deletions | additions       diff --git a/Results: Centroiding.tex b/Results: Centroiding.tex  index 6bb48be..c712865 100644  --- a/Results: Centroiding.tex  +++ b/Results: Centroiding.tex 
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where $N_{max}$, $N_{min}$, and $N_{mean}$ are the maximum, minimum and average number of counts in the 5$\times$5 array of subpixel positions, respectively. For a completely random distribution, this number should approach zero with increasing number of photons.  Several of ThunderSTORM's centroiding algorithms were tested to find an algorithm that leads to a minimum amount of fixed pattern noise. The distributions of centroided positions are shown in  Fig~\ref{fig_pixelimages}, where the pixels are further divided into a 13$\times$13 grid. The results are summarised in Table~\ref{table:results}. Maximum likelihood (ML) fitting with a Gaussian PSF produces the most uniform distribution of localised positions (Fig~\ref{fig_pixelimages}a) with FPN of 71\%, as well as the finding the highest number of photons. As reported previously,\cite{Hirvonen2014_rsi} the horizontal widening of the photon events, most likely caused by the CCD read-out, causes a bias in the centroided positions and photons are most likely to be found towards the right edge of the pixel. Radial symmetry method produces similar results with a slightly higher FPN of 91\%, but changes the bias to the vertical direction (Fig~\ref{fig_pixelimages}b). (Fig~\ref{fig_pixelimages}c).  Other methods produce results with similar distribution of centroided positions as ML (an example of weighted LS fit with integrated Gaussian PSF is shown in Fig~\ref{fig_pixelimages}c), Fig~\ref{fig_pixelimages}b),  but with higher FPN and lower photon count.