Update classical shadows (#708)

* More

* typo

* Trigger CI

* lightning req no depth

* Trigger CI

demonstrations/tutorial_classical_shadows.py

@@ -198,6 +198,7 @@ def calculate_classical_shadow(circuit_template, params, shadow_size, num_qubits
 # set up a two-qubit device with shots = 1 to ensure that we only get a single measurement
 dev = qml.device("default.qubit", wires=num_qubits, shots=1)
 
+
 # simple circuit to prepare rho
 @qml.qnode(dev)
 def local_qubit_rotation_circuit(params, **kwargs):
@@ -352,6 +353,7 @@ def shadow_state_reconstruction(shadow):
 
 dev = qml.device("default.qubit", wires=num_qubits, shots=1)
 
+
 # circuit to create a Bell state and measure it in
 # the bases specified by the 'observable' keyword argument.
 @qml.qnode(dev)
@@ -387,6 +389,7 @@ def bell_state_circuit(params, **kwargs):
 
 bell_state = np.array([[0.5, 0, 0, 0.5], [0, 0, 0, 0], [0, 0, 0, 0], [0.5, 0, 0, 0.5]])
 
+
 ##############################################################################
 # To measure the closeness we can use the operator norm.
 
@@ -435,6 +438,7 @@ def operator_2_norm(R):
 plt.ylabel("Distance")
 plt.show()
 
+
 ##############################################################################
 # As expected, when the number of snapshots increases, the state reconstruction
 # becomes closer to the ideal state.
@@ -520,8 +524,8 @@ def estimate_shadow_obervable(shadow, observable, k=10):
 
         # assign the splits temporarily
         b_lists_k, obs_lists_k = (
-            b_lists[i : i + shadow_size // k],
-            obs_lists[i : i + shadow_size // k],
+            b_lists[i: i + shadow_size // k],
+            obs_lists[i: i + shadow_size // k],
         )
 
         # find the exact matches for the observable of interest at the specified locations
@@ -581,8 +585,7 @@ def shadow_bound(error, observables, failure_rate=0.01):
 dev = qml.device("default.qubit", wires=num_qubits, shots=1)
 
 
-@qml.qnode(dev)
-def circuit(params, **kwargs):
+def circuit_base(params, **kwargs):
     observables = kwargs.pop("observable")
     for w in range(num_qubits):
         qml.Hadamard(wires=w)
@@ -594,6 +597,8 @@ def circuit(params, **kwargs):
     return [qml.expval(o) for o in observables]
 
 
+circuit = qml.QNode(circuit_base, dev)
+
 params = np.random.randn(2 * num_qubits)
 
 ##############################################################################
@@ -604,9 +609,9 @@ def circuit(params, **kwargs):
 #   O = \sum_{i=0}^{n-1} X_i X_{i+1} + Y_i Y_{i+1} + Z_i Z_{i+1}.
 
 list_of_observables = (
-    [qml.PauliX(i) @ qml.PauliX(i + 1) for i in range(num_qubits - 1)]
-    + [qml.PauliY(i) @ qml.PauliY(i + 1) for i in range(num_qubits - 1)]
-    + [qml.PauliZ(i) @ qml.PauliZ(i + 1) for i in range(num_qubits - 1)]
+        [qml.PauliX(i) @ qml.PauliX(i + 1) for i in range(num_qubits - 1)]
+        + [qml.PauliY(i) @ qml.PauliY(i + 1) for i in range(num_qubits - 1)]
+        + [qml.PauliZ(i) @ qml.PauliZ(i + 1) for i in range(num_qubits - 1)]
 )
 
 ##############################################################################
@@ -652,9 +657,10 @@ def circuit(params, **kwargs):
 
 dev_exact = qml.device("default.qubit", wires=num_qubits)
 # change the simulator to be the exact one.
-circuit.device = dev_exact
+circuit = qml.QNode(circuit_base, dev_exact)
+
 expval_exact = [
-    circuit(params, wires=dev_exact.wires, observable=[o]) for o in list_of_observables
+    circuit(params, observable=[o]) for o in list_of_observables
 ]
 
 ##############################################################################
@@ -691,7 +697,7 @@ def circuit(params, **kwargs):
 # calculate entanglement witnesses, and even find a way to approximate the von Neumann entropy.
 # These applications illustrate the potential power
 # of classical shadows for the characterization of quantum systems.
- 
+
 
 ##############################################################################
 # References

requirements.txt

@@ -16,7 +16,6 @@ pyscf==2.1.1
 cirq-core==0.14.1
 cirq-pasqal==0.14.1
 openfermionpyscf==0.5   # required by 2 tutorials: tutorial_quantum_chemistry and tutorial_adaptive_circuits and tutorial_diffable_shadows
-pennylane-lightning
 git+https://github.com/PennyLaneAI/pennylane.git
 git+https://github.com/PennyLaneAI/pennylane-sf.git
 git+https://github.com/PennyLaneAI/pennylane-cirq.git

requirements_no_deps.txt

@@ -1,2 +1,3 @@
 mitiq==0.13.0
 pyquil==2.21
+pennylane-lightning