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Co-authored-by: Yushao Chen (Jerry) <[email protected]>

doc/releases/changelog-dev.md

@@ -15,7 +15,7 @@
 * The coefficients of observables now have improved differentiability.
   [(#6598)](https://github.com/PennyLaneAI/pennylane/pull/6598)
 
-* An informative error is raised in a qnode with `diff_method=None` is differentiated.
+* An informative error is raised when a `QNode` with `diff_method=None` is differentiated.
   [(#6770)](https://github.com/PennyLaneAI/pennylane/pull/6770)
 
 <h3>Breaking changes 💔</h3>

pennylane/workflow/jacobian_products.py

@@ -212,20 +212,22 @@ def execute_and_compute_jacobian(self, tapes: QuantumScriptBatch) -> tuple[Resul
 
 class NoGradients(JacobianProductCalculator):
     """A jacobian product calculator that raises errors when a vjp or jvp is requested."""
+
+    error_msg = "Derivatives cannot be calculated with diff_method=None"
 
     def compute_jacobian(self, tapes: QuantumScriptBatch) -> tuple:
-        raise qml.QuantumFunctionError("Derivatives cannot be calculated with diff_method=None")
+        raise qml.QuantumFunctionError(NoGradients.error_msg)
 
     def compute_vjp(self, tapes: QuantumScriptBatch, dy: Sequence[Sequence[TensorLike]]) -> tuple:
-        raise qml.QuantumFunctionError("Derivatives cannot be calculated with diff_method=None")
+        raise qml.QuantumFunctionError(NoGradients.error_msg)
 
     def execute_and_compute_jvp(
         self, tapes: QuantumScriptBatch, tangents: Sequence[Sequence[TensorLike]]
     ) -> tuple[ResultBatch, tuple]:
-        raise qml.QuantumFunctionError("Derivatives cannot be calculated with diff_method=None")
+        raise qml.QuantumFunctionError(NoGradients.error_msg)
 
     def execute_and_compute_jacobian(self, tapes: QuantumScriptBatch) -> tuple[ResultBatch, tuple]:
-        raise qml.QuantumFunctionError("Derivatives cannot be calculated with diff_method=None")
+        raise qml.QuantumFunctionError(NoGradients.error_msg)
 
 
 class TransformJacobianProducts(JacobianProductCalculator):

tests/gradients/core/test_pulse_gradient.py

@@ -1152,7 +1152,8 @@ def test_constant_commuting(self, t):
         assert qml.math.allclose(res, exp_grad)
         r = qml.execute([tape], dev, None)
         # Effective rotation parameters
-        assert qml.math.isclose(r, jnp.cos(2 * p[0]) * jnp.cos(2 * p[1]))
+        exp = jnp.cos(2 * p[0]) * jnp.cos(2 * p[1])
+        assert qml.math.isclose(r, exp)
         jax.clear_caches()
 
     @pytest.mark.slow