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I'm trying to run some quantum circuits on qasm simulator using the noise information from IBM Q quantum device:

provider = IBMQ.load_account()
backend = provider.get_backend('ibmq_casablanca') 
noise_model = NoiseModel.from_backend(backend)
coupling_map = backend.configuration().coupling_map
basis_gates = noise_model.basis_gates

As I print(noise_model), I got

NoiseModel:
  Basis gates: ['cx', 'id', 'reset', 'rz', 'sx', 'x']
  Instructions with noise: ['reset', 'measure', 'x', 'sx', 'id', 'cx']
  Qubits with noise: [0, 1, 2, 3, 4, 5, 6]
  Specific qubit errors: [('id', [0]), ('id', [1]), ('id', [2]), ('id', [3]), ('id', [4]), ('id', [5]), ('id', [6]), ('sx', [0]), ('sx', [1]), ('sx', [2]), ('sx', [3]), ('sx', [4]), ('sx', [5]), ('sx', [6]), ('x', [0]), ('x', [1]), ('x', [2]), ('x', [3]), ('x', [4]), ('x', [5]), ('x', [6]), ('cx', [6, 5]), ('cx', [5, 6]), ('cx', [5, 4]), ('cx', [4, 5]), ('cx', [5, 3]), ('cx', [3, 5]), ('cx', [3, 1]), ('cx', [1, 3]), ('cx', [1, 2]), ('cx', [2, 1]), ('cx', [1, 0]), ('cx', [0, 1]), ('reset', [0]), ('reset', [1]), ('reset', [2]), ('reset', [3]), ('reset', [4]), ('reset', [5]), ('reset', [6]), ('measure', [0]), ('measure', [1]), ('measure', [2]), ('measure', [3]), ('measure', [4]), ('measure', [5]), ('measure', [6])]

So I could see the source of errors as well as qubit connections. However, I wonder as I give this information to qasm simulator and run the experiments, am I using the real-time error rate as the noise model?

result = execute(circ, Aer.get_backend('qasm_simulator'),
                 coupling_map=coupling_map,
                 basis_gates=basis_gates,
                 noise_model=noise_model).result()

If so, should we expect to see any difference between the qasm results and the results from real quantum devices? (I could not print out the noise information, so I'm a bit confused which error values we are using.) Thanks!

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2 Answers 2

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I expect you get the Noise Model from the calibrated data of the hardware, however I am not sure how often it is updated. I doubt that it is live or even daily.

You can check the noise model by running

noise_model._local_quantum_errors and noise_model._local_readout_errors

For instance:

device = provider.get_backend('ibmq_armonk')
noise_model = NoiseModel.from_backend(device.properties())
print(noise_model._local_quantum_errors)
print(noise_model._local_readout_errors)

gives

{'id': {'0': QuantumError([([{'name': 'kraus', 'qubits': [0], 'params': [array([[-0.99994317+0.j,  0.        +0.j],
       [ 0.        +0.j, -0.99972553+0.j]]), array([[-0.00832337+0.j,  0.        +0.j],
       [ 0.        +0.j,  0.00832518+0.j]]), array([[0.        +0.j, 0.        +0.j],
       [0.00666197+0.j, 0.        +0.j]]), array([[0.        +0.j, 0.02189868+0.j],
       [0.        +0.j, 0.        +0.j]])]}], 1.0)])}, 'sx': {'0': QuantumError([([{'name': 'kraus', 'qubits': [0], 'params': [array([[-0.99994317+0.j,  0.        +0.j],
       [ 0.        +0.j, -0.99972553+0.j]]), array([[-0.00832337+0.j,  0.        +0.j],
       [ 0.        +0.j,  0.00832518+0.j]]), array([[0.        +0.j, 0.        +0.j],
       [0.00666197+0.j, 0.        +0.j]]), array([[0.        +0.j, 0.02189868+0.j],
       [0.        +0.j, 0.        +0.j]])]}], 1.0)])}, 'x': {'0': QuantumError([([{'name': 'kraus', 'qubits': [0], 'params': [array([[-0.99994317+0.j,  0.        +0.j],
       [ 0.        +0.j, -0.99972553+0.j]]), array([[-0.00832337+0.j,  0.        +0.j],
       [ 0.        +0.j,  0.00832518+0.j]]), array([[0.        +0.j, 0.        +0.j],
       [0.00666197+0.j, 0.        +0.j]]), array([[0.        +0.j, 0.02189868+0.j],
       [0.        +0.j, 0.        +0.j]])]}], 1.0)])}}
{'0': ReadoutError([[0.9756 0.0244]
 [0.0376 0.9624]])}
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IBM Quantum Systems are calibrated daily, and the system properties update once this calibration sequence is complete. It means that your noise model could change on a daily basis.

More information in the documentation:

https://quantum-computing.ibm.com/lab/docs/iql/manage/systems/properties

https://quantum-computing.ibm.com/admin/docs/admin/calibration-jobs

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