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26 changes: 13 additions & 13 deletions Documentation/Doc.idx
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\indexentry{\texttt{Checkerboard}}{25}
\indexentry{\texttt{Checkerboard}}{24}
\indexentry{\texttt{Symm}}{25}
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\indexentry{\texttt{Precision Phase}}{30}
\indexentry{\path{NWrap}}{30}
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\indexentry{\path{Bilayer_square}}{77}
\indexentry{\path{N_leg_ladder}}{77}
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\indexentry{\texttt{Bilayer\_honeycomb}}{77}
\indexentry{\texttt{Triangular}}{78}
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\indexentry{\texttt{Symm}}{26}
\indexentry{\texttt{Precision Green} }{29}
\indexentry{\texttt{Precision Phase}}{29}
\indexentry{\path{NWrap}}{29}
\indexentry{\texttt{Square} }{77}
\indexentry{\path{Bilayer_square}}{78}
\indexentry{\path{N_leg_ladder}}{78}
\indexentry{\path{Honeycomb}}{78}
\indexentry{\texttt{Bilayer\_honeycomb}}{78}
\indexentry{\texttt{Triangular}}{79}
\indexentry{\texttt{Kagome}}{79}
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2 changes: 1 addition & 1 deletion Documentation/sampling.tex
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Expand Up @@ -74,7 +74,7 @@ \subsection{An explicit example of error estimation}\label{sec:autocorr}
In order to determine the autocorrelation time, we calculate the correlation function
\begin{equation}
\label{eqn:autocorrel}
S_{\hat{O}}(t_{\textrm{Auto}})=\sum_{i=1}^{N_{\textrm{Bin}}-t_{\textrm{Auto}}}\frac{\left(O_i-\left\langle \hat{O}\right\rangle \right)\left(O_{i+t_{\textrm{Auto}}}-\left\langle \hat{O}\right\rangle \right)}{\left(O_i-\left\langle \hat{O}\right\rangle \right)\left(O_{i}-\left\langle \hat{O}\right\rangle \right)}\, ,
S_{\hat{O}}(t_{\textrm{Auto}})=\frac{\sum_{i=1}^{N_{\textrm{Bin}}-t_{\textrm{Auto}}}\left(O_i-\left\langle \hat{O}\right\rangle \right)\left(O_{i+t_{\textrm{Auto}}}-\left\langle \hat{O}\right\rangle \right)}{\sum_{i=1}^{N_{\textrm{Bin}}-t_{\textrm{Auto}}}\left(O_i-\left\langle \hat{O}\right\rangle \right)\left(O_{i}-\left\langle \hat{O}\right\rangle \right)}\, ,
\end{equation}
where $O_i$ refers to the Monte Carlo estimate of the observable $\hat{O}$ in the $i^{\text{th}}$ bin. This function typically shows an exponential decay and the decay rate defines the autocorrelation time.
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