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coruscating authored Nov 29, 2023
2 parents b048f98 + 4623ea5 commit ff3fb66
Showing 5 changed files with 6 additions and 8 deletions.
4 changes: 2 additions & 2 deletions docs/tutorials/calibrations.rst
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@@ -195,8 +195,8 @@ Run the calibration experiment:

The instance of ``calibrations`` has been automatically updated with the measured
frequency, as shown below. In addition to the columns shown below, ``calibrations`` also
store the group to which a value belongs, whether a values is valid or not and the
experiment id that produce a value.
stores the group to which a value belongs, whether a value is valid or not, and the
experiment id that produced a value.

.. jupyter-execute::

2 changes: 1 addition & 1 deletion qiskit_experiments/calibration_management/__init__.py
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@@ -23,7 +23,7 @@
otherwise indicated.
Calibrating qubit setups is the task of finding the pulse shapes and parameter
values that maximizes the fidelity of the resulting quantum operations. This
values that maximize the fidelity of the resulting quantum operations. This
therefore requires experiments which are analyzed to extract parameter values.
Furthermore, the resulting parameter values and schedules must be managed. The
calibration management module in Qiskit experiments allows users to manage
2 changes: 1 addition & 1 deletion requirements-dev.txt
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@@ -1,4 +1,4 @@
qiskit-terra>=0.45.0
qiskit>=0.45.0
black~=22.0
fixtures
stestr
2 changes: 1 addition & 1 deletion requirements-extras.txt
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@@ -1,5 +1,5 @@
qiskit-ibm-provider>=0.6.1 # for submitting experiments to backends through the IBM provider
cvxpy>=1.3.2 # for tomography
scikit-learn # for discriminators
qiskit-aer>=0.11.0,<=0.12.2 # temporary version pin until 0.13.1 release
qiskit-aer>=0.11.0
qiskit_dynamics>=0.4.0 # for the PulseBackend
4 changes: 1 addition & 3 deletions test/library/tomography/tomo_utils.py
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@@ -87,9 +87,7 @@ def readout_noise_model(num_qubits, seed=None):
p1g0s = 0.15 * rng.random(num_qubits)
p0g1s = 0.3 * rng.random(num_qubits)
amats = np.stack([[1 - p1g0s, p1g0s], [p0g1s, 1 - p0g1s]]).T
# Set `basis_gates` so that reset is included.
# See https://github.com/Qiskit/qiskit-aer/issues/1975
noise_model = NoiseModel(basis_gates=["id", "rz", "sx", "cx", "reset"])
noise_model = NoiseModel()
for i, amat in enumerate(amats):
noise_model.add_readout_error(amat.T, [i])
return noise_model

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