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.
$\begingroup$
$\endgroup$
Add a comment
|
1 Answer
$\begingroup$
$\endgroup$
3
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:')
print(nm_1._local_readout_errors)
q0_RO_er = ReadoutError([[0.8,0.2],[0.2,0.8]])
nm_1._local_readout_errors[(0,)] = q0_RO_er
print()
print('The readout errors after altering are:')
print(nm_1._local_readout_errors)
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).
