
0.001,6000,0.0355,0.0030075886692517706,212.99999999999997
0.0015,4000,0.0835,0.007239766684647431,334.0
0.002,2000,0.2025,0.018679455867679495,405.0
0.0025,2000,0.3635,0.036947712076332184,727.0
0.003,2000,0.5605,0.06621568805942701,1121.0
0.0035,2000,0.749,0.10880485867108969,1498.0
0.004,2000,0.8895,0.1676994342621433,1779.0
1 physical_p num_trials LER LER_per_round num_errors
2 0.001 6000 0.0355 0.0030075886692517706 212.99999999999997
3 0.0015 4000 0.0835 0.007239766684647431 334.0
4 0.002 2000 0.2025 0.018679455867679495 405.0
5 0.0025 2000 0.3635 0.036947712076332184 727.0
6 0.003 2000 0.5605 0.06621568805942701 1121.0
7 0.0035 2000 0.749 0.10880485867108969 1498.0
8 0.004 2000 0.8895 0.1676994342621433 1779.0

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@@ -0,0 +1,8 @@
physical_p,num_trials,LER,LER_per_round,num_errors
0.001,12000,0.0174166666666666,0.0014631053822830031,208.9999999999992
0.0015,4000,0.051,0.004352706093600722,204.0
0.002,2000,0.1315,0.011680224751058454,263.0
0.0025,2000,0.281,0.02711671729858034,562.0
0.003,2000,0.46,0.050052771570453625,920.0
0.0035,2000,0.662,0.08642741539493726,1324.0
0.004,2000,0.8145,0.13098222531638515,1629.0
1 physical_p num_trials LER LER_per_round num_errors
2 0.001 12000 0.0174166666666666 0.0014631053822830031 208.9999999999992
3 0.0015 4000 0.051 0.004352706093600722 204.0
4 0.002 2000 0.1315 0.011680224751058454 263.0
5 0.0025 2000 0.281 0.02711671729858034 562.0
6 0.003 2000 0.46 0.050052771570453625 920.0
7 0.0035 2000 0.662 0.08642741539493726 1324.0
8 0.004 2000 0.8145 0.13098222531638515 1629.0

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@@ -0,0 +1,8 @@
physical_p,num_trials,LER,LER_per_round,num_errors
0.001,2000,0.6955,0.09433912151694923,1391.0
0.0015,2000,0.816,0.13156999840650407,1632.0
0.002,2000,0.9215,0.19107956872744314,1843.0
0.0025,2000,0.9595,0.2344834483240309,1919.0
0.003,2000,0.9895,0.31593226271987895,1979.0
0.0035,2000,0.997,0.3837454986270925,1994.0
0.004,2000,0.999,0.4376586748096508,1998.0
1 physical_p num_trials LER LER_per_round num_errors
2 0.001 2000 0.6955 0.09433912151694923 1391.0
3 0.0015 2000 0.816 0.13156999840650407 1632.0
4 0.002 2000 0.9215 0.19107956872744314 1843.0
5 0.0025 2000 0.9595 0.2344834483240309 1919.0
6 0.003 2000 0.9895 0.31593226271987895 1979.0
7 0.0035 2000 0.997 0.3837454986270925 1994.0
8 0.004 2000 0.999 0.4376586748096508 1998.0

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@@ -0,0 +1,8 @@
physical_p,num_trials,LER,LER_per_round,num_errors
0.001,4000,0.087,0.0075562567245422985,348.0
0.0015,2000,0.2025,0.018679455867679495,405.0
0.002,2000,0.3515,0.035447587291447924,703.0
0.0025,2000,0.5605,0.06621568805942701,1121.0
0.003,2000,0.766,0.11399809680348838,1532.0
0.0035,2000,0.896,0.1718936562142762,1792.0
0.004,2000,0.9535,0.22561949205779908,1907.0
1 physical_p num_trials LER LER_per_round num_errors
2 0.001 4000 0.087 0.0075562567245422985 348.0
3 0.0015 2000 0.2025 0.018679455867679495 405.0
4 0.002 2000 0.3515 0.035447587291447924 703.0
5 0.0025 2000 0.5605 0.06621568805942701 1121.0
6 0.003 2000 0.766 0.11399809680348838 1532.0
7 0.0035 2000 0.896 0.1718936562142762 1792.0
8 0.004 2000 0.9535 0.22561949205779908 1907.0

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@@ -0,0 +1,8 @@
physical_p,num_trials,LER,LER_per_round,num_errors
0.001,6000,0.0341666666666666,0.0028928071163165647,204.9999999999996
0.0015,4000,0.0915,0.007964810720254789,366.0
0.002,2000,0.202,0.018628199928893086,404.0
0.0025,2000,0.3685,0.03758042822058505,737.0
0.003,2000,0.562,0.06648168584179992,1124.0
0.0035,2000,0.7435,0.10719362881586803,1487.0
0.004,2000,0.876,0.15966624844871136,1752.0
1 physical_p num_trials LER LER_per_round num_errors
2 0.001 6000 0.0341666666666666 0.0028928071163165647 204.9999999999996
3 0.0015 4000 0.0915 0.007964810720254789 366.0
4 0.002 2000 0.202 0.018628199928893086 404.0
5 0.0025 2000 0.3685 0.03758042822058505 737.0
6 0.003 2000 0.562 0.06648168584179992 1124.0
7 0.0035 2000 0.7435 0.10719362881586803 1487.0
8 0.004 2000 0.876 0.15966624844871136 1752.0

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@@ -0,0 +1,8 @@
physical_p,num_trials,LER,LER_per_round,num_errors
0.001,24000,0.008875,0.0007426089118820478,212.99999999999997
0.0015,8000,0.027375,0.002310383366790014,219.0
0.002,4000,0.0805,0.006969370086301163,322.0
0.0025,2000,0.1765,0.016052408593168255,353.0
0.003,2000,0.321,0.03174633874742727,642.0
0.0035,2000,0.5295,0.06089683913260491,1059.0
0.004,2000,0.703,0.09621935287123151,1406.0
1 physical_p num_trials LER LER_per_round num_errors
2 0.001 24000 0.008875 0.0007426089118820478 212.99999999999997
3 0.0015 8000 0.027375 0.002310383366790014 219.0
4 0.002 4000 0.0805 0.006969370086301163 322.0
5 0.0025 2000 0.1765 0.016052408593168255 353.0
6 0.003 2000 0.321 0.03174633874742727 642.0
7 0.0035 2000 0.5295 0.06089683913260491 1059.0
8 0.004 2000 0.703 0.09621935287123151 1406.0

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@@ -0,0 +1,8 @@
physical_p,num_trials,LER,LER_per_round,num_errors
0.001,100000,0.0018,0.00015012389249957625,180.0
0.0015,30000,0.0071666666666666,0.000599192960614614,214.999999999998
0.002,8000,0.026125,0.0022035952056765895,209.0
0.0025,4000,0.08375,0.0072623363421430165,335.0
0.003,2000,0.184,0.016802316683105167,368.0
0.0035,2000,0.344,0.0345228792367418,688.0
0.004,2000,0.5175,0.058923829667395955,1035.0
1 physical_p num_trials LER LER_per_round num_errors
2 0.001 100000 0.0018 0.00015012389249957625 180.0
3 0.0015 30000 0.0071666666666666 0.000599192960614614 214.999999999998
4 0.002 8000 0.026125 0.0022035952056765895 209.0
5 0.0025 4000 0.08375 0.0072623363421430165 335.0
6 0.003 2000 0.184 0.016802316683105167 368.0
7 0.0035 2000 0.344 0.0345228792367418 688.0
8 0.004 2000 0.5175 0.058923829667395955 1035.0

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@@ -0,0 +1,8 @@
physical_p,num_trials,LER,LER_per_round,num_errors
0.001,100000,0.0007,5.83520569852336e-05,70.0
0.0015,62000,0.003258064516129,0.0002719116557121648,201.999999999998
0.002,16000,0.013,0.0010898423190723872,208.0
0.0025,6000,0.0468333333333333,0.0039891474854014675,280.99999999999983
0.003,2000,0.1165,0.010268909922777514,233.0
0.0035,2000,0.2525,0.023960037096822373,505.0
0.004,2000,0.4255,0.04513750370753944,851.0
1 physical_p num_trials LER LER_per_round num_errors
2 0.001 100000 0.0007 5.83520569852336e-05 70.0
3 0.0015 62000 0.003258064516129 0.0002719116557121648 201.999999999998
4 0.002 16000 0.013 0.0010898423190723872 208.0
5 0.0025 6000 0.0468333333333333 0.0039891474854014675 280.99999999999983
6 0.003 2000 0.1165 0.010268909922777514 233.0
7 0.0035 2000 0.2525 0.023960037096822373 505.0
8 0.004 2000 0.4255 0.04513750370753944 851.0

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@@ -0,0 +1,8 @@
physical_p,num_trials,LER,LER_per_round,num_errors
0.001,6000,0.0453333333333333,0.0038586229394146354,271.99999999999983
0.0015,4000,0.09175,0.007987562516493574,367.0
0.002,2000,0.199,0.018321281103642173,398.0
0.0025,2000,0.362,0.036758785596775034,724.0
0.003,2000,0.5155,0.058599376123828484,1031.0
0.0035,2000,0.7085,0.09762605599754803,1417.0
0.004,2000,0.856,0.149129354542893,1712.0
1 physical_p num_trials LER LER_per_round num_errors
2 0.001 6000 0.0453333333333333 0.0038586229394146354 271.99999999999983
3 0.0015 4000 0.09175 0.007987562516493574 367.0
4 0.002 2000 0.199 0.018321281103642173 398.0
5 0.0025 2000 0.362 0.036758785596775034 724.0
6 0.003 2000 0.5155 0.058599376123828484 1031.0
7 0.0035 2000 0.7085 0.09762605599754803 1417.0
8 0.004 2000 0.856 0.149129354542893 1712.0

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@@ -0,0 +1,8 @@
physical_p,num_trials,LER,LER_per_round,num_errors
0.001,44000,0.0045454545454545,0.00037957931952325996,199.999999999998
0.0015,16000,0.014625,0.001226996590199092,234.0
0.002,6000,0.046,0.003916610622698213,276.0
0.0025,2000,0.128,0.011348930715916694,256.0
0.003,2000,0.239,0.022503101573992157,478.0
0.0035,2000,0.4195,0.044310417497246735,839.0
0.004,2000,0.5965,0.07284225986971693,1193.0
1 physical_p num_trials LER LER_per_round num_errors
2 0.001 44000 0.0045454545454545 0.00037957931952325996 199.999999999998
3 0.0015 16000 0.014625 0.001226996590199092 234.0
4 0.002 6000 0.046 0.003916610622698213 276.0
5 0.0025 2000 0.128 0.011348930715916694 256.0
6 0.003 2000 0.239 0.022503101573992157 478.0
7 0.0035 2000 0.4195 0.044310417497246735 839.0
8 0.004 2000 0.5965 0.07284225986971693 1193.0

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@@ -0,0 +1,8 @@
physical_p,num_trials,LER,LER_per_round,num_errors
0.001,100000,0.00122,0.00010172355962756452,122.0
0.0015,42000,0.0047857142857142,0.0003996869775206857,200.9999999999964
0.002,12000,0.0196666666666666,0.001653849971735899,235.9999999999992
0.0025,4000,0.066,0.0056737465539274945,264.0
0.003,2000,0.1485,0.01330698362831062,297.0
0.0035,2000,0.3085,0.03027331056488236,617.0
0.004,2000,0.473,0.05197988715416113,946.0
1 physical_p num_trials LER LER_per_round num_errors
2 0.001 100000 0.00122 0.00010172355962756452 122.0
3 0.0015 42000 0.0047857142857142 0.0003996869775206857 200.9999999999964
4 0.002 12000 0.0196666666666666 0.001653849971735899 235.9999999999992
5 0.0025 4000 0.066 0.0056737465539274945 264.0
6 0.003 2000 0.1485 0.01330698362831062 297.0
7 0.0035 2000 0.3085 0.03027331056488236 617.0
8 0.004 2000 0.473 0.05197988715416113 946.0

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@@ -0,0 +1,8 @@
physical_p,num_trials,LER,LER_per_round,num_errors
0.001,2000,0.626,0.07868961436921773,1252.0
0.0015,2000,0.7655,0.11384048722645845,1531.0
0.002,2000,0.8745,0.15882379851291006,1749.0
0.0025,2000,0.933,0.20168755384893544,1866.0
0.003,2000,0.972,0.2576708709890312,1944.0
0.0035,2000,0.985,0.29529459105967726,1970.0
0.004,2000,0.994,0.3471010990626149,1988.0
1 physical_p num_trials LER LER_per_round num_errors
2 0.001 2000 0.626 0.07868961436921773 1252.0
3 0.0015 2000 0.7655 0.11384048722645845 1531.0
4 0.002 2000 0.8745 0.15882379851291006 1749.0
5 0.0025 2000 0.933 0.20168755384893544 1866.0
6 0.003 2000 0.972 0.2576708709890312 1944.0
7 0.0035 2000 0.985 0.29529459105967726 1970.0
8 0.004 2000 0.994 0.3471010990626149 1988.0

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@@ -0,0 +1,8 @@
physical_p,num_trials,LER,LER_per_round,num_errors
0.001,8000,0.026875,0.0022676530141574336,215.0
0.0015,4000,0.06075,0.005209184439765924,243.0
0.002,2000,0.1275,0.011301702536387737,255.0
0.0025,2000,0.2435,0.022986095764761516,487.0
0.003,2000,0.4095,0.04294919734292335,819.0
0.0035,2000,0.605,0.07448578964497943,1210.0
0.004,2000,0.767,0.11431424426031134,1534.0
1 physical_p num_trials LER LER_per_round num_errors
2 0.001 8000 0.026875 0.0022676530141574336 215.0
3 0.0015 4000 0.06075 0.005209184439765924 243.0
4 0.002 2000 0.1275 0.011301702536387737 255.0
5 0.0025 2000 0.2435 0.022986095764761516 487.0
6 0.003 2000 0.4095 0.04294919734292335 819.0
7 0.0035 2000 0.605 0.07448578964497943 1210.0
8 0.004 2000 0.767 0.11431424426031134 1534.0

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@@ -0,0 +1,8 @@
physical_p,num_trials,LER,LER_per_round,num_errors
0.001,68000,0.0030882352941176,0.00025771792946360783,209.9999999999968
0.0015,22000,0.0100454545454545,0.0008410003766037288,220.999999999999
0.002,6000,0.0353333333333333,0.0029932330235841187,211.9999999999998
0.0025,4000,0.08725,0.007578905691289939,349.0
0.003,2000,0.191,0.017507953228264928,382.0
0.0035,2000,0.3535,0.03569583157768186,707.0
0.004,2000,0.5215,0.059576452112257594,1043.0
1 physical_p num_trials LER LER_per_round num_errors
2 0.001 68000 0.0030882352941176 0.00025771792946360783 209.9999999999968
3 0.0015 22000 0.0100454545454545 0.0008410003766037288 220.999999999999
4 0.002 6000 0.0353333333333333 0.0029932330235841187 211.9999999999998
5 0.0025 4000 0.08725 0.007578905691289939 349.0
6 0.003 2000 0.191 0.017507953228264928 382.0
7 0.0035 2000 0.3535 0.03569583157768186 707.0
8 0.004 2000 0.5215 0.059576452112257594 1043.0

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@@ -0,0 +1,8 @@
physical_p,num_trials,LER,LER_per_round,num_errors
0.001,24000,0.00875,0.0007321073812772694,210.00000000000003
0.0015,8000,0.025125,0.00211825510203556,201.0
0.002,4000,0.0815,0.0070594123157259325,326.0
0.0025,2000,0.174,0.015803830077221748,348.0
0.003,2000,0.319,0.03150899241712146,638.0
0.0035,2000,0.5135,0.05827614798780856,1027.0
0.004,2000,0.7075,0.09736849218423416,1415.0
1 physical_p num_trials LER LER_per_round num_errors
2 0.001 24000 0.00875 0.0007321073812772694 210.00000000000003
3 0.0015 8000 0.025125 0.00211825510203556 201.0
4 0.002 4000 0.0815 0.0070594123157259325 326.0
5 0.0025 2000 0.174 0.015803830077221748 348.0
6 0.003 2000 0.319 0.03150899241712146 638.0
7 0.0035 2000 0.5135 0.05827614798780856 1027.0
8 0.004 2000 0.7075 0.09736849218423416 1415.0

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@@ -0,0 +1,8 @@
physical_p,num_trials,LER,LER_per_round,num_errors
0.001,100000,0.00146,0.00012174815796772709,146.0
0.0015,32000,0.0064375,0.000538047705478828,206.0
0.002,10000,0.0229,0.0019286609080385597,229.0
0.0025,4000,0.07525,0.006498116023036737,301.0
0.003,2000,0.1585,0.01427786270551501,317.0
0.0035,2000,0.3395,0.033972695445756096,679.0
0.004,2000,0.4985,0.055890042576412724,997.0
1 physical_p num_trials LER LER_per_round num_errors
2 0.001 100000 0.00146 0.00012174815796772709 146.0
3 0.0015 32000 0.0064375 0.000538047705478828 206.0
4 0.002 10000 0.0229 0.0019286609080385597 229.0
5 0.0025 4000 0.07525 0.006498116023036737 301.0
6 0.003 2000 0.1585 0.01427786270551501 317.0
7 0.0035 2000 0.3395 0.033972695445756096 679.0
8 0.004 2000 0.4985 0.055890042576412724 997.0

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@@ -0,0 +1,8 @@
physical_p,num_trials,LER,LER_per_round,num_errors
0.001,100000,0.0004,3.3339446006586115e-05,40.0
0.0015,72000,0.0027916666666666,0.0002329370855657098,200.9999999999952
0.002,18000,0.0121666666666666,0.0010195870693898712,218.9999999999988
0.0025,6000,0.0435,0.0036993479983105093,261.0
0.003,4000,0.097,0.00846668118140581,388.0
0.0035,2000,0.2385,0.022449597267178878,477.0
0.004,2000,0.4015,0.04187535144908072,803.0
1 physical_p num_trials LER LER_per_round num_errors
2 0.001 100000 0.0004 3.3339446006586115e-05 40.0
3 0.0015 72000 0.0027916666666666 0.0002329370855657098 200.9999999999952
4 0.002 18000 0.0121666666666666 0.0010195870693898712 218.9999999999988
5 0.0025 6000 0.0435 0.0036993479983105093 261.0
6 0.003 4000 0.097 0.00846668118140581 388.0
7 0.0035 2000 0.2385 0.022449597267178878 477.0
8 0.004 2000 0.4015 0.04187535144908072 803.0

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@@ -0,0 +1,8 @@
physical_p,num_trials,LER,LER_per_round,num_errors
0.001,6000,0.038,0.003223196672329065,228.0
0.0015,4000,0.098,0.008558231287084661,392.0
0.002,2000,0.206,0.019039074473767514,412.0
0.0025,2000,0.3485,0.035076533583668024,697.0
0.003,2000,0.5245,0.060069209055131356,1049.0
0.0035,2000,0.6985,0.09508606438098832,1397.0
0.004,2000,0.8495,0.14599310907967555,1699.0
1 physical_p num_trials LER LER_per_round num_errors
2 0.001 6000 0.038 0.003223196672329065 228.0
3 0.0015 4000 0.098 0.008558231287084661 392.0
4 0.002 2000 0.206 0.019039074473767514 412.0
5 0.0025 2000 0.3485 0.035076533583668024 697.0
6 0.003 2000 0.5245 0.060069209055131356 1049.0
7 0.0035 2000 0.6985 0.09508606438098832 1397.0
8 0.004 2000 0.8495 0.14599310907967555 1699.0

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@@ -0,0 +1,8 @@
physical_p,num_trials,LER,LER_per_round,num_errors
0.001,46000,0.004391304347826,0.0003666806266127143,201.99999999999602
0.0015,14000,0.0164285714285714,0.001379465734122176,229.9999999999996
0.002,6000,0.0438333333333333,0.003728286251850954,262.99999999999983
0.0025,2000,0.118,0.010409048871669824,236.0
0.003,2000,0.228,0.02133338177466315,456.0
0.0035,2000,0.4185,0.04417333224775788,837.0
0.004,2000,0.594,0.07236490793227202,1188.0
1 physical_p num_trials LER LER_per_round num_errors
2 0.001 46000 0.004391304347826 0.0003666806266127143 201.99999999999602
3 0.0015 14000 0.0164285714285714 0.001379465734122176 229.9999999999996
4 0.002 6000 0.0438333333333333 0.003728286251850954 262.99999999999983
5 0.0025 2000 0.118 0.010409048871669824 236.0
6 0.003 2000 0.228 0.02133338177466315 456.0
7 0.0035 2000 0.4185 0.04417333224775788 837.0
8 0.004 2000 0.594 0.07236490793227202 1188.0

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@@ -0,0 +1,8 @@
physical_p,num_trials,LER,LER_per_round,num_errors
0.001,100000,0.00095,7.920115808901507e-05,95.0
0.0015,42000,0.0050238095238095,0.00041961787574185117,210.999999999999
0.002,12000,0.01975,0.0016609222901676768,237.0
0.0025,4000,0.062,0.005319578163374583,248.0
0.003,2000,0.159,0.014326683792962536,318.0
0.0035,2000,0.313,0.030800767790453154,626.0
0.004,2000,0.47,0.0515313313739999,940.0
1 physical_p num_trials LER LER_per_round num_errors
2 0.001 100000 0.00095 7.920115808901507e-05 95.0
3 0.0015 42000 0.0050238095238095 0.00041961787574185117 210.999999999999
4 0.002 12000 0.01975 0.0016609222901676768 237.0
5 0.0025 4000 0.062 0.005319578163374583 248.0
6 0.003 2000 0.159 0.014326683792962536 318.0
7 0.0035 2000 0.313 0.030800767790453154 626.0
8 0.004 2000 0.47 0.0515313313739999 940.0

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@@ -0,0 +1,8 @@
physical_p,num_trials,LER,LER_per_round,num_errors
0.001,2000,0.626,0.07868961436921773,1252.0
0.0015,2000,0.7655,0.11384048722645845,1531.0
0.002,2000,0.8745,0.15882379851291006,1749.0
0.0025,2000,0.933,0.20168755384893544,1866.0
0.003,2000,0.972,0.2576708709890312,1944.0
0.0035,2000,0.985,0.29529459105967726,1970.0
0.004,2000,0.994,0.3471010990626149,1988.0
1 physical_p num_trials LER LER_per_round num_errors
2 0.001 2000 0.626 0.07868961436921773 1252.0
3 0.0015 2000 0.7655 0.11384048722645845 1531.0
4 0.002 2000 0.8745 0.15882379851291006 1749.0
5 0.0025 2000 0.933 0.20168755384893544 1866.0
6 0.003 2000 0.972 0.2576708709890312 1944.0
7 0.0035 2000 0.985 0.29529459105967726 1970.0
8 0.004 2000 0.994 0.3471010990626149 1988.0

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@@ -0,0 +1,8 @@
physical_p,num_trials,LER,LER_per_round,num_errors
0.001,8000,0.026125,0.0022035952056765895,209.0
0.0015,4000,0.06075,0.005209184439765924,243.0
0.002,2000,0.136,0.012107977177767903,272.0
0.0025,2000,0.254,0.02412340479098629,508.0
0.003,2000,0.4115,0.043219741997103434,823.0
0.0035,2000,0.6,0.07351512752093081,1200.0
0.004,2000,0.7645,0.11352619006706066,1529.0
1 physical_p num_trials LER LER_per_round num_errors
2 0.001 8000 0.026125 0.0022035952056765895 209.0
3 0.0015 4000 0.06075 0.005209184439765924 243.0
4 0.002 2000 0.136 0.012107977177767903 272.0
5 0.0025 2000 0.254 0.02412340479098629 508.0
6 0.003 2000 0.4115 0.043219741997103434 823.0
7 0.0035 2000 0.6 0.07351512752093081 1200.0
8 0.004 2000 0.7645 0.11352619006706066 1529.0

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@@ -0,0 +1,8 @@
physical_p,num_trials,LER,LER_per_round,num_errors
0.001,72000,0.0027777777777777,0.00023177671578233916,199.9999999999944
0.0015,20000,0.0105,0.0008792394039432994,210.0
0.002,8000,0.032125,0.0027173290492218394,257.0
0.0025,4000,0.08575,0.007443097095222506,343.0
0.003,2000,0.186,0.01700335914772977,372.0
0.0035,2000,0.356,0.03600712878727563,712.0
0.004,2000,0.529,0.06081371425997428,1058.0
1 physical_p num_trials LER LER_per_round num_errors
2 0.001 72000 0.0027777777777777 0.00023177671578233916 199.9999999999944
3 0.0015 20000 0.0105 0.0008792394039432994 210.0
4 0.002 8000 0.032125 0.0027173290492218394 257.0
5 0.0025 4000 0.08575 0.007443097095222506 343.0
6 0.003 2000 0.186 0.01700335914772977 372.0
7 0.0035 2000 0.356 0.03600712878727563 712.0
8 0.004 2000 0.529 0.06081371425997428 1058.0

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@@ -0,0 +1,8 @@
physical_p,num_trials,LER,LER_per_round,num_errors
0.001,6000,0.0453333333333333,0.0038586229394146354,271.99999999999983
0.0015,2000,0.1245,0.011018853369859305,249.0
0.002,2000,0.2185,0.02033539996612399,437.0
0.0025,2000,0.3975,0.041343353576980935,795.0
0.003,2000,0.5945,0.07246016235632424,1189.0
0.0035,2000,0.735,0.1047647873005133,1470.0
0.004,2000,0.8745,0.15882379851291006,1749.0
1 physical_p num_trials LER LER_per_round num_errors
2 0.001 6000 0.0453333333333333 0.0038586229394146354 271.99999999999983
3 0.0015 2000 0.1245 0.011018853369859305 249.0
4 0.002 2000 0.2185 0.02033539996612399 437.0
5 0.0025 2000 0.3975 0.041343353576980935 795.0
6 0.003 2000 0.5945 0.07246016235632424 1189.0
7 0.0035 2000 0.735 0.1047647873005133 1470.0
8 0.004 2000 0.8745 0.15882379851291006 1749.0

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@@ -0,0 +1,8 @@
physical_p,num_trials,LER,LER_per_round,num_errors
0.001,8000,0.030875,0.00261006088942628,247.0
0.0015,4000,0.07825,0.006767102824702054,313.0
0.002,2000,0.141,0.012585659483247746,282.0
0.0025,2000,0.279,0.02689148662280816,558.0
0.003,2000,0.4385,0.046957034683799304,877.0
0.0035,2000,0.633,0.08013907230132367,1266.0
0.004,2000,0.793,0.12300416913096102,1586.0
1 physical_p num_trials LER LER_per_round num_errors
2 0.001 8000 0.030875 0.00261006088942628 247.0
3 0.0015 4000 0.07825 0.006767102824702054 313.0
4 0.002 2000 0.141 0.012585659483247746 282.0
5 0.0025 2000 0.279 0.02689148662280816 558.0
6 0.003 2000 0.4385 0.046957034683799304 877.0
7 0.0035 2000 0.633 0.08013907230132367 1266.0
8 0.004 2000 0.793 0.12300416913096102 1586.0

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@@ -0,0 +1,8 @@
physical_p,num_trials,LER,LER_per_round,num_errors
0.001,8000,0.027625,0.0023317560946333193,221.0
0.0015,4000,0.06525,0.005607234208600653,261.0
0.002,2000,0.122,0.010783823589648356,244.0
0.0025,2000,0.2335,0.021916318194268203,467.0
0.003,2000,0.385,0.03970147975050575,770.0
0.0035,2000,0.569,0.0677341570379616,1138.0
0.004,2000,0.729,0.10309294344737896,1458.0
1 physical_p num_trials LER LER_per_round num_errors
2 0.001 8000 0.027625 0.0023317560946333193 221.0
3 0.0015 4000 0.06525 0.005607234208600653 261.0
4 0.002 2000 0.122 0.010783823589648356 244.0
5 0.0025 2000 0.2335 0.021916318194268203 467.0
6 0.003 2000 0.385 0.03970147975050575 770.0
7 0.0035 2000 0.569 0.0677341570379616 1138.0
8 0.004 2000 0.729 0.10309294344737896 1458.0

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@@ -0,0 +1,8 @@
physical_p,num_trials,LER,LER_per_round,num_errors
0.001,2000,0.122,0.010783823589648356,244.0
0.0015,2000,0.2475,0.02341764001219704,495.0
0.002,2000,0.38,0.039053282833609426,760.0
0.0025,2000,0.5705,0.06800496801270284,1141.0
0.003,2000,0.7255,0.10213330493021633,1451.0
0.0035,2000,0.846,0.14435544028130065,1692.0
0.004,2000,0.944,0.2135296839449985,1888.0
1 physical_p num_trials LER LER_per_round num_errors
2 0.001 2000 0.122 0.010783823589648356 244.0
3 0.0015 2000 0.2475 0.02341764001219704 495.0
4 0.002 2000 0.38 0.039053282833609426 760.0
5 0.0025 2000 0.5705 0.06800496801270284 1141.0
6 0.003 2000 0.7255 0.10213330493021633 1451.0
7 0.0035 2000 0.846 0.14435544028130065 1692.0
8 0.004 2000 0.944 0.2135296839449985 1888.0

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@@ -0,0 +1,8 @@
physical_p,num_trials,LER,LER_per_round,num_errors
0.001,6000,0.0375,0.00318003401506195,225.0
0.0015,4000,0.08775,0.007624220689530503,351.0
0.002,2000,0.169,0.015308735184581312,338.0
0.0025,2000,0.3185,0.03144975567894859,637.0
0.003,2000,0.4945,0.055264800927331104,989.0
0.0035,2000,0.6715,0.08859526368715209,1343.0
0.004,2000,0.8295,0.13706709042620446,1659.0
1 physical_p num_trials LER LER_per_round num_errors
2 0.001 6000 0.0375 0.00318003401506195 225.0
3 0.0015 4000 0.08775 0.007624220689530503 351.0
4 0.002 2000 0.169 0.015308735184581312 338.0
5 0.0025 2000 0.3185 0.03144975567894859 637.0
6 0.003 2000 0.4945 0.055264800927331104 989.0
7 0.0035 2000 0.6715 0.08859526368715209 1343.0
8 0.004 2000 0.8295 0.13706709042620446 1659.0

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@@ -0,0 +1,8 @@
physical_p,num_trials,LER,LER_per_round,num_errors
0.001,8000,0.029125,0.0024600983395249854,233.0
0.0015,4000,0.06525,0.005607234208600653,261.0
0.002,2000,0.129,0.011443461592906767,258.0
0.0025,2000,0.2545,0.02417792760750781,509.0
0.003,2000,0.416,0.043831562260356005,832.0
0.0035,2000,0.5905,0.07170112206446477,1181.0
0.004,2000,0.763,0.1130570306237979,1526.0
1 physical_p num_trials LER LER_per_round num_errors
2 0.001 8000 0.029125 0.0024600983395249854 233.0
3 0.0015 4000 0.06525 0.005607234208600653 261.0
4 0.002 2000 0.129 0.011443461592906767 258.0
5 0.0025 2000 0.2545 0.02417792760750781 509.0
6 0.003 2000 0.416 0.043831562260356005 832.0
7 0.0035 2000 0.5905 0.07170112206446477 1181.0
8 0.004 2000 0.763 0.1130570306237979 1526.0

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@@ -0,0 +1,8 @@
physical_p,num_trials,LER,LER_per_round,num_errors
0.001,2000,0.789,0.12160429293407071,1578.0
0.0015,2000,0.9,0.1745958147319816,1800.0
0.002,2000,0.9465,0.21651717275071503,1893.0
0.0025,2000,0.967,0.24743705884517853,1934.0
0.003,2000,0.9905,0.32161385879719506,1981.0
0.0035,2000,0.9965,0.3757780964762649,1993.0
0.004,2000,0.9995,0.4692204681934514,1999.0
1 physical_p num_trials LER LER_per_round num_errors
2 0.001 2000 0.789 0.12160429293407071 1578.0
3 0.0015 2000 0.9 0.1745958147319816 1800.0
4 0.002 2000 0.9465 0.21651717275071503 1893.0
5 0.0025 2000 0.967 0.24743705884517853 1934.0
6 0.003 2000 0.9905 0.32161385879719506 1981.0
7 0.0035 2000 0.9965 0.3757780964762649 1993.0
8 0.004 2000 0.9995 0.4692204681934514 1999.0

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@@ -0,0 +1,8 @@
physical_p,num_trials,LER,LER_per_round,num_errors
0.001,4000,0.09675,0.008443808176524459,387.0
0.0015,2000,0.1775,0.01615203373482954,355.0
0.002,2000,0.322,0.03186525232867321,644.0
0.0025,2000,0.4605,0.050126101092695885,921.0
0.003,2000,0.653,0.08442458415488852,1306.0
0.0035,2000,0.798,0.12478930891509032,1596.0
0.004,2000,0.912,0.18334199643064264,1824.0
1 physical_p num_trials LER LER_per_round num_errors
2 0.001 4000 0.09675 0.008443808176524459 387.0
3 0.0015 2000 0.1775 0.01615203373482954 355.0
4 0.002 2000 0.322 0.03186525232867321 644.0
5 0.0025 2000 0.4605 0.050126101092695885 921.0
6 0.003 2000 0.653 0.08442458415488852 1306.0
7 0.0035 2000 0.798 0.12478930891509032 1596.0
8 0.004 2000 0.912 0.18334199643064264 1824.0

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@@ -0,0 +1,8 @@
physical_p,num_trials,LER,LER_per_round,num_errors
0.001,6000,0.0365,0.0030937703263473892,219.0
0.0015,4000,0.0795,0.006879417576947544,318.0
0.002,2000,0.1575,0.01418030025167627,315.0
0.0025,2000,0.29,0.028137416075114108,580.0
0.003,2000,0.4455,0.04795283848945675,891.0
0.0035,2000,0.6305,0.07961852200020059,1261.0
0.004,2000,0.7825,0.11938055324065988,1565.0
1 physical_p num_trials LER LER_per_round num_errors
2 0.001 6000 0.0365 0.0030937703263473892 219.0
3 0.0015 4000 0.0795 0.006879417576947544 318.0
4 0.002 2000 0.1575 0.01418030025167627 315.0
5 0.0025 2000 0.29 0.028137416075114108 580.0
6 0.003 2000 0.4455 0.04795283848945675 891.0
7 0.0035 2000 0.6305 0.07961852200020059 1261.0
8 0.004 2000 0.7825 0.11938055324065988 1565.0

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@@ -0,0 +1,8 @@
physical_p,num_trials,LER,LER_per_round,num_errors
0.001,6000,0.0343333333333333,0.0029071468641445053,205.9999999999998
0.0015,4000,0.0885,0.0076922358935922475,354.0
0.002,2000,0.177,0.0161022072935475,354.0
0.0025,2000,0.3325,0.03312364612025187,665.0
0.003,2000,0.501,0.05628314409130197,1002.0
0.0035,2000,0.682,0.09105921022136998,1364.0
0.004,2000,0.8345,0.13920480678485292,1669.0
1 physical_p num_trials LER LER_per_round num_errors
2 0.001 6000 0.0343333333333333 0.0029071468641445053 205.9999999999998
3 0.0015 4000 0.0885 0.0076922358935922475 354.0
4 0.002 2000 0.177 0.0161022072935475 354.0
5 0.0025 2000 0.3325 0.03312364612025187 665.0
6 0.003 2000 0.501 0.05628314409130197 1002.0
7 0.0035 2000 0.682 0.09105921022136998 1364.0
8 0.004 2000 0.8345 0.13920480678485292 1669.0

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@@ -0,0 +1,8 @@
physical_p,num_trials,LER,LER_per_round,num_errors
0.001,10000,0.0225,0.0018946185336699006,225.0
0.0015,4000,0.05,0.004265318777560645,200.0
0.002,2000,0.1095,0.009617798287998358,219.0
0.0025,2000,0.214,0.01986654747829364,428.0
0.003,2000,0.364,0.03701077827175081,728.0
0.0035,2000,0.5525,0.06481093518102832,1105.0
0.004,2000,0.7365,0.10518816757921234,1473.0
1 physical_p num_trials LER LER_per_round num_errors
2 0.001 10000 0.0225 0.0018946185336699006 225.0
3 0.0015 4000 0.05 0.004265318777560645 200.0
4 0.002 2000 0.1095 0.009617798287998358 219.0
5 0.0025 2000 0.214 0.01986654747829364 428.0
6 0.003 2000 0.364 0.03701077827175081 728.0
7 0.0035 2000 0.5525 0.06481093518102832 1105.0
8 0.004 2000 0.7365 0.10518816757921234 1473.0

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@@ -0,0 +1,8 @@
physical_p,num_trials,LER,LER_per_round,num_errors
0.001,12000,0.0199166666666666,0.0016750685805796417,238.9999999999992
0.0015,6000,0.0413333333333333,0.0035114743705089158,247.9999999999998
0.002,4000,0.082,0.007104467133977943,328.0
0.0025,2000,0.194,0.01781208360090769,388.0
0.003,2000,0.321,0.03174633874742727,642.0
0.0035,2000,0.4975,0.055733304754966406,995.0
0.004,2000,0.6875,0.0923797676224748,1375.0
1 physical_p num_trials LER LER_per_round num_errors
2 0.001 12000 0.0199166666666666 0.0016750685805796417 238.9999999999992
3 0.0015 6000 0.0413333333333333 0.0035114743705089158 247.9999999999998
4 0.002 4000 0.082 0.007104467133977943 328.0
5 0.0025 2000 0.194 0.01781208360090769 388.0
6 0.003 2000 0.321 0.03174633874742727 642.0
7 0.0035 2000 0.4975 0.055733304754966406 995.0
8 0.004 2000 0.6875 0.0923797676224748 1375.0

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@@ -0,0 +1,8 @@
physical_p,num_trials,LER,LER_per_round,num_errors
0.001,2000,0.124,0.010971798240880681,248.0
0.0015,2000,0.2365,0.0222359015716157,473.0
0.002,2000,0.3665,0.037326792598442404,733.0
0.0025,2000,0.5595,0.06603881814539603,1119.0
0.003,2000,0.73,0.10336921268218224,1460.0
0.0035,2000,0.837,0.14029596115963894,1674.0
0.004,2000,0.9355,0.20421336158924952,1871.0
1 physical_p num_trials LER LER_per_round num_errors
2 0.001 2000 0.124 0.010971798240880681 248.0
3 0.0015 2000 0.2365 0.0222359015716157 473.0
4 0.002 2000 0.3665 0.037326792598442404 733.0
5 0.0025 2000 0.5595 0.06603881814539603 1119.0
6 0.003 2000 0.73 0.10336921268218224 1460.0
7 0.0035 2000 0.837 0.14029596115963894 1674.0
8 0.004 2000 0.9355 0.20421336158924952 1871.0

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@@ -0,0 +1,8 @@
physical_p,num_trials,LER,LER_per_round,num_errors
0.001,8000,0.0295,0.002492212300538421,236.0
0.0015,4000,0.07525,0.006498116023036737,301.0
0.002,2000,0.154,0.013839665569208792,308.0
0.0025,2000,0.293,0.02848028572607786,586.0
0.003,2000,0.4585,0.04983315584200687,917.0
0.0035,2000,0.6525,0.08431471728347295,1305.0
0.004,2000,0.802,0.1262468270496201,1604.0
1 physical_p num_trials LER LER_per_round num_errors
2 0.001 8000 0.0295 0.002492212300538421 236.0
3 0.0015 4000 0.07525 0.006498116023036737 301.0
4 0.002 2000 0.154 0.013839665569208792 308.0
5 0.0025 2000 0.293 0.02848028572607786 586.0
6 0.003 2000 0.4585 0.04983315584200687 917.0
7 0.0035 2000 0.6525 0.08431471728347295 1305.0
8 0.004 2000 0.802 0.1262468270496201 1604.0

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@@ -0,0 +1,8 @@
physical_p,num_trials,LER,LER_per_round,num_errors
0.001,8000,0.025875,0.0021822526517427665,207.0
0.0015,4000,0.0535,0.004571544229555857,214.0
0.002,2000,0.1165,0.010268909922777514,233.0
0.0025,2000,0.231,0.021650873371036106,462.0
0.003,2000,0.3665,0.037326792598442404,733.0
0.0035,2000,0.552,0.06472390440895348,1104.0
0.004,2000,0.742,0.10675969983223876,1484.0
1 physical_p num_trials LER LER_per_round num_errors
2 0.001 8000 0.025875 0.0021822526517427665 207.0
3 0.0015 4000 0.0535 0.004571544229555857 214.0
4 0.002 2000 0.1165 0.010268909922777514 233.0
5 0.0025 2000 0.231 0.021650873371036106 462.0
6 0.003 2000 0.3665 0.037326792598442404 733.0
7 0.0035 2000 0.552 0.06472390440895348 1104.0
8 0.004 2000 0.742 0.10675969983223876 1484.0

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@@ -0,0 +1,8 @@
physical_p,num_trials,LER,LER_per_round,num_errors
0.001,2000,0.789,0.12160429293407071,1578.0
0.0015,2000,0.9,0.1745958147319816,1800.0
0.002,2000,0.9465,0.21651717275071503,1893.0
0.0025,2000,0.967,0.24743705884517853,1934.0
0.003,2000,0.9905,0.32161385879719506,1981.0
0.0035,2000,0.9965,0.3757780964762649,1993.0
0.004,2000,0.9995,0.4692204681934514,1999.0
1 physical_p num_trials LER LER_per_round num_errors
2 0.001 2000 0.789 0.12160429293407071 1578.0
3 0.0015 2000 0.9 0.1745958147319816 1800.0
4 0.002 2000 0.9465 0.21651717275071503 1893.0
5 0.0025 2000 0.967 0.24743705884517853 1934.0
6 0.003 2000 0.9905 0.32161385879719506 1981.0
7 0.0035 2000 0.9965 0.3757780964762649 1993.0
8 0.004 2000 0.9995 0.4692204681934514 1999.0

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@@ -0,0 +1,8 @@
physical_p,num_trials,LER,LER_per_round,num_errors
0.001,4000,0.0915,0.007964810720254789,366.0
0.0015,2000,0.18,0.016401583188387914,360.0
0.002,2000,0.307,0.03009819055291696,614.0
0.0025,2000,0.4545,0.04925022878399943,909.0
0.003,2000,0.649,0.08354968174320077,1298.0
0.0035,2000,0.793,0.12300416913096102,1586.0
0.004,2000,0.9115,0.18295632456593924,1823.0
1 physical_p num_trials LER LER_per_round num_errors
2 0.001 4000 0.0915 0.007964810720254789 366.0
3 0.0015 2000 0.18 0.016401583188387914 360.0
4 0.002 2000 0.307 0.03009819055291696 614.0
5 0.0025 2000 0.4545 0.04925022878399943 909.0
6 0.003 2000 0.649 0.08354968174320077 1298.0
7 0.0035 2000 0.793 0.12300416913096102 1586.0
8 0.004 2000 0.9115 0.18295632456593924 1823.0

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@@ -0,0 +1,8 @@
physical_p,num_trials,LER,LER_per_round,num_errors
0.001,8000,0.030125,0.002545760854709589,241.0
0.0015,4000,0.067,0.005762505879780444,268.0
0.002,2000,0.1355,0.012060348411758404,271.0
0.0025,2000,0.2805,0.027060355839749417,561.0
0.003,2000,0.4395,0.0470985932750948,879.0
0.0035,2000,0.619,0.07726481455474521,1238.0
0.004,2000,0.7745,0.11672579914287295,1549.0
1 physical_p num_trials LER LER_per_round num_errors
2 0.001 8000 0.030125 0.002545760854709589 241.0
3 0.0015 4000 0.067 0.005762505879780444 268.0
4 0.002 2000 0.1355 0.012060348411758404 271.0
5 0.0025 2000 0.2805 0.027060355839749417 561.0
6 0.003 2000 0.4395 0.0470985932750948 879.0
7 0.0035 2000 0.619 0.07726481455474521 1238.0
8 0.004 2000 0.7745 0.11672579914287295 1549.0

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@@ -0,0 +1,8 @@
physical_p,num_trials,LER,LER_per_round,num_errors
0.001,2000,0.115,0.010128988904076097,230.0
0.0015,2000,0.2165,0.020126716372619535,433.0
0.002,2000,0.3575,0.0361944392516631,715.0
0.0025,2000,0.5255,0.06023409479070929,1051.0
0.003,2000,0.6935,0.09384489827464226,1387.0
0.0035,2000,0.816,0.13156999840650407,1632.0
0.004,2000,0.9105,0.1821909360735222,1821.0
1 physical_p num_trials LER LER_per_round num_errors
2 0.001 2000 0.115 0.010128988904076097 230.0
3 0.0015 2000 0.2165 0.020126716372619535 433.0
4 0.002 2000 0.3575 0.0361944392516631 715.0
5 0.0025 2000 0.5255 0.06023409479070929 1051.0
6 0.003 2000 0.6935 0.09384489827464226 1387.0
7 0.0035 2000 0.816 0.13156999840650407 1632.0
8 0.004 2000 0.9105 0.1821909360735222 1821.0

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physical_p,num_trials,LER,LER_per_round,num_errors
0.001,4000,0.0975,0.008512444610847103,390.0
0.0015,2000,0.1915,0.017558569754261066,383.0
0.002,2000,0.2765,0.02661075227253118,553.0
0.0025,2000,0.448,0.04831127709115113,896.0
0.003,2000,0.5865,0.07094884804525436,1173.0
0.0035,2000,0.7455,0.10777583350900755,1491.0
0.004,2000,0.8585,0.15037026489320615,1717.0
1 physical_p num_trials LER LER_per_round num_errors
2 0.001 4000 0.0975 0.008512444610847103 390.0
3 0.0015 2000 0.1915 0.017558569754261066 383.0
4 0.002 2000 0.2765 0.02661075227253118 553.0
5 0.0025 2000 0.448 0.04831127709115113 896.0
6 0.003 2000 0.5865 0.07094884804525436 1173.0
7 0.0035 2000 0.7455 0.10777583350900755 1491.0
8 0.004 2000 0.8585 0.15037026489320615 1717.0

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physical_p,num_trials,LER,LER_per_round,num_errors
0.001,4000,0.0925,0.008055852365631777,370.0
0.0015,2000,0.1735,0.015754197146499838,347.0
0.002,2000,0.265,0.025330719468954155,530.0
0.0025,2000,0.427,0.04534551221126004,854.0
0.003,2000,0.571,0.0680954310203834,1142.0
0.0035,2000,0.7105,0.09814362266376564,1421.0
0.004,2000,0.8315,0.1379151915045972,1663.0
1 physical_p num_trials LER LER_per_round num_errors
2 0.001 4000 0.0925 0.008055852365631777 370.0
3 0.0015 2000 0.1735 0.015754197146499838 347.0
4 0.002 2000 0.265 0.025330719468954155 530.0
5 0.0025 2000 0.427 0.04534551221126004 854.0
6 0.003 2000 0.571 0.0680954310203834 1142.0
7 0.0035 2000 0.7105 0.09814362266376564 1421.0
8 0.004 2000 0.8315 0.1379151915045972 1663.0

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@@ -0,0 +1,8 @@
physical_p,num_trials,LER,LER_per_round,num_errors
0.001,2000,0.189,0.01730577346851303,378.0
0.0015,2000,0.334,0.03330489586414709,668.0
0.002,2000,0.462,0.050346464045528894,924.0
0.0025,2000,0.67,0.088249181932055,1340.0
0.003,2000,0.8035,0.12680036354194668,1607.0
0.0035,2000,0.8915,0.1689653255579383,1783.0
0.004,2000,0.965,0.2437378987592076,1930.0
1 physical_p num_trials LER LER_per_round num_errors
2 0.001 2000 0.189 0.01730577346851303 378.0
3 0.0015 2000 0.334 0.03330489586414709 668.0
4 0.002 2000 0.462 0.050346464045528894 924.0
5 0.0025 2000 0.67 0.088249181932055 1340.0
6 0.003 2000 0.8035 0.12680036354194668 1607.0
7 0.0035 2000 0.8915 0.1689653255579383 1783.0
8 0.004 2000 0.965 0.2437378987592076 1930.0

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@@ -0,0 +1,8 @@
physical_p,num_trials,LER,LER_per_round,num_errors
0.001,4000,0.092,0.008010320054115394,368.0
0.0015,2000,0.182,0.016601725400650635,364.0
0.002,2000,0.2885,0.027966478964539188,577.0
0.0025,2000,0.468,0.05123358540561418,936.0
0.003,2000,0.6195,0.07736578684966466,1239.0
0.0035,2000,0.7805,0.11870857647232991,1561.0
0.004,2000,0.8815,0.16283731439217686,1763.0
1 physical_p num_trials LER LER_per_round num_errors
2 0.001 4000 0.092 0.008010320054115394 368.0
3 0.0015 2000 0.182 0.016601725400650635 364.0
4 0.002 2000 0.2885 0.027966478964539188 577.0
5 0.0025 2000 0.468 0.05123358540561418 936.0
6 0.003 2000 0.6195 0.07736578684966466 1239.0
7 0.0035 2000 0.7805 0.11870857647232991 1561.0
8 0.004 2000 0.8815 0.16283731439217686 1763.0

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@@ -0,0 +1,8 @@
physical_p,num_trials,LER,LER_per_round,num_errors
0.001,4000,0.0825,0.007149544452537682,330.0
0.0015,2000,0.1585,0.01427786270551501,317.0
0.002,2000,0.2535,0.024068915462335805,507.0
0.0025,2000,0.4035,0.042142573743546796,807.0
0.003,2000,0.5605,0.06621568805942701,1121.0
0.0035,2000,0.729,0.10309294344737896,1458.0
0.004,2000,0.8435,0.14320643674428069,1687.0
1 physical_p num_trials LER LER_per_round num_errors
2 0.001 4000 0.0825 0.007149544452537682 330.0
3 0.0015 2000 0.1585 0.01427786270551501 317.0
4 0.002 2000 0.2535 0.024068915462335805 507.0
5 0.0025 2000 0.4035 0.042142573743546796 807.0
6 0.003 2000 0.5605 0.06621568805942701 1121.0
7 0.0035 2000 0.729 0.10309294344737896 1458.0
8 0.004 2000 0.8435 0.14320643674428069 1687.0

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@@ -0,0 +1,8 @@
physical_p,num_trials,LER,LER_per_round,num_errors
0.001,2000,0.818,0.13236056607309032,1636.0
0.0015,2000,0.901,0.17528682442801136,1802.0
0.002,2000,0.9565,0.2299112633774043,1913.0
0.0025,2000,0.969,0.25134773793289455,1938.0
0.003,2000,0.9945,0.3518181130178767,1989.0
0.0035,2000,0.997,0.3837454986270925,1994.0
0.004,2000,0.9995,0.4692204681934514,1999.0
1 physical_p num_trials LER LER_per_round num_errors
2 0.001 2000 0.818 0.13236056607309032 1636.0
3 0.0015 2000 0.901 0.17528682442801136 1802.0
4 0.002 2000 0.9565 0.2299112633774043 1913.0
5 0.0025 2000 0.969 0.25134773793289455 1938.0
6 0.003 2000 0.9945 0.3518181130178767 1989.0
7 0.0035 2000 0.997 0.3837454986270925 1994.0
8 0.004 2000 0.9995 0.4692204681934514 1999.0

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@@ -0,0 +1,8 @@
physical_p,num_trials,LER,LER_per_round,num_errors
0.001,2000,0.146,0.013065897372720348,292.0
0.0015,2000,0.2805,0.027060355839749417,561.0
0.002,2000,0.415,0.043695229663312296,830.0
0.0025,2000,0.578,0.06937216612000952,1156.0
0.003,2000,0.746,0.10792203989196847,1492.0
0.0035,2000,0.8665,0.15448086847325826,1733.0
0.004,2000,0.9405,0.2095463416012857,1881.0
1 physical_p num_trials LER LER_per_round num_errors
2 0.001 2000 0.146 0.013065897372720348 292.0
3 0.0015 2000 0.2805 0.027060355839749417 561.0
4 0.002 2000 0.415 0.043695229663312296 830.0
5 0.0025 2000 0.578 0.06937216612000952 1156.0
6 0.003 2000 0.746 0.10792203989196847 1492.0
7 0.0035 2000 0.8665 0.15448086847325826 1733.0
8 0.004 2000 0.9405 0.2095463416012857 1881.0

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@@ -0,0 +1,8 @@
physical_p,num_trials,LER,LER_per_round,num_errors
0.001,4000,0.082,0.007104467133977943,328.0
0.0015,2000,0.1555,0.013985493383097625,311.0
0.002,2000,0.26,0.024779901164930007,520.0
0.0025,2000,0.434,0.04632286722747814,868.0
0.003,2000,0.603,0.07409618065132939,1206.0
0.0035,2000,0.7465,0.10806851033720544,1493.0
0.004,2000,0.859,0.1506208564330962,1718.0
1 physical_p num_trials LER LER_per_round num_errors
2 0.001 4000 0.082 0.007104467133977943 328.0
3 0.0015 2000 0.1555 0.013985493383097625 311.0
4 0.002 2000 0.26 0.024779901164930007 520.0
5 0.0025 2000 0.434 0.04632286722747814 868.0
6 0.003 2000 0.603 0.07409618065132939 1206.0
7 0.0035 2000 0.7465 0.10806851033720544 1493.0
8 0.004 2000 0.859 0.1506208564330962 1718.0

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