Fix cotransform of quantum_fisher

doc/releases/changelog-dev.md

@@ -220,6 +220,9 @@
 
 <h3>Bug fixes 🐛</h3>
 
+* `quantum_fisher` now respects the classical Jacobian of QNodes.
+  [(#6350)](https://github.com/PennyLaneAI/pennylane/pull/6350)
+
 * `qml.map_wires` can now be applied to a batch of tapes.
   [(#6295)](https://github.com/PennyLaneAI/pennylane/pull/6295)
 

pennylane/gradients/fisher.py

@@ -19,6 +19,7 @@
 from pennylane import transform
 from pennylane.devices import DefaultQubit
 from pennylane.gradients import adjoint_metric_tensor
+from pennylane.gradients.metric_tensor import _contract_metric_tensor_with_cjac
 from pennylane.typing import PostprocessingFn
 
 
@@ -280,7 +281,7 @@ def wrapper(*args, **kwargs):
     return wrapper
 
 
-@partial(transform, is_informative=True)
+@partial(transform, classical_cotransform=_contract_metric_tensor_with_cjac, is_informative=True)
 def quantum_fisher(
     tape: qml.tape.QuantumScript, device, *args, **kwargs
 ) -> tuple[qml.tape.QuantumScriptBatch, PostprocessingFn]:

tests/gradients/core/test_fisher.py

@@ -152,16 +152,17 @@ def circ(params):
         ),
     )
     def test_quantum_fisher_info(self, dev):
-        """Integration test of quantum fisher information matrix CFIM. This is just calling ``qml.metric_tensor`` or ``qml.adjoint_metric_tensor`` and multiplying by a factor of 4"""
+        """Integration test of quantum fisher information matrix CFIM. This is just calling
+        ``qml.metric_tensor`` or ``qml.adjoint_metric_tensor`` and multiplying by a factor of 4"""
 
         n_wires = 2
 
         rng = pnp.random.default_rng(200)
         dev_hard = qml.device("default.qubit", wires=n_wires + 1, shots=1000, seed=rng)
 
         def qfunc(params):
-            qml.RX(params[0], wires=0)
             qml.RX(params[1], wires=0)
+            qml.RX(params[0] / 3, wires=0)
             qml.CNOT(wires=(0, 1))
             return qml.probs(wires=[0, 1])