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\subsection{Fourier Statistics}  All Fourier Stastistic statistic  color plots are shown in Fig ???. Unlike the Intensity Statistics, statistics,  the Fourier Statistics do not share a common general behavior among behavior, and  their color plots. plots appear more heterogeneous.  As a whole, we note various sensitivities towards to  changes in stellar mass-loss rates, magnetic field strength, and time evolution. The Delta-Variance and Wavelet transform color plots closely resemble those of the intensity statistics, as their greatest sensitivities correspond to changes in stellar-mass loss rates. In fact, the Delta-variance exhibits a hierarchical structure in wind model pairings, similar to what we find with the Kurtosis and Skewness. For the Wavelet transform, we note a different hierarchical structure, one linked to magnetic fields. As we compare our The Delta-Variance's  strong wind models to different turbulent clouds, the distances vary, and often decrease if weaker winds are comparisons  also considered. When comparing turbulent runs with weaker wind models, the Delta-Variance shows small responses, but the Wavelet Transform appears appear  slightly sensitive. impacted by magnetic field strength, as seen in their distance magnitudes. The Wavelet transform displays a similar trend that is further augmented by time evolution.  The VCS statistic demonstrates strong, roughly equal sensitivities to both stellar mass-loss rates and magnetic field strength. As seen in its color-plot, distances solely quantifying changes %In fact, the Delta-variance exhibits a hierarchical structure/trend  in stellar mass-loss rates  -%-(T2 constant)--  tend wind model pairings similar  toresemble those explicitly comparing changes in magnetic field.  %--ones  thatdon't involve W1.   In fact, some  ofour largest distances involve T4,  the run with Kurtosis and Skewness. For  the strongest magnetic field. We also Wavelet transform, we  note large distances between a different hierarchical structure, one closer linked to magnetic fields. As we compare  ourtwo turbulent clouds T1 and T2 in the presence of  strong winds. These clouds have the same magnetic field strength, indicating that the VCS is sensitive wind models  to initial conditions. We different turbulent clouds, the distances vary, and often decrease if weaker winds are  also find considered. When comparing turbulent runs with weaker wind models,  the SPS to be sensitive to all of our simulation parameters, Delta-Variance shows small responses,  butit is not as structured as that of  the VCS. %(not sure how much to elaborate on this statistic). Wavelet Transform appears slightly sensitive.  For purely turbulent runs, we find the Bicoherence's behavior The VCS statistic demonstrates strong, roughly equal sensitivities to both stellar mass-loss rates and magnetic field strength. As its color-plot shows, distances solely quantifying changes in stellar mass-loss rates tend  to resemble that those explicitly comparing changes in magnetic field. In fact, some  of the Cramer statistic. While it usually yields equal our largest  distances for all simulation pairs, involve T4,  the statistic produces a range of values for comparisons involving purely turbulent runs. T3t0 and T4t0 appear to be relatively similar, and different from all other simulations. And, although run with  the strongest magnetic field. We also note large  distancesfor pairs (W3T2t0.1, T3t0) and (W2T4t0.1, T4t0) appear to be different, the distance  between runs W3T2t0.1 our two turbulent clouds T1  and W2T4t0.1 T2 in the presence of strong winds. These clouds have the same magnetic field strength, indicating that the VCS  is found sensitive to the initial turbulence conditions. We also find the SPS  to be similar. %still waiting for HPC sensitive  to fix python issue, so I can't test out all of our simulation parameters, but unlike  the new distance metric just yet. VCS, it's sensitivities are not structured. (This makes it a difficult statistic to utilize?)  For purely turbulent runs, we find the Bicoherence to exhibit a binary behavior, similar to that of the Cramer statistic. While it usually yields equal distances for all simulation pairs, the statistic produces a range of values for comparisons involving purely turbulent runs. T3t0 and T4t0 appear to be relatively similar, and different from all other simulations. And, although the distances for pairs (W3T2t0.1, T3t0) and (W2T4t0.1, T4t0) appear to be different, the distance between runs W3T2t0.1 and W2T4t0.1 is found to be similar. %still waiting for HPC to fix python issue, so I can't test out the new distance metric just yet.  Out of all of our statistics, the VCA demonstrates the weakest sensitivity towards magnetic field strength. The behavior of its color-plot suggests an invariance insensitivity  to turbulent structure, as distances only change with wind model and evolution time. This allows the VCA to clearly detect changes in stellar mass-loss rates of varying sizes. The color plot shows the statistic's outputs for strong wind models to be different from that of all other models. But, once we introduce weaker winds to our turbulent clouds, they begin to resemble each other. As time evolves, the outputs become more alike. The magnetic field's weak impact on the statistic allows us to clearly see this. Despite the various degrees of sensitivities, many of the Fourier statistics fail to produce distinct visual differences corresponding to feedback. As seen in section 3.2, the most common difference is horizontal offset, which is relatively minor (in taking observations?). The VCS does produce distinct features, but its color plot suggests sensitivities to parameters other than stellar mass-loss rates.