I am trying to build a realistic noise model in Qiskit for a quantum computer that might be available 2-3 few years from now on. I tried to start from an existing noise model generated from a fake device, use NoiseModel.to_dict() method, tweak the dictionary a bit and load it back using the NoiseModel.from_dict() method. Unfortunately, the from_dict() method is now deprecated. Is there another method to adjust an existing noise model? There are several examples around on how to build a custom noise model in Qiskit, but I do not trust myself building a realistic one because there are so many settings that can be adjusted.


1 Answer 1


There might be a better manner to do that, but anyway:

You can generate a NoiseModel instance from an actual backend (or from fake V1 backends) by using the NoiseModel.from_backend() method.

Then it is possible to further customize the noise model using the methods and attributes of the NoiseModel class.

For example, this piece of code generates a noise model from ibmq_quito and alters one of its readout errors:

from qiskit import IBMQ
from qiskit.providers.aer.noise import NoiseModel, ReadoutError

provider = IBMQ.load_account()
backend = provider.get_backend('ibmq_quito')
nm_1 = NoiseModel.from_backend(backend)

print('The readout errors defined before altering are:')

q0_RO_er = ReadoutError([[0.8,0.2],[0.2,0.8]])
nm_1._local_readout_errors[(0,)] = q0_RO_er

print('The readout errors after altering are:')

This is an example for altering existing definitions. Adding error deifnitions is easier, and can be done using the add_XXX methods of the NoiseModel class (there are several).

  • $\begingroup$ Indeed, using NoiseModel __ dict __ method gives access to NoiseModel internals. $\endgroup$
    – Radu M.
    Commented Sep 19, 2022 at 8:43
  • $\begingroup$ @Radu M. what do you mean? $\endgroup$
    – Ohad
    Commented Sep 19, 2022 at 14:29
  • $\begingroup$ The dict member provides access to NoiseModel internals. I used it to validate your proposed solution. $\endgroup$
    – Radu M.
    Commented Sep 21, 2022 at 7:06

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