diff --git a/simulations/airshower_beacon_simulation/dc_grid_power_time_fixes.py b/simulations/airshower_beacon_simulation/dc_grid_power_time_fixes.py
index 2372ac8..585f080 100755
--- a/simulations/airshower_beacon_simulation/dc_grid_power_time_fixes.py
+++ b/simulations/airshower_beacon_simulation/dc_grid_power_time_fixes.py
@@ -194,19 +194,49 @@ if __name__ == "__main__":
                 power_sort_idx = np.argsort(a_max)
 
                 N_plot = 30
-                for i, idx in enumerate(power_sort_idx):
+                for i, idx in enumerate(reversed(power_sort_idx)):
                     if i > N_plot:
                         break
-                    
-                    alpha = max(0.7, 1/len(a_))
 
-                    axs.plot(t_[idx], a_[idx], color='r', alpha=alpha)
+                    alpha = max(0.4, 1/len(a_))
+
+                    axs.plot(t_[idx], a_[idx], color='r', alpha=alpha, lw=2)
 
                 if fig_dir:
                     fig.tight_layout()
+
                     fig.savefig(path.join(fig_dir, path.basename(__file__) + f'.trace_overlap.{case}.pdf'))
                     fig.savefig(path.join(fig_dir, path.basename(__file__) + f'.trace_overlap.{case}.png'), transparent=True)
 
+                    # Take center between t_low and t_high
+                    if True:
+                        orig_xlims = axs.get_xlim()
+
+                        if not True: # t_high and t_low from strongest signal
+                            t_low = np.min(t_[power_sort_idx[-1]])
+                            t_high = np.max(t_[power_sort_idx[-1]])
+                        else: # take t_high and t_low from plotted signals
+                            a = [np.min(t_[idx]) for idx in power_sort_idx[-N_plot:]]
+                            axs.plot(a, [0]*N_plot, 'gx', ms=10)
+                            t_low  = np.nanmin(a)
+                            b = [np.max(t_[idx]) for idx in power_sort_idx[-N_plot:]]
+                            axs.plot(b, [0]*N_plot, 'b+', ms=10)
+                            t_high = np.nanmax(b)
+
+                        center_x = (t_high - t_low)/2 + t_low
+                        wx = 200
+
+                        low_xlim  = max(orig_xlims[0], center_x - wx)
+                        high_xlim = min(orig_xlims[1], center_x + wx)
+
+                        axs.set_xlim(low_xlim, high_xlim)
+                        fig.savefig(path.join(fig_dir, path.basename(__file__) + f'.trace_overlap.zoomed.{case}.pdf'))
+                        fig.savefig(path.join(fig_dir, path.basename(__file__) + f'.trace_overlap.zoomed.{case}.png'), transparent=True)
+
+
+                if True:
+                    continue
+
             # Measure power on grid
             for scalename, scale in scales.items():
                 wx, wy = scale, scale
@@ -223,3 +253,7 @@ if __name__ == "__main__":
                 if fig_dir:
                     fig.tight_layout()
                     fig.savefig(path.join(fig_dir, path.basename(__file__) + f'.X{X}.{case}.{scalename}.pdf'))
+
+    if args.show_plots:
+        plt.show()
+