Bugfix for comparison to zero with torch tensor (#5183)

**Context:**
`ctrl_decomp_zyz` with a target with `torch` parameters fails because
`qml.math.isclose(torch.Tensor, float)` raises a `TypeError`. From forum
post
[here](https://discuss.pennylane.ai/t/precautions-to-take-when-switching-to-an-ibm-device/3982/6).

**Description of the Change:**
Switching to `qml.math.isclose(float, torch.Tensor)` seems to appease
PyTorch.

**Related GitHub Issues:**
#5185

doc/releases/changelog-dev.md

@@ -459,10 +459,14 @@
 * `default.mixed` no longer throws `ValueError` when applying a state vector that is not of type `complex128` when used with tensorflow.
   [(#5155)](https://github.com/PennyLaneAI/pennylane/pull/5155)
 
+* `ctrl_decomp_zyz` no longer raises a `TypeError` if the rotation parameters are of type `torch.Tensor`
+  [(#5183)](https://github.com/PennyLaneAI/pennylane/pull/5183)
+
 * Comparing `Prod` and `Sum` objects now works regardless of nested structure with `qml.equal` if the
   operators have a valid `pauli_rep` property.
   [(#5177)](https://github.com/PennyLaneAI/pennylane/pull/5177)
 
+
 <h3>Contributors ✍️</h3>
 
 This release contains contributions from (in alphabetical order):
@@ -473,6 +477,7 @@ Gabriel Bottrill,
 Astral Cai,
 Isaac De Vlugt,
 Diksha Dhawan,
+Lillian Frederiksen,
 Eugenio Gigante,
 Diego Guala,
 Soran Jahangiri,

pennylane/ops/op_math/controlled_decompositions.py

@@ -193,9 +193,9 @@ def decomp_circuit(op):
 
     decomp = []
 
-    if not qml.math.isclose(phi, 0.0, atol=1e-8, rtol=0):
+    if not qml.math.isclose(0.0, phi, atol=1e-8, rtol=0):
         decomp.append(qml.RZ(phi, wires=target_wire))
-    if not qml.math.isclose(theta / 2, 0.0, atol=1e-8, rtol=0):
+    if not qml.math.isclose(0.0, theta / 2, atol=1e-8, rtol=0):
         decomp.extend(
             [
                 qml.RY(theta / 2, wires=target_wire),
@@ -205,10 +205,10 @@ def decomp_circuit(op):
         )
     else:
         decomp.append(qml.ctrl(qml.PauliX(wires=target_wire), control=control_wires))
-    if not qml.math.isclose(-(phi + omega) / 2, 0.0, atol=1e-6, rtol=0):
+    if not qml.math.isclose(0.0, -(phi + omega) / 2, atol=1e-6, rtol=0):
         decomp.append(qml.RZ(-(phi + omega) / 2, wires=target_wire))
     decomp.append(qml.ctrl(qml.PauliX(wires=target_wire), control=control_wires))
-    if not qml.math.isclose((omega - phi) / 2, 0.0, atol=1e-8, rtol=0):
+    if not qml.math.isclose(0.0, (omega - phi) / 2, atol=1e-8, rtol=0):
         decomp.append(qml.RZ((omega - phi) / 2, wires=target_wire))
 
     return decomp

tests/ops/op_math/test_controlled_decompositions.py

@@ -257,6 +257,22 @@ def test_zyz_decomp_control_values(self, test_expand):
         expected = qml.ops.ctrl_decomp_zyz(base, (0,))
         assert equal_list(decomp, expected)
 
+    @pytest.mark.torch
+    def test_zyz_decomp_with_torch_params(self):
+        """Tests that the ZYZ decomposition runs when the target operation parameters
+        are of type torch.Tensor"""
+        import torch
+
+        target_op1 = qml.RY(torch.Tensor([1.2]), 0)
+        target_op2 = qml.RY(1.2, 0)
+
+        torch_decomp = ctrl_decomp_zyz(target_op1, 1)
+        decomp = ctrl_decomp_zyz(target_op2, 1)
+
+        assert np.all(
+            [qml.equal(op1, op2, check_interface=False) for op1, op2 in zip(torch_decomp, decomp)]
+        )
+
 
 class TestControlledBisectOD:
     """tests for qml.ops._ctrl_decomp_bisect_od"""