diff --git a/mpitests/test_adjoint_jacobian.py b/mpitests/test_adjoint_jacobian.py
index ea95aafbf..9bc92779e 100644
--- a/mpitests/test_adjoint_jacobian.py
+++ b/mpitests/test_adjoint_jacobian.py
@@ -103,9 +103,9 @@ def circuit():
             qml.RX(0.4, wires=[0])
             return qml.expval(qml.PauliZ(0))
 
-        qnode = QNode(circuit, dev, diff_method="adjoint")
+        result = QNode(circuit, dev, diff_method="adjoint")
 
-        jac = qml.grad(qnode)()
+        jac = qml.grad(result)()
 
         assert len(jac) == 0
 
@@ -222,7 +222,18 @@ def test_Rot_gradient(self, stateprep, theta, batch_obs, dev):
     @pytest.mark.parametrize("param", [1, -2, 1.623, -0.051, 0])  # integers, floats, zero
     @pytest.mark.parametrize(
         "rotation,obs,expected_func",
-        [(qml.RY, qml.PauliX, lambda x: np.cos(x)), (qml.RX, qml.PauliZ, lambda x: -np.sin(x))],
+        [
+            (
+                qml.RY, 
+                qml.PauliX, 
+                lambda x: np.cos(x)
+            ), 
+            (
+                qml.RX, 
+                qml.PauliZ, 
+                lambda x: -np.sin(x)
+            ),
+        ],
     )
     @pytest.mark.parametrize("batch_obs", [True, False])
     def test_r_gradient(
diff --git a/mpitests/test_expval.py b/mpitests/test_expval.py
index c7d600d18..43ca43122 100644
--- a/mpitests/test_expval.py
+++ b/mpitests/test_expval.py
@@ -135,9 +135,6 @@ def test_expval_single_wire_no_parameters(self, tol, operation, wires, C_DTYPE,
         """Tests that expectation values are properly calculated for single-wire observables without parameters."""
         num_wires = numQubits
         comm = MPI.COMM_WORLD
-        commSize = comm.Get_size()
-        num_global_wires = commSize.bit_length() - 1
-        num_local_wires = num_wires - num_global_wires
 
         dev_mpi = qml.device(
             "lightning.gpu", wires=numQubits, mpi=True, c_dtype=C_DTYPE, batch_obs=batch_obs
@@ -436,5 +433,7 @@ def circuit():
             expected_val = -(
                 np.cos(varphi) * np.sin(phi) + np.sin(varphi) * np.cos(theta)
             ) / np.sqrt(2)
+        else:
+            expected_val = 0
 
         assert np.allclose(res, expected_val, atol=tol)