TN distance: lossen test tol + add precision note

quimb/tensor/tensor_core.py

@@ -1264,7 +1264,10 @@ def tensor_network_distance(
             = ( \langle A | A \rangle - 2 \mathrm{Re} \langle A | B \rangle|
             + \langle B | B \rangle ) ^{1/2}
 
-    which should have a matching external indices.
+    which should have matching outer indices. Note the default approach to
+    computing the norm is precision limited to about ``eps**0.5`` where ``eps``
+    is the precision of the data type, e.g. ``1e-8`` for float64. This is due
+    to the subtraction in the above expression.
 
     Parameters
     ----------

tests/test_tensor/test_tensor_core.py

@@ -1320,10 +1320,10 @@ def test_subgraphs(_):
     def test_expand_bond_dimension_zeros(self):
         k = MPS_rand_state(10, 7)
         k0 = k.copy()
-        k0.expand_bond_dimension(13)
+        k0.expand_bond_dimension_(13)
         assert k0.max_bond() == 13
         assert k0.ind_size("k0") == 2
-        assert k0.distance(k) == pytest.approx(0.0)
+        assert k0.distance(k) == pytest.approx(0.0, abs=1e-7)
 
     def test_expand_bond_dimension_random(self):
         tn = qtn.TN_rand_reg(6, 3, 2, dist="uniform")