deletions | additions       diff --git a/subsubsection_Genus_Statistic_Genus_statistics__.tex b/subsubsection_Genus_Statistic_Genus_statistics__.tex  index fe91d4c..934661a 100644  --- a/subsubsection_Genus_Statistic_Genus_statistics__.tex  +++ b/subsubsection_Genus_Statistic_Genus_statistics__.tex 
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Figure 11 shows the genus for our two fiducial outputs. Positive values indicate a relative excess of peaks (a ``clump-dominated" topology), while a negative genus indicates an excess of voids. We find both curves exhibit similar behavior for intensities below 4 $\kms$. As expected, output W1T2t0.2 has a broader range of intensity values due to the higher velocities and excitation in the wind shells, and thus, exhibits some structure for higher integrated intensities. Between thresholds of $-1\kms$ and $1\kms$, the genus is smaller for the purely turbulent model, which indicates that there are more voids in the emission compared to the case with feedback. The genus for W1T2t0.2 is higher at low-intensities, but this may be because the voids created by winds are larger than those created by pure turbulence, such that the total number of minima is reduced. This effect would likely be enhanced for real clouds, where winds can break out and create sight-lines nearly empty of molecular emission (A11).  Our analysis highlights one advantage of the genus statistic: it is sensitive to both over-densities and voids. \citet{chepurov08} \citet{chepurnov08}  analyzed HI data of the SMC, which visually displays a large number of expanding shells with sizes of $\sim 100$ pc. The shells were not apparent at small scales ($< 100$ pc), but at intermediate scales (120-200 pc) the genus had a neutral or slightly positive value, which they attributed to shells. %Consequently, it may be useful for quantifying the porosity of clouds.   In practice, however, the thickness and morphology of clouds varies significantly between different star forming regions. In our comparison, the difference between the two curves is relatively subtle. Thus, it may be most informative when employed to compare sub-regions within clouds.