# Error measuring expval on qiskit cpu **URL:** \ **Category:** PennyLane Qiskit\ **Created:** [October 16, 2024, 12:08am UTC](https://discuss.pennylane.ai/t/error-measuring-expval-on-qiskit-cpu/7314 "2024-10-16T00:08:57Z")\ **Posts on this page:** 2\ **Page:** 1
**Author:** ![ecasciaro\_unifi](https://yyz2.discourse-cdn.com/flex012/user_avatar/discuss.pennylane.ai/ecasciaro_unifi/32/3239_2.png) [@ecasciaro\_unifi](https://discuss.pennylane.ai/u/ecasciaro_unifi)\ **Post date:** [October 16, 2024, 12:08am UTC](https://discuss.pennylane.ai/t/error-measuring-expval-on-qiskit-cpu/7314/1 "2024-10-16T00:08:57Z")
Hello everyone! I was trying to use the qiskit plugin to get access to IBM QPUs, but I get the following error when measuring the expectation value of an operator: `ValueError: The number of qubits of the circuit (127) does not match the number of qubits of the (0,)-th observable (4)`. According to this [post](https://quantumcomputing.stackexchange.com/questions/38790/valueerror-the-number-of-qubits-of-the-circuit-127-does-not-match-the-number) the error is caused by the observable not being expressed using the **Instruction Set Architecture** of the QPU. How can I perform this optimisation in Pennylane, if this is the issue? ```auto import pennylane as qml from qiskit_ibm_runtime import QiskitRuntimeService service = QiskitRuntimeService() backend = service.least_busy(min_num_qubits=4) print(backend.name) device = qml.device("qiskit.remote", wires=4, backend=backend) @qml.qnode(device) def circuit_probs(): qml.Hadamard(wires=0) return qml.probs() @qml.qnode(device) def circuit_expval(): qml.Hadamard(wires=0) return qml.expval(qml.PauliZ(0)) print(circuit_probs()) print(circuit_expval()) ``` If you want help with diagnosing an error, please put the full error message below: ```auto --------------------------------------------------------------------------- ValueError Traceback (most recent caall last) Cell In[1], line 19 16 return qml.expval(qml.PauliZ(0)) 18 print(circuit_probs()) ---> 19 print(circuit_expval()) File ~/miniforge3/envs/stations/lib/python3.10/site-packages/pennylane/workflow/qnode.py:1020, in QNode. __caall__ (self, *args, **kwargs) 1018 if qml.capture.enabled(): 1019 return qml.capture.qnode_caall(self, *args, **kwargs) -> 1020 return self._impl_caall(*args, **kwargs) File ~/miniforge3/envs/stations/lib/python3.10/site-packages/pennylane/workflow/qnode.py:1008, in QNode._impl_caall(self, *args, **kwargs) 1005 self._update_gradient_fn(shots=override_shots, tape=self._tape) 1007 try: -> 1008 res = self._execution_component(args, kwargs, override_shots=override_shots) 1009 finally: 1010 if old_interface == "auto": File ~/miniforge3/envs/stations/lib/python3.10/site-packages/pennylane/workflow/qnode.py:957, in QNode._execution_component(self, args, kwargs, override_shots) 951 warnings.filterwarnings( 952 action="ignore", 953 message=r".*argument is deprecated and will be removed in version 0.39.*", 954 category=qml.PennyLaneDeprecationWarning, 955 ) 956 # pylint: disable=unexpected-keyword-arg --> 957 res = qml.execute( 958 (self._tape,), 959 device=self.device, 960 gradient_fn=self.gradient_fn, 961 interface=self.interface, 962 transform_program=full_transform_program, 963 inner_transform=inner_transform_program, 964 config=config, 965 gradient_kwargs=self.gradient_kwargs, 966 override_shots=override_shots, 967 **execute_kwargs, 968 ) 969 res = res[0] 971 # convert result to the interface in case the qfunc has no parameters File ~/miniforge3/envs/stations/lib/python3.10/site-packages/pennylane/workflow/execution.py:771, in execute(tapes, device, gradient_fn, interface, transform_program, inner_transform, config, grad_on_execution, gradient_kwargs, cache, cachesize, max_diff, override_shots, expand_fn, max_expansion, device_batch_transform, device_vjp, mcm_config) 763 ml_boundary_execute = _get_ml_boundary_execute( 764 interface, 765 config.grad_on_execution, 766 config.use_device_jacobian_product, 767 differentiable=max_diff > 1, 768 ) 770 if interface in jpc_interfaces: --> 771 results = ml_boundary_execute(tapes, execute_fn, jpc, device=device) 772 else: 773 results = ml_boundary_execute( 774 tapes, device, execute_fn, gradient_fn, gradient_kwargs, _n=1, max_diff=max_diff 775 ) File ~/miniforge3/envs/stations/lib/python3.10/site-packages/pennylane/workflow/interfaces/autograd.py:147, in autograd_execute(tapes, execute_fn, jpc, device) 142 # pylint misidentifies autograd.builtins as a dict 143 # pylint: disable=no-member 144 parameters = autograd.builtins.tuple( 145 [autograd.builtins.list(t.get_parameters()) for t in tapes] 146 ) --> 147 return _execute(parameters, tuple(tapes), execute_fn, jpc) File ~/miniforge3/envs/stations/lib/python3.10/site-packages/autograd/tracer.py:48, in primitive..f_wrapped(*args, **kwargs) 46 return new_box(ans, trace, node) 47 else: ---> 48 return f_raw(*args, **kwargs) File ~/miniforge3/envs/stations/lib/python3.10/site-packages/pennylane/workflow/interfaces/autograd.py:168, in _execute(parameters, tapes, execute_fn, jpc) 150 @autograd.extend.primitive 151 def _execute( 152 parameters, (...) 155 jpc, 156 ): # pylint: disable=unused-argument 157 """Autodifferentiable wrapper around a way of executing tapes. 158 159 Args: (...) 166 167 """ --> 168 return execute_fn(tapes) File ~/miniforge3/envs/stations/lib/python3.10/site-packages/pennylane/workflow/execution.py:212, in _make_inner_execute..inner_execute(tapes, **_) 209 transformed_tapes, transform_post_processing = transform_program(tapes) 211 if transformed_tapes: --> 212 results = device.execute(transformed_tapes, execution_config=execution_config) 213 else: 214 results = () File ~/miniforge3/envs/stations/lib/python3.10/site-packages/pennylane_qiskit/qiskit_device.py:66, in custom_simulator_tracking..execute(self, circuits, execution_config) 64 @wraps(tracked_execute) 65 def execute(self, circuits, execution_config=DefaultExecutionConfig): ---> 66 results = tracked_execute(self, circuits, execution_config) 67 if self.tracker.active: 68 res = [] File ~/miniforge3/envs/stations/lib/python3.10/site-packages/pennylane/devices/modifiers/simulator_tracking.py:30, in _track_execute..execute(self, circuits, execution_config) 28 @wraps(untracked_execute) 29 def execute(self, circuits, execution_config=DefaultExecutionConfig): ---> 30 results = untracked_execute(self, circuits, execution_config) 31 if isinstance(circuits, QuantumScript): 32 batch = (circuits,) File ~/miniforge3/envs/stations/lib/python3.10/site-packages/pennylane_qiskit/qiskit_device.py:590, in QiskitDevice.execute(self, circuits, execution_config) 587 finally: 588 session.close() --> 590 with execute_circuits(session) as results: 591 return results File ~/miniforge3/envs/stations/lib/python3.10/contextlib.py:135, in _GeneratorContextManager. __enter__ (self) 133 del self.args, self.kwds, self.func 134 try: --> 135 return next(self.gen) 136 except StopIteration: 137 raise RuntimeError("generator didn't yield") from None File ~/miniforge3/envs/stations/lib/python3.10/site-packages/pennylane_qiskit/qiskit_device.py:585, in QiskitDevice.execute..execute_circuits(session) 583 else: 584 execute_fn = self._execute_sampler --> 585 results.append(execute_fn(circ, session)) 586 yield results 587 finally: File ~/miniforge3/envs/stations/lib/python3.10/site-packages/pennylane_qiskit/qiskit_device.py:656, in QiskitDevice._execute_estimator(self, circuit, session) 651 # split into one caall per measurement 652 # could technically be more efficient if there are some observables where we ask 653 # for expectation value and variance on the same observable, but spending time on 654 # that right now feels excessive 655 circ_and_obs = [(compiled_circuits[0], pauli_observables)] --> 656 result = estimator.run( 657 circ_and_obs, 658 precision=np.sqrt(1 / circuit.shots.total_shots) if circuit.shots else None, 659 ).result() 660 self._current_job = result 661 result = self._process_estimator_job(circuit.measurements, result) File ~/miniforge3/envs/stations/lib/python3.10/site-packages/qiskit_ibm_runtime/estimator.py:191, in EstimatorV2.run(self, pubs, precision) 189 if precision <= 0: 190 raise ValueError("The precision value must be strictly greater than 0.") --> 191 coerced_pubs = [EstimatorPub.coerce(pub, precision) for pub in pubs] 192 validate_estimator_pubs(coerced_pubs) 193 return self._run(coerced_pubs) File ~/miniforge3/envs/stations/lib/python3.10/site-packages/qiskit_ibm_runtime/estimator.py:191, in (.0) 189 if precision <= 0: 190 raise ValueError("The precision value must be strictly greater than 0.") --> 191 coerced_pubs = [EstimatorPub.coerce(pub, precision) for pub in pubs] 192 validate_estimator_pubs(coerced_pubs) 193 return self._run(coerced_pubs) File ~/miniforge3/envs/stations/lib/python3.10/site-packages/qiskit/primitives/containers/estimator_pub.py:162, in EstimatorPub.coerce(cls, pub, precision) 159 if len(pub) > 3 and pub[3] is not None: 160 precision = pub[3] --> 162 return cls( 163 circuit=circuit, 164 observables=observables, 165 parameter_values=parameter_values, 166 precision=precision, 167 validate=True, 168 ) File ~/miniforge3/envs/stations/lib/python3.10/site-packages/qiskit/primitives/containers/estimator_pub.py:85, in EstimatorPub. __init__ (self, circuit, observables, parameter_values, precision, validate) 79 raise ValueError( 80 f"The observables shape {self.observables.shape} and the " 81 f"parameter values shape {self.parameter_values.shape} are not broadcastable." 82 ) from ex 84 if validate: ---> 85 self.validate() File ~/miniforge3/envs/stations/lib/python3.10/site-packages/qiskit/primitives/containers/estimator_pub.py:188, in EstimatorPub.validate(self) 186 num_qubits = len(next(iter(observable))) 187 if self.circuit.num_qubits != num_qubits: --> 188 raise ValueError( 189 f"The number of qubits of the circuit ({self.circuit.num_qubits}) does " 190 f"not match the number of qubits of the {i}-th observable ({num_qubits})." 191 ) 193 # Cross validate circuits and parameter_values 194 num_parameters = self.parameter_values.num_parameters ValueError: The number of qubits of the circuit (127) does not match the number of qubits of the (0,)-th observable (4). ``` And, finally, make sure to include the versions of your packages. Specifically, show us the output of `qml.about()`. ```auto Name: PennyLane Version: 0.38.0 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: https://github.com/PennyLaneAI/pennylane Author: Author-email: License: Apache License 2.0 Location: /Users/manu/miniforge3/envs/stations/lib/python3.10/site-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: macOS-14.7-x86_64-i386-64bit Python version: 3.10.13 Numpy version: 1.26.4 Scipy version: 1.12.0 Installed devices: - qiskit.aer (PennyLane-qiskit-0.38.0) - qiskit.basicaer (PennyLane-qiskit-0.38.0) - qiskit.basicsim (PennyLane-qiskit-0.38.0) - qiskit.remote (PennyLane-qiskit-0.38.0) - lightning.qubit (PennyLane_Lightning-0.38.0) - default.clifford (PennyLane-0.38.0) - default.gaussian (PennyLane-0.38.0) - default.mixed (PennyLane-0.38.0) - default.qubit (PennyLane-0.38.0) - default.qubit.autograd (PennyLane-0.38.0) - default.qubit.jax (PennyLane-0.38.0) - default.qubit.legacy (PennyLane-0.38.0) - default.qubit.tf (PennyLane-0.38.0) - default.qubit.torch (PennyLane-0.38.0) - default.qutrit (PennyLane-0.38.0) - default.qutrit.mixed (PennyLane-0.38.0) - default.tensor (PennyLane-0.38.0) - null.qubit (PennyLane-0.38.0) ``` ---
**Author:** ![CatalinaAlbornoz](https://yyz2.discourse-cdn.com/flex012/user_avatar/discuss.pennylane.ai/catalinaalbornoz/32/1196_2.png) [@CatalinaAlbornoz](https://discuss.pennylane.ai/u/CatalinaAlbornoz)\ **Post date:** [October 18, 2024, 4:08am UTC](https://discuss.pennylane.ai/t/error-measuring-expval-on-qiskit-cpu/7314/2 "2024-10-18T04:08:57Z")
Hi @ecasciaro_unifi , welcome to the Forum! You should specify wires=127 since this is how many qubits the actual device has. Let me know if this fixes the issue for you!