diff --git a/pax/datastructure.py b/pax/datastructure.py
index 962b123e..e3019397 100644
--- a/pax/datastructure.py
+++ b/pax/datastructure.py
@@ -199,6 +199,9 @@ class Peak(StrictModel):
     #: Total areas of all hits per PMT (pe).
     area_per_channel = np.array([], dtype='float64')
 
+    # contribution to tight coincidence, 1 or 0 for each channel
+    coincidence_per_channel = np.array([], dtype=np.int16)
+
     #: Total area of all hits across all PMTs (pes).
     #: In XerawdpImitation mode, rightmost sample is not included in area integral.
     area = 0.0
diff --git a/pax/plugins/peak_processing/BasicProperties.py b/pax/plugins/peak_processing/BasicProperties.py
index 4ffc738a..207ff235 100644
--- a/pax/plugins/peak_processing/BasicProperties.py
+++ b/pax/plugins/peak_processing/BasicProperties.py
@@ -122,6 +122,13 @@ def transform_event(self, event):
             right = peak.index_of_maximum + self.tight_coincidence_samples
             peak.tight_coincidence = len(np.unique(peak.hits['channel'][(x >= left) & (x <= right)]))
 
+            # list of pmts that contribute to tight coincidence of the peak
+            peak.coincidence_per_channel = np.zeros_like(peak.hits_per_channel)
+            for hitt in peak.hits:
+                if hitt['index_of_maximum'] >= left and hitt['index_of_maximum'] <= right:
+                    pmt_index = hitt['channel']
+                    peak.coincidence_per_channel[pmt_index] = 1
+
             # Store the waveform; for tpc also store the top waveform
             put_w_in_center_of_field(w, peak.sum_waveform, cog_idx)
             if peak.detector == 'tpc':