Hey @sun! Welcome to the forum

This error message doesn’t have anything to do with PennyLane lightning actually . The same error happens with `default.qubit`

:

```
import pennylane as qml
from pennylane import numpy as np
dev = qml.device("default.qubit", wires=2)
@qml.qnode(dev, diff_method="parameter-shift")
def circuit(params):
qml.RX(params[0], wires=0)
qml.RY(params[1], wires=0)
return qml.state()
params = np.array([0.1, 0.2], requires_grad=True)
qml.jacobian(circuit)(params)
```

```
ValueError: Computing the gradient of circuits that return the state with the parameter-shift rule gradient transform is not supported, as it is a hardware-compatible method.
```

The incompatibility here is due to the fact that the parameter-shift rule is intrinsically hardware compatible; it relies on the measurement being something that a real quantum computer can churn out, and the full quantum state is not one of those things . Check out this page for more info: qml.gradients.param_shift — PennyLane 0.32.0 documentation

If you return, say, an expectation value, then using the parameter-shift rule is all fine and dandy!

```
import pennylane as qml
from pennylane import numpy as np
dev = qml.device("lightning.qubit", wires=2)
@qml.qnode(dev, diff_method="parameter-shift")
def circuit(params):
qml.RX(params[0], wires=0)
qml.RY(params[1], wires=0)
qml.RX(params[2], wires=0)
return qml.expval(qml.PauliZ(0))
params = np.array([0.1, 0.2, 0.3], requires_grad=True)
qml.jacobian(circuit)(params)
```

```
array([-0.3875172 , -0.18884787, -0.38355704])
```

Let me know if this helps