0
$\begingroup$

I wish to be able to model a quantum computer with all the noise sources of an IBM quantum computer. For a given set of T1, T2, readout_errors, U2_errors and CNOT errors I want to know how to include all these errors. I can run a quantum circuit using the expected noise from a particular computer through the following code

backend = provider.get_backend('ibmqx2')
    noise_model = NoiseModel.from_backend(backend)
# Get coupling map from backend
    coupling_map = backend.configuration().coupling_map
# Get basis gates from noise model
    basis_gates = noise_model.basis_gates

This runs my code with the noise from ibmqx2. I then try to implement each noise source. For example if the single qubit U2 error rate is er1, I implement this as follows:

 error_1 = noise.depolarizing_error(er1, 1)
noise_model.add_quantum_error(error_1, ['u1', 'u2', 'u3','h'],[0])

I implement the two qubit and readout errors in the same way. Is this correct? Also how do I implement the errors associated with the T1 and T2 values? I am asking because my current model when I add each noise source myself does not match when I simply import the noise model. I wish to reconcile this.

$\endgroup$
0
$\begingroup$

If you are intending to add noise to the specific qubit (qubit [0] in this case) then this seems to be correct. At least from looking at this document: Building Noise Models

| improve this answer | |
$\endgroup$
  • $\begingroup$ Yes but the results from this model don't match the results from when I directly import the noise model. I suspect this has to do with the times T1 and T2 but I am not sure how $\endgroup$ – LOC Oct 18 at 5:19
  • $\begingroup$ Make sure to note that the device noise model is not fixed either. The device is being calibrated a couple of times a day (I think) and the noise_model will change based on the calibration results. $\endgroup$ – KAJ226 Oct 18 at 6:37

Your Answer

By clicking “Post Your Answer”, you agree to our terms of service, privacy policy and cookie policy

Not the answer you're looking for? Browse other questions tagged or ask your own question.