diff --git a/airshower_beacon_simulation/ca_period_from_shower.py b/airshower_beacon_simulation/ca_period_from_shower.py
index daac20f..f95ce61 100755
--- a/airshower_beacon_simulation/ca_period_from_shower.py
+++ b/airshower_beacon_simulation/ca_period_from_shower.py
@@ -41,9 +41,6 @@ def find_best_period_shifts_summing_at_location(test_loc, antennas, allowed_ks,
         else:
             plot_iteration_with_shifted_trace = []
 
-    allowed_sample_shifts = np.rint(allowed_ks * period /dt).astype(int)
-    sample_shift_first_trace = np.rint(period_shift_first_trace * period/dt).astype(int)
-
     # propagate to test location
     for i, ant in enumerate(antennas):
         aloc = [ant.x, ant.y, ant.z]
@@ -72,14 +69,13 @@ def find_best_period_shifts_summing_at_location(test_loc, antennas, allowed_ks,
     t_sum = np.arange(t_min+max_neg_shift, t_max+max_pos_shift, dt)
     a_sum = np.zeros(len(t_sum))
 
-    best_sample_shifts = np.zeros( (len(antennas)) ,dtype=int)
+    best_period_shifts = np.zeros( (len(antennas)) ,dtype=int)
     for i, (t_r, E_) in enumerate(zip(t_, a_)):
         f = interp1d(t_r, E_, assume_sorted=True, bounds_error=False, fill_value=0)
-        a_int = f(t_sum)
 
         if i == 0:
-            a_sum += a_int
-            best_sample_shifts[i] = sample_shift_first_trace
+            a_sum += f(t_sum)
+            best_period_shifts[i] = period_shift_first_trace
             continue
 
         # init figure
@@ -90,26 +86,27 @@ def find_best_period_shifts_summing_at_location(test_loc, antennas, allowed_ks,
             ax.set_ylabel("Amplitude")
             ax.plot(t_sum, a_sum)
 
-        shift_maxima = np.zeros( len(allowed_sample_shifts) )
-        for j, shift in enumerate(allowed_sample_shifts):
-            augmented_a = np.roll(a_int, shift)
+        # find the maxima for each period shift k
+        shift_maxima = np.zeros( len(allowed_ks) )
+        for j, k in enumerate(allowed_ks):
+            augmented_a = f(t_sum + k*period)
 
             shift_maxima[j] = np.max(augmented_a + a_sum)
 
-            if i in plot_iteration_with_shifted_trace:
-                ax.plot(t_sum, augmented_a, alpha=0.7, ls='dashed', label=f'{shift}')
+            if i in plot_iteration_with_shifted_trace and abs(k) <= 3:
+                ax.plot(t_sum, augmented_a, alpha=0.7, ls='dashed', label=f'{k:g}')
 
         # transform maximum into best_sample_shift
         best_idx = np.argmax(shift_maxima)
 
-        best_sample_shifts[i] = allowed_sample_shifts[best_idx]
-        best_augmented_a = np.roll(a_int, best_sample_shifts[i])
+        best_period_shifts[i] = allowed_ks[best_idx]
+        best_augmented_a = f(t_sum + k*period)
         a_sum += best_augmented_a
 
         # cleanup figure
         if i in plot_iteration_with_shifted_trace:
             if True: # plot best k again
-                ax.plot(t_sum, augmented_a, alpha=0.8, label=f'best k={best_sample_shifts[i]}', lw=2)
+                ax.plot(t_sum, best_augmented_a, alpha=0.8, label=f'best $k$={best_period_shifts[i]:g}', lw=2)
 
             ax.legend( ncol=5 )
             if fig_dir:
@@ -126,7 +123,7 @@ def find_best_period_shifts_summing_at_location(test_loc, antennas, allowed_ks,
 
                     if True: # zoomed on peak of this trace
                         x = t_r[np.argmax(E_)]
-                        wx = 50 + (max(best_sample_shifts) - min(best_sample_shifts))*dt
+                        wx = 50 + (max(best_period_shifts) - min(best_period_shifts))*dt
                         ax.set_xlim(x-wx, x+wx)
                         fig.savefig(fname + ".zoomed.peak.pdf")
 
@@ -138,10 +135,10 @@ def find_best_period_shifts_summing_at_location(test_loc, antennas, allowed_ks,
     # sort by antenna (undo sorting by maximum)
     undo_sort_idx = np.argsort(sort_idx)
 
-    best_sample_shifts = best_sample_shifts[undo_sort_idx]
+    best_period_shifts = best_period_shifts[undo_sort_idx]
 
     # Return ks
-    return best_sample_shifts, np.max(a_sum)
+    return best_period_shifts, np.max(a_sum)
 
 if __name__ == "__main__":
     import sys
@@ -413,16 +410,10 @@ if __name__ == "__main__":
             yy.append(y_+yoff)
 
             # Find best k for each antenna
-            shifts, maximum = find_best_period_shifts_summing_at_location(test_loc, ev.antennas, allowed_ks, period=1/f_beacon, dt=dt,
+            ks_per_loc[i], maxima_per_loc[i] = find_best_period_shifts_summing_at_location(test_loc, ev.antennas, allowed_ks, period=1/f_beacon, dt=dt,
                     plot_iteration_with_shifted_trace=[ 5, len(ev.antennas)-1],
                     fig_dir=tmp_fig_subdir, fig_distinguish=f"run{r}.")
 
-            # Translate sample shifts back into period multiple k
-            ks = np.rint(shifts*f_beacon*dt)
-
-            ks_per_loc[i] = ks
-            maxima_per_loc[i] = maximum
-
         xx = np.array(xx)
         yy = np.array(yy)
         locs = list(zip(xx, yy))