Manual demo fixes for 0.42 QA (#1436)

* Update `ahs_aquila` demo to render `qml.QuantumFunctionError`
deprecation warning
* Update `qnspsa` demo to stop unravelling parameters to cost function
* Update adjoint differentiation demos (`adjoint_diff_benchmarking` and
`tutorial_adjoint_diff`) to use autograd instead of JAX
  * Use log scaling for y-axis of second plot
* Update `getting_started_with_hybrid_jobs` demo to render deprecation
warning, and use a while loop to block until job metrics are available
* Update `quantum_volume` demo with new coupling map and instructions
for setting up API key

Author: mudit2812

_static/demonstration_assets/adjoint_diff/scaling.png

@@ -6,7 +6,7 @@
         }
     ],
     "dateOfPublication": "2021-11-23T00:00:00+00:00",
-    "dateOfLastModification": "2024-10-07T00:00:00+00:00",
+    "dateOfLastModification": "2025-07-11T00:00:00+00:00",
     "categories": [
         "Getting Started"
     ],

_static/demonstration_assets/quantum_volume/fake_lima.png

@@ -22,23 +22,20 @@
 import timeit
 import matplotlib.pyplot as plt
 import pennylane as qml
-import jax
-
-jax.config.update("jax_platform_name", "cpu")
-jax.config.update('jax_enable_x64', True)
+import pennylane.numpy as pnp
 
 plt.style.use("bmh")
 
 n_samples = 5
 
 
 def get_time(qnode, params):
-    globals_dict = {'grad': jax.grad, 'circuit': qnode, 'params': params}
+    globals_dict = {"grad": qml.grad, "circuit": qnode, "params": params}
     return timeit.timeit("grad(circuit)(params)", globals=globals_dict, number=n_samples)
 
 
 def wires_scaling(n_wires, n_layers):
-    key = jax.random.PRNGKey(42)
+    rng = pnp.random.default_rng(12345)
 
     t_adjoint = []
     t_ps = []
@@ -58,7 +55,7 @@ def circuit(params, wires):
 
         # set up the parameters
         param_shape = qml.StronglyEntanglingLayers.shape(n_wires=i_wires, n_layers=n_layers)
-        params = jax.random.normal(key, param_shape)
+        params = rng.normal(size=pnp.prod(param_shape), requires_grad=True).reshape(param_shape)
 
         t_adjoint.append(get_time(circuit_adjoint, params))
         t_backprop.append(get_time(circuit_backprop, params))
@@ -68,10 +65,10 @@ def circuit(params, wires):
 
 
 def layers_scaling(n_wires, n_layers):
-    key = jax.random.PRNGKey(42)
+    rng = pnp.random.default_rng(12345)
 
     dev = qml.device("lightning.qubit", wires=n_wires)
-    dev_python = qml.device('default.qubit', wires=n_wires)
+    dev_python = qml.device("default.qubit", wires=n_wires)
 
     t_adjoint = []
     t_ps = []
@@ -88,7 +85,7 @@ def circuit(params):
     for i_layers in n_layers:
         # set up the parameters
         param_shape = qml.StronglyEntanglingLayers.shape(n_wires=n_wires, n_layers=i_layers)
-        params = jax.random.normal(key, param_shape)
+        params = rng.normal(size=pnp.prod(param_shape), requires_grad=True).reshape(param_shape)
 
         t_adjoint.append(get_time(circuit_adjoint, params))
         t_backprop.append(get_time(circuit_backprop, params))
@@ -110,9 +107,9 @@ def circuit(params):
     # Generating the graphic
     fig, (ax1, ax2) = plt.subplots(1, 2, figsize=(10, 4))
 
-    ax1.plot(wires_list, adjoint_wires, '.-', label="adjoint")
-    ax1.plot(wires_list, ps_wires, '.-', label="parameter-shift")
-    ax1.plot(wires_list, backprop_wires, '.-', label="backprop")
+    ax1.plot(wires_list, adjoint_wires, ".-", label="adjoint")
+    ax1.plot(wires_list, ps_wires, ".-", label="parameter-shift")
+    ax1.plot(wires_list, backprop_wires, ".-", label="backprop")
 
     ax1.legend()
 
@@ -122,16 +119,17 @@ def circuit(params):
     ax1.set_yscale("log")
     ax1.set_title("Scaling with wires")
 
-    ax2.plot(layers_list, adjoint_layers, '.-', label="adjoint")
-    ax2.plot(layers_list, ps_layers, '.-', label="parameter-shift")
-    ax2.plot(layers_list, backprop_layers, '.-', label="backprop")
+    ax2.plot(layers_list, adjoint_layers, ".-", label="adjoint")
+    ax2.plot(layers_list, ps_layers, ".-", label="parameter-shift")
+    ax2.plot(layers_list, backprop_layers, ".-", label="backprop")
 
     ax2.legend()
 
     ax2.set_xlabel("Number of layers")
     ax2.set_xticks(layers_list)
-    ax2.set_ylabel("Time")
-    ax2.set_title("Scaling with Layers")
+    ax2.set_ylabel("Log Time")
+    ax2.set_yscale("log")
+    ax2.set_title("Scaling with layers")
 
     plt.savefig("scaling.png")
 

_static/demonstration_assets/quantum_volume/lima.svg

@@ -6,7 +6,7 @@
         }
     ],
     "dateOfPublication": "2023-05-16T00:00:00+00:00",
-    "dateOfLastModification": "2024-10-07T00:00:00+00:00",
+    "dateOfLastModification": "2025-07-11T00:00:00+00:00",
     "categories": ["Quantum Hardware", "Devices and Performance", "Quantum Computing"],
     "tags": [],
     "previewImages": [

demonstrations/adjoint_diff_benchmarking.metadata.json

@@ -132,7 +132,7 @@
 
 The modification of the energy levels when atoms are in proximity gives rise to Rydberg blockade,
 where atoms that have been driven by a pulse that would, in isolation, leave them in the excited state
-instead remain in the ground state due to neighboring atoms being excited. The distance within which two 
+instead remain in the ground state due to neighboring atoms being excited. The distance within which two
 neighboring atoms are effectively prevented from both being excited is referred to as the *blockade radius* :math:`R_b.`
 
 This brings us to our discussion of the second part of the Hamiltonian: the drive term.
@@ -220,6 +220,16 @@
     device_arn="arn:aws:braket:us-east-1::device/qpu/quera/Aquila",
     wires=3,
 )
+##############################################################################
+# .. rst-class:: sphx-glr-script-out
+#
+#
+#  .. code-block:: none
+#
+#      pennylane/pennylane/__init__.py:201: PennyLaneDeprecationWarning: pennylane.QuantumFunctionError is no longer accessible at top-level
+#      and must be imported as pennylane.exceptions.QuantumFunctionError. Support for top-level access will be removed in v0.43.
+#        warnings.warn(
+#
 
 rydberg_simulator = qml.device("braket.local.ahs", wires=3)
 

demonstrations/adjoint_diff_benchmarking.py

@@ -6,7 +6,7 @@
         }
     ],
     "dateOfPublication": "2023-10-16T00:00:00+00:00",
-    "dateOfLastModification": "2025-01-14T00:00:00+00:00",
+    "dateOfLastModification": "2025-07-11T00:00:00+00:00",
     "categories": [
         "Devices and Performance"
     ],