Hi, I am using Pennylane to connect to Rigetti device, when i connect to Ankaa-2 or Ankaa-9Q-3 device (currently online) I get the Error: User program used too many qubits: 9 used and 0 available in the largest connected component. although i just use 1 qubit on my circuit.
I already config the secret of Rigetti account at ~/.qcs
Did I misconfigure or use it incorrectly? I would greatly appreciate the team’s help. Thank you very much.
My code:
import pennylane as qml
dev_qpu = qml.device('rigetti.qpu',device='Ankaa-9Q-3')
@qml.qnode(dev_qpu)
def func(x):
qml.RZ(x, wires=0)
return qml.expval(qml.PauliZ(0))
func(0.4)
The error message is:
C:\Users\thienthang.letran\Desktop\Workspace\Test-python\pennylane-rigetti\.venv\Scripts\python.exe C:\Users\thienthang.letran\Desktop\Workspace\Test-python\pennylane-rigetti\main.py
Traceback (most recent call last):
File "C:\Users\thienthang.letran\Desktop\Workspace\Test-python\pennylane-rigetti\main.py", line 13, in <module>
func(0.4)
File "C:\Users\thienthang.letran\Desktop\Workspace\Test-python\pennylane-rigetti\.venv\lib\site-packages\pennylane\workflow\qnode.py", line 1020, in __call__
return self._impl_call(*args, **kwargs)
File "C:\Users\thienthang.letran\Desktop\Workspace\Test-python\pennylane-rigetti\.venv\lib\site-packages\pennylane\workflow\qnode.py", line 1008, in _impl_call
res = self._execution_component(args, kwargs, override_shots=override_shots)
File "C:\Users\thienthang.letran\Desktop\Workspace\Test-python\pennylane-rigetti\.venv\lib\site-packages\pennylane\workflow\qnode.py", line 957, in _execution_component
res = qml.execute(
File "C:\Users\thienthang.letran\Desktop\Workspace\Test-python\pennylane-rigetti\.venv\lib\site-packages\pennylane\workflow\execution.py", line 771, in execute
results = ml_boundary_execute(tapes, execute_fn, jpc, device=device)
File "C:\Users\thienthang.letran\Desktop\Workspace\Test-python\pennylane-rigetti\.venv\lib\site-packages\pennylane\workflow\interfaces\autograd.py", line 147, in autograd_execute
return _execute(parameters, tuple(tapes), execute_fn, jpc)
File "C:\Users\thienthang.letran\Desktop\Workspace\Test-python\pennylane-rigetti\.venv\lib\site-packages\autograd\tracer.py", line 48, in f_wrapped
return f_raw(*args, **kwargs)
File "C:\Users\thienthang.letran\Desktop\Workspace\Test-python\pennylane-rigetti\.venv\lib\site-packages\pennylane\workflow\interfaces\autograd.py", line 168, in _execute
return execute_fn(tapes)
File "C:\Users\thienthang.letran\Desktop\Workspace\Test-python\pennylane-rigetti\.venv\lib\site-packages\pennylane\workflow\execution.py", line 212, in inner_execute
results = device.execute(transformed_tapes, execution_config=execution_config)
File "C:\Users\thienthang.letran\Desktop\Workspace\Test-python\pennylane-rigetti\.venv\lib\site-packages\pennylane\devices\modifiers\single_tape_support.py", line 32, in execute
results = batch_execute(self, circuits, execution_config)
File "C:\Users\thienthang.letran\Desktop\Workspace\Test-python\pennylane-rigetti\.venv\lib\site-packages\pennylane\devices\legacy_facade.py", line 456, in execute
results = _set_shots(dev, first_shot)(dev.batch_execute)(circuits, **kwargs)
File "C:\Users\thienthang.letran\AppData\Local\Programs\Python\Python310\lib\contextlib.py", line 79, in inner
return func(*args, **kwds)
File "C:\Users\thienthang.letran\Desktop\Workspace\Test-python\pennylane-rigetti\.venv\lib\site-packages\pennylane\devices\_qubit_device.py", line 510, in batch_execute
res = self.execute(circuit, **kwargs)
File "C:\Users\thienthang.letran\Desktop\Workspace\Test-python\pennylane-rigetti\.venv\lib\site-packages\pennylane_rigetti\qpu.py", line 201, in execute
return super().execute(circuit, **kwargs)
File "C:\Users\thienthang.letran\Desktop\Workspace\Test-python\pennylane-rigetti\.venv\lib\site-packages\pennylane_rigetti\qc.py", line 260, in execute
return super().execute(circuit, **kwargs)
File "C:\Users\thienthang.letran\Desktop\Workspace\Test-python\pennylane-rigetti\.venv\lib\site-packages\pennylane\devices\_qubit_device.py", line 316, in execute
self._samples = self.generate_samples()
File "C:\Users\thienthang.letran\Desktop\Workspace\Test-python\pennylane-rigetti\.venv\lib\site-packages\pennylane_rigetti\qpu.py", line 204, in generate_samples
return None if self._skip_generate_samples else super().generate_samples()
File "C:\Users\thienthang.letran\Desktop\Workspace\Test-python\pennylane-rigetti\.venv\lib\site-packages\pennylane_rigetti\qc.py", line 272, in generate_samples
self._compiled_program = self.compile()
File "C:\Users\thienthang.letran\Desktop\Workspace\Test-python\pennylane-rigetti\.venv\lib\site-packages\pennylane_rigetti\qc.py", line 254, in compile
return self.qc.compile(self.prog)
File "C:\Users\thienthang.letran\Desktop\Workspace\Test-python\pennylane-rigetti\.venv\lib\site-packages\pyquil\api\_quantum_computer.py", line 399, in compile
nq_program = self.compiler.quil_to_native_quil(program, protoquil=protoquil)
File "C:\Users\thienthang.letran\Desktop\Workspace\Test-python\pennylane-rigetti\.venv\lib\site-packages\pyquil\api\_abstract_compiler.py", line 123, in quil_to_native_quil
response = self._compiler_client.compile_to_native_quil(request)
File "C:\Users\thienthang.letran\Desktop\Workspace\Test-python\pennylane-rigetti\.venv\lib\site-packages\pyquil\api\_compiler_client.py", line 188, in compile_to_native_quil
response: rpcq.messages.NativeQuilResponse = rpcq_client.call(
File "C:\Users\thienthang.letran\Desktop\Workspace\Test-python\pennylane-rigetti\.venv\lib\site-packages\rpcq\_client.py", line 205, in call
raise utils.RPCError(reply.error)
rpcq._utils.RPCError: Unhandled error in host program:
User program used too many qubits: 9 used and 0 available in the largest connected component.
Process finished with exit code 1
The qml.about() output is:
Name: PennyLane
Version: 0.38.1
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: https://github.com/PennyLaneAI/pennylane
Author:
Author-email:
License: Apache License 2.0
Location: c:\users\thienthang.letran\desktop\workspace\test-python\pennylane-rigetti\.venv\lib\site-packages
Requires: appdirs, autograd, autoray, cachetools, networkx, numpy, packaging, pennylane-lightning, requests, rustworkx, scipy, toml, typing-extensions
Required-by: PennyLane-Rigetti, PennyLane_Lightning
Platform info: Windows-10-10.0.18362-SP0
Python version: 3.10.11
Numpy version: 1.26.4
Scipy version: 1.14.1
Installed devices:
- default.clifford (PennyLane-0.38.1)
- default.gaussian (PennyLane-0.38.1)
- default.mixed (PennyLane-0.38.1)
- default.qubit (PennyLane-0.38.1)
- default.qubit.autograd (PennyLane-0.38.1)
- default.qubit.jax (PennyLane-0.38.1)
- default.qubit.legacy (PennyLane-0.38.1)
- default.qubit.tf (PennyLane-0.38.1)
- default.qubit.torch (PennyLane-0.38.1)
- default.qutrit (PennyLane-0.38.1)
- default.qutrit.mixed (PennyLane-0.38.1)
- default.tensor (PennyLane-0.38.1)
- null.qubit (PennyLane-0.38.1)
- lightning.qubit (PennyLane_Lightning-0.38.0)
- rigetti.numpy_wavefunction (PennyLane-Rigetti-0.36.0.post0)
- rigetti.qpu (PennyLane-Rigetti-0.36.0.post0)
- rigetti.qvm (PennyLane-Rigetti-0.36.0.post0)
- rigetti.wavefunction (PennyLane-Rigetti-0.36.0.post0)
and I am using Forest SDK version 2.23.0 (Latest)