Hello,

I’m trying to calculate the metric_tensor of a subset of my total circuit before measurement takes place. In particular, in my code below, I want to calculate it after `U1(params)`

. My code is as follows:

```
def get_observables(N):
observables = []
# Coupling operators
for i in range(N-1):
observables.append(qml.PauliZ(i) @ qml.PauliZ(i+1))
# Identity operator
for i in range(N):
observables.append(qml.Identity(i))
return observables
def get_coeffs(params, N):
coeffs = []
# Coupling coeffs
for i in range(N-1):
coeffs.append((params[0])**2/params[1])
# Constant coeffs
for i in range(N):
coeffs.append(params[1])
return coeffs
def create_Hamiltonian(params):
coeffs = get_coeffs(params, nqubits)
obs = get_observables(nqubits)
H = qml.Hamiltonian(coeffs, obs, id='QP')
return H
def create_params(L, scale = 0.1):
params = np.array([], requires_grad=True)
for i in range(L):
J = scale*np.random.uniform()
O = 1.0
theta = scale*np.random.uniform()
params = np.append(params, [J, O, theta], requires_grad=True)
return params
dev = qml.device("default.qubit", wires=nqubits, shots=None)
def U1(params):
start_index = 0
num_trotter_steps = 10
for i in range(L):
new_params = params[start_index:start_index + 3]
H = create_Hamiltonian(new_params[0:2])
qml.evolve(H, num_steps = num_trotter_steps)
for j in range(nqubits):
qml.RX(new_params[2], wires=j)
start_index += 3 # Put state_index in again
@qml.qnode(dev)
def circuit(params, phi):
U1(params)
for z in range(nqubits): # Perturbation
qml.RY(phi[0], wires = z)
qml.adjoint(U1)(params)
expectation_values = [qml.expval(qml.PauliY(wires=i)) for i in range(nqubits)]
return expectation_values # List of expected values of every input qubit
```

This is the output of my `qml.about()`

```
Name: PennyLane
Version: 0.33.1
Summary: PennyLane is a Python quantum machine learning library by Xanadu Inc.
Home-page: https://github.com/PennyLaneAI/pennylane
Author:
Author-email:
License: Apache License 2.0
Location: /.../python3.11/site-packages
Requires: appdirs, autograd, autoray, cachetools, networkx, numpy, pennylane-lightning, requests, rustworkx, scipy, semantic-version, toml, typing-extensions
Required-by: PennyLane-Lightning
Platform info: macOS-13.4.1-x86_64-i386-64bit
Python version: 3.11.5
Numpy version: 1.26.2
Scipy version: 1.11.4
Installed devices:
- default.gaussian (PennyLane-0.33.1)
- default.mixed (PennyLane-0.33.1)
- default.qubit (PennyLane-0.33.1)
- default.qubit.autograd (PennyLane-0.33.1)
- default.qubit.jax (PennyLane-0.33.1)
- default.qubit.legacy (PennyLane-0.33.1)
- default.qubit.tf (PennyLane-0.33.1)
- default.qubit.torch (PennyLane-0.33.1)
- default.qutrit (PennyLane-0.33.1)
- null.qubit (PennyLane-0.33.1)
- lightning.qubit (PennyLane-Lightning-0.33.1)
```

Any help would be appreciated. Thanks in advance!