deletions | additions       diff --git a/reconstructed_wedges.tex b/reconstructed_wedges.tex  index 2ce91e9..882e147 100644  --- a/reconstructed_wedges.tex  +++ b/reconstructed_wedges.tex 
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In Figure \ref{fig:wizcola_hdaModes_z60_epsilonT15} we present our results of $\alpha_{||}$, $\alpha_{\perp}$ modes and in Figure \ref{fig:wizcola_hdaUnc_z60_epsilonT15} their uncertainties.   Because of limitations of the data, in addition to the 50\% priors on $\alpha_{||}$, $\alpha_{\perp}$ mentioned above, we also investigate flat priors on their combinatoins which we hereon perscribe as $\epsilon$ ($\sim 1/H/D_{\rm A}$) and $\alpha (\sim D_{\rm A}^2/H$). The $\alpha$ parameter is mostly sensitive to $\xi_0$ and $\epsilon$ to $\xi_2$, although both terms appear in all multipoles (see \cite{Padmanabhan_2008} for a discussion). In the analysis we apply a 15\% flat prior on $\epsilon$, which is marked by the red dot-dashed lines. We investigate priors on $\alpha$, but do not apply for these results, but mark the $25\%$ threshold as blue dashed lines. In addition we select from the 600 realizations that have a significance of detection of the BAO of at least $2.9\sigma$ (as in the observations).We find 87 (15\%; marked as large blue circles), and quote their statistics below. In Figure \ref{fig:wizcola_hdaUnc_z60_epsilonT15} we also add the WiggleZ $\Delta z^{\rm Far}$ result with a yellow star.   The pile-up of many of the realizations along the $\epsilon$ cutoff lines in Figure \ref{fig:wizcola_hdaModes_z60_epsilonT15} demonestrate the limited constraining power of an average WiggleZ volume. We do find, however, that the high significance detection threshold is concentrated around the true values of $\alpha_{||},\alpha_\perp=1$. We find $<\alpha>$ (median) $<\alpha_{||}>=0.999\pm 0.154$, $<\alpha_{\perp}>=1.001\pm0.081$ (medians, standard deviations).  %The resulting mock modes of $\alpha_{||}$, $\alpha_{\perp}$ obtained without using a prior on $\epsilon$ and $\alpha$ are displayed in Figure REF and their uncertianties in Figure REF. These clearly shows the limitation of constraining power of the WiggleZ volume. Similar results when using flat priors on $\epsilon$ of $15\%$ and $7\%$ are displayed in Figures REF. We clearly see that the results are both less biassed and yield tighter constraints when ruling out the parameter space, pointing out that our mechanism of reconstruction and fitting algorithm do not raise biases that are larger than the statistical uncertainties. ... a few words about $\alpha$ priors....