Rephrase to remove 'gate schedule'

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2026-05-01 21:56:03 +02:00
parent 47493a6beb
commit 606d68e2c1

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@@ -1103,8 +1103,8 @@ chosen noise model.
Moving one level of abstraction higher, the syndrome extraction
circuit itself must be generated.
This entails defining the gate schedule for the ancilla measurements
and specifying the error locations introduced by the chosen noise
This entails constructing the full circuit, including the ancilla
measurements and the error locations introduced by the chosen noise
model, both of which depend on the code and noise model in question.
Even further up, given an already constructed syndrome extraction
@@ -1130,63 +1130,6 @@ reimplementation in Rust to achieve higher simulation speeds due to
the compiled nature of the language.
We reimplemented both the window splitting and the decoders themselves.
% %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% \section{Numerical results}
%
% % Intro
%
% In this section, we perform numerical experiments to evaluate the
% modification to sliding-window decoding we introduced in
% \Cref{sec:warm_start_bp}.
% We chose to carry out our simulations on \ac{bb} codes, as they
% \red{[something about qldpc codes being a hot topic in the literature
% currently because of some promising properties]}.
% Specifically, we chose the $\llbracket 144, 12, 12 \rrbracket$ BB
% code, as this \red{[something something]}.\\
% \red{[Circuit-level noise]} \\
% \red{[Per-round LER]} \\
% All datapoints have been generated by simulating at least $200$
% logical error events.
%
% For the practical aspects of implementation, several layers of
% abstraction must be considered.
% The lowest layer is the circuit-level simulator.
% This serves as the backbone of all further simulations.
% It takes care of the quantum mechanical aspects of the system.
% \red{It is, for example, responsible for the introduction of noise
% [rephrase this]}.
%
% Moving one level of abstraction higher, aside from the circuit
% simulation itself, the circuit also has to be generated.
% E.g., the syndrome extraction circuitry must be defined and possible
% sources of noise must be modeled.
% This heavily depends on the code in question and the chosen noise model.
% \red{[Find something more to say]}
%
% Even further up, we have already defined syndrome extraction
% circuitry and built the \acf{dem}.
% We must now split the detector error matrix into separate windows and
% manage the interplay of the inner decoders acting on the individual
% windows themselves.
% \red{[Find something more to say]}
%
% Finally, we require the decoder itself.
% This simply gets a \acf{pcm} and a syndrome with no regard
% \red{[Rephrase this] for the complexity in the rest of the system}.
%
% In our implementations, Stim \cite{gidney_stim_2021} served as the
% circuit-level simulator \red{[Possibly mention why stim was chosen]}.
% For the circuit generation, we employed utilities from QUITS
% \cite{kang_quits_2025}, where syndrome extraction circuitry
% generation is implemented for a number of different \ac{qldpc} codes.
% An initial Python implementation used QUITS for the window
% splitting and subsequent sliding-window decoding as well.
% The \ac{bp} and \ac{bpgd} decoders were also initially implemented in Python.
% After a preliminary investigation, we opted for a complete
% reimplementation in Rust to achieve higher simulation speeds due to
% the compiled nature of the language.
% We reimplemented both the window splitting and the decoders themselves.
%%%%%%%%%%%%%%%%
\subsection{Belief Propagation}
\label{subsec:Belief Propagation}
@@ -1195,7 +1138,7 @@ We reimplemented both the window splitting and the decoders themselves.
\content{Use min-sum}
\begin{figure}[H]
\begin{figure}[t]
\centering
\begin{tikzpicture}
\begin{axis}[
@@ -1255,7 +1198,7 @@ We reimplemented both the window splitting and the decoders themselves.
}
\end{figure}
\begin{figure}[H]
\begin{figure}[t]
\centering
\begin{tikzpicture}
\begin{axis}[
@@ -1338,7 +1281,7 @@ We reimplemented both the window splitting and the decoders themselves.
}
\end{figure}
\begin{figure}[H]
\begin{figure}[t]
\centering
\begin{tikzpicture}
\begin{axis}[
@@ -1412,7 +1355,7 @@ We reimplemented both the window splitting and the decoders themselves.
}
\end{figure}
\begin{figure}[H]
\begin{figure}[t]
\centering
\begin{subfigure}{0.48\textwidth}
\centering
@@ -1572,7 +1515,7 @@ We reimplemented both the window splitting and the decoders themselves.
\subsection{Belief Propagation with Guided Decimation}
\label{subsec:Belief Propagation with Guided Decimation}
\begin{figure}[H]
\begin{figure}[t]
\centering
\hspace*{-6mm}
\begin{subfigure}{0.5\textwidth}
@@ -1726,7 +1669,7 @@ We reimplemented both the window splitting and the decoders themselves.
}
\end{figure}
\begin{figure}[H]
\begin{figure}[t]
\centering
\hspace*{-6mm}
\begin{subfigure}{0.48\textwidth}
@@ -1889,7 +1832,7 @@ We reimplemented both the window splitting and the decoders themselves.
}
\end{figure}
\begin{figure}[H]
\begin{figure}[t]
\centering
\hspace*{-6mm}
\begin{subfigure}{0.5\textwidth}
@@ -2043,7 +1986,7 @@ We reimplemented both the window splitting and the decoders themselves.
}
\end{figure}
\begin{figure}[H]
\begin{figure}[t]
\centering
\hspace*{-6mm}
\begin{subfigure}{0.48\textwidth}