Quantum Device Error, Device qiskit does not exist. Make sure the required plugin is installed

PennyLane Plugins PennyLane Qiskit
1

Hello! so I’m using google colab and I have tensorflow pennylane qiskit qiskit_ibm_runtime pennylane_qiskit. I restarted runtime too but the error is still there.

# Quantum Circuit Setup
n_qubits = 2  
n_layers = 1

#Available Backends
available_backends = service.backends(filters=lambda x: (x.configuration().n_qubits >= n_qubits) and (x.status().operational))
print("Available backends:")
for backend in available_backends:
    print(f"- {backend.name}")

# Choose a backend from the available ones
backend_name = 'ibm_brisbane'  

#Define the Quantum Device
dev = qml.device(
    'qiskit',           
    wires=n_qubits,
    backend=backend_name,
    provider=service,
    shots=1024
)

# Adjust the QNode
@qml.qnode(dev, interface='tf', diff_method='parameter-shift')
def quantum_circuit(inputs, weights):
    qml.templates.AngleEmbedding(inputs, wires=range(n_qubits), rotation='Y')
    qml.templates.StronglyEntanglingLayers(weights, wires=range(n_qubits))
    return [qml.expval(qml.PauliZ(wires=i)) for i in range(n_qubits)]

weight_shapes = {"weights": (n_layers, n_qubits, 3)}
quantum_layer = qml.qnn.KerasLayer(quantum_circuit, weight_shapes, output_dim=n_qubits)

If you want help with diagnosing an error, please put the full error message below:

DeviceError                               Traceback (most recent call last)
<ipython-input-9-0950305dbfbc> in <cell line: 71>()
     69 
     70 # **Define the Quantum Device**
---> 71 dev = qml.device(
     72     'qiskit',            
     73     wires=n_qubits,

/usr/local/lib/python3.10/dist-packages/pennylane/devices/device_constructor.py in device(name, *args, **kwargs)
    282         return dev
    283 
--> 284     raise qml.DeviceError(
    285         f"Device {name} does not exist. Make sure the required plugin is installed."
    286     )

DeviceError: Device qiskit does not exist. Make sure the required plugin is installed.

And, finally, make sure to include the versions of your packages. Specifically, show us the output of qml.about().

Name: PennyLane
Version: 0.39.0
Summary: PennyLane is a cross-platform Python library for quantum computing, quantum machine learning, and quantum chemistry. Train a quantum computer the same way as a neural network.
Home-page: GitHub - PennyLaneAI/pennylane: PennyLane is a cross-platform Python library for quantum computing, quantum machine learning, and quantum chemistry. Train a quantum computer the same way as a neural network.
Author:
Author-email:
License: Apache License 2.0
Location: /usr/local/lib/python3.10/dist-packages
Requires: appdirs, autograd, autoray, cachetools, networkx, numpy, packaging, pennylane-lightning, requests, rustworkx, scipy, toml, typing-extensions
Required-by: PennyLane-qiskit, PennyLane_Lightning

Platform info: Linux-6.1.85±x86_64-with-glibc2.35
Python version: 3.10.12
Numpy version: 1.26.4
Scipy version: 1.13.1
Installed devices:

  • qiskit.aer (PennyLane-qiskit-0.40.0.dev0)
  • qiskit.basicaer (PennyLane-qiskit-0.40.0.dev0)
  • qiskit.basicsim (PennyLane-qiskit-0.40.0.dev0)
  • qiskit.remote (PennyLane-qiskit-0.40.0.dev0)
  • default.clifford (PennyLane-0.39.0)
  • default.gaussian (PennyLane-0.39.0)
  • default.mixed (PennyLane-0.39.0)
  • default.qubit (PennyLane-0.39.0)
  • default.qutrit (PennyLane-0.39.0)
  • default.qutrit.mixed (PennyLane-0.39.0)
  • default.tensor (PennyLane-0.39.0)
  • null.qubit (PennyLane-0.39.0)
  • reference.qubit (PennyLane-0.39.0)
  • lightning.qubit (PennyLane_Lightning-0.39.0)
2

Hi @shay, welcome to the Forum!

Note that the device you want to use is actually ‘qiskit.remote’ instead of just ‘qiskit’. This is why you’re getting the error.

If you’re using Google Colab you actually don’t need to install all of those packages.
All you need is !pip install pennylane-qiskit :smile:

On the other hand, I noticed that you’re using the development version of the plugin (as opposed to v0.39 which is the stable version). This should work well at the moment but if you run into issues in the future let us know.

Finally, as a personal recommendation, I’ve had better luck using ‘ibm_sherbrooke’ instead of ‘ibm_brisbane’ recently. So if your simulation is taking too long you may want to consider changing your backend.

I hope this helps!