diff --git a/views.py b/views.py
index d8c60ad..278f92b 100644
--- a/views.py
+++ b/views.py
@@ -908,12 +908,14 @@ class StackedUpperLimitView(APIView):
 
         # iterate over source vectors, making maps
 
-        # Create a single list to hold all Healpix IDs
-        all_map_pixels = []
-        source_indices = []
+        # # Create a single list to hold all Healpix IDs
+        # all_map_pixels = []
+        # source_indices = []
+
+        hpid_to_source_indices_map = defaultdict(list)
 
         # Iterate over source vectors and get all unique Healpix IDs
-        for index, src_vec in enumerate(src_vec_list):
+        for source_index, src_vec in enumerate(src_vec_list):
             pixels = hp.query_disc(
                 nside=4096,
                 vec=src_vec,
@@ -921,33 +923,54 @@ class StackedUpperLimitView(APIView):
                 nest=False,
                 radius=(map_radius * u.arcsecond).to(u.radian).value,
             )
-            all_map_pixels.extend(pixels)
-            source_indices.extend([index] * len(pixels))
+            for p in pixels:
+                hpid_to_source_indices_map[p].append(source_index)
 
         # Get only unique Healpix IDs
-        unique_map_pixels = list(set(all_map_pixels))
-
+        # unique_map_pixels = list(set(all_map_pixels))
+        unique_map_pixels = list(hpid_to_source_indices_map.keys())
         # Perform a single database query for all unique pixels
+
         map_pixels_qs = (
             Pixel.objects.filter(hpid__in=unique_map_pixels, survey__in=survey_numbers)
             .values("hpid")
             .annotate(counts=Sum("counts"), exposure=Sum("exposure"))
-            .order_by("hpid")
         )
 
-        # turn the queryset to a list
-        map_pixels_list = list(map_pixels_qs)
+        db_results_map = {p["hpid"]: p for p in map_pixels_qs}
 
-        # get lists of healpix indices and count values
-        map_healpix_list = [d["hpid"] for d in map_pixels_list]
-        map_counts_list = [d["counts"] for d in map_pixels_list]
-        map_exposure_list = [d["exposure"] for d in map_pixels_list]
-        # map_contaminated_list = [d["contaminated"] for d in map_pixels_list]
+        map_healpix_list = []
+        map_counts_list = []
+        map_exposure_list = []
+        map_source_indices_list = []
 
-        # set map nside
+        # # turn the queryset to a list
+        # map_pixels_list = list(map_pixels_qs)
+
+        # # get lists of healpix indices and count values
+        # map_healpix_list = [d["hpid"] for d in map_pixels_list]
+        # map_counts_list = [d["counts"] for d in map_pixels_list]
+        # map_exposure_list = [d["exposure"] for d in map_pixels_list]
+        # # map_contaminated_list = [d["contaminated"] for d in map_pixels_list]
+
+        for hpid, source_indices in hpid_to_source_indices_map.items():
+            # Check if this pixel was actually found in the database query
+            if hpid in db_results_map:
+                db_data = db_results_map[hpid]
+                counts = db_data["counts"]
+                exposure = db_data["exposure"]
+
+                # For each source this pixel is associated with, create a parallel entry
+                for source_index in source_indices:
+                    map_healpix_list.append(hpid)
+                    map_counts_list.append(counts)
+                    map_exposure_list.append(exposure)
+                    map_source_indices_list.append(source_index)
+
+        # set map nside explicitly
         map_nside = 4096
 
-        # set map order
+        # set map order explicitly
         map_order = "ring"
 
         # assemble the result dict
@@ -955,7 +978,7 @@ class StackedUpperLimitView(APIView):
             "healpix": map_healpix_list,
             "counts": map_counts_list,
             "exposure": map_exposure_list,
-            "source_index": source_indices,
+            "source_index": map_source_indices_list,
             # "contaminated": map_contaminated_list,
             "nside": map_nside,
             "order": map_order,