diff --git a/python/datastruct.py b/python/datastruct.py
index 330d2fe..0b970a0 100644
--- a/python/datastruct.py
+++ b/python/datastruct.py
@@ -115,6 +115,7 @@ class UnionFindQueue(Generic[_NameT, _ElemT]):
         if node is not None:
             node.owner = None
         while node is not None:
+            node.min_node = None  # type: ignore
             prev_node = node
             if node.left is not None:
                 node = node.left
diff --git a/python/mwmatching.py b/python/mwmatching.py
index d49b95f..9c58709 100644
--- a/python/mwmatching.py
+++ b/python/mwmatching.py
@@ -610,7 +610,7 @@ class _MatchingContext:
         # For each T-vertex or unlabeled vertex "x",
         # "vertex_sedge_queue[x]" is a queue of edges between "x" and any
         # S-vertex. The priority of an edge is 2 times its pseudo-slack.
-        self.vertex_sedge_queue: list[PriorityQueue]
+        self.vertex_sedge_queue: list[PriorityQueue[int]]
         self.vertex_sedge_queue = [PriorityQueue() for _x in range(num_vertex)]
         self.vertex_sedge_node: list[Optional[PriorityQueue.Node]]
         self.vertex_sedge_node = [None for _e in graph.edges]
@@ -623,9 +623,9 @@ class _MatchingContext:
 
         for blossom in itertools.chain(self.trivial_blossom,
                                        self.nontrivial_blossom):
+            blossom.parent = None
             blossom.vertex_set.clear()
             del blossom.vertex_set
-            blossom.tree_blossoms = None
 
     #
     # Least-slack edge tracking:
@@ -1316,6 +1316,9 @@ class _MatchingContext:
 
             self.delta2_enable_blossom(sub)
 
+        # Avoid leaking a reference cycle.
+        del blossom.vertex_set
+
         # Delete the expanded blossom.
         self.nontrivial_blossom.remove(blossom)
 
@@ -1827,7 +1830,7 @@ class _MatchingContext:
         # This loop runs through at most O(n) iterations per stage.
         while True:
 
-            self._check_alternating_tree_consistency()  # TODO -- remove this
+            # self._check_alternating_tree_consistency()  # TODO -- remove this
 
             # Consider the incident edges of newly labeled S-vertices.
             self.scan_new_s_vertices()