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Rabi #74
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Rabi #74
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* Black lint.
* Docstring, black and lint. * Improved fit guessing.
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There see
Co-authored-by: Naoki Kanazawa <[email protected]>
* Added some circuit tests.
* Improved fit guesses. * Improved tests.
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I put a couple questions but it looks good to me.
I wonder about allowing a pulse as an experiment option, but the schedule is probably good enough.
* * Skeleton of the Rabi experiment. * * Completed the fit function. * * Added test for the rabi * * Added test and fixed variance issue. * * Added draft of end to end test. * * Added TODO. * * data processing and options. * * Updated the options for the Rabi experiment. * * Added more resilience in sigmas processing and a test. * * Improved tests. * * Refactored tests to use mock IQ backends. * Black lint. * * Improved fitting. * * Gave fit function variables comprehensive names. * Docstring, black and lint. * Improved fit guessing. * * black. * * Refactored tests based on IQ data to lighten the code. * Update qiskit_experiments/calibration/experiments/rabi.py Co-authored-by: Naoki Kanazawa <[email protected]> * * Aligned Rabi API to current varsion. * Added some circuit tests. * * Fixed docstring typo. * * Docstring fix. * * Fix error message. * * Refactored mock_backend. * * Added np.integer to Probability node. * * Improved test. * * Fixed docstring and label. * * Aligned Rabi with the curve fitting PR. * * Improved the mock IQ backend. * * Black and lint. * * Added amplitude rounding. * * Added plot labels in defaults. * * Docstrings. * * Changed the label of the report. * * Remove normalization option in Rabi. * * Added normalization option to the Rabi experiment. * * Updated phase initial guesses. * * Moved normalization option from run to experiment options. * * Aligned Rabi with master. * Improved fit guesses. * Improved tests. * * Changed a and b to amp and baseline. * Added an extra test. * * Black. Co-authored-by: Naoki Kanazawa <[email protected]>
Summary
The PR implements a Rabi experiment.
Details and comments
The Rabi experiment is implemented by scanning the amplitude of a single-qubit pulse such as a Drag or Gaussian pulse. Since a discriminator is typically not available the data is analyzed using a SVD. The resulting signal is then fit to a cosine function.