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### Summary
This PR moves all Stark experiments to new module
`qiskit_experiments.library.driven_freq_tuning` to define a module-wise
utility file. This util file contains the `StarkCoefficients` dataclass
to combine all seven coefficients from third-order polynomial fit
characterizing the Stark shift. This object is shared among all
experiments and analyses in new module.
In addition to this, `StarkP1Spectroscopy` allows users to scan xval in
units of either amplitude or frequency (previously only amplitude was
allowed). These two domains are mutually convertible with the
`StarkCoefficients` object. The domain conversion functions are also
included in the util file.
### Details and comments
Experiment option names are updated to be more general, namely `amp` ->
`xval` and new option `xval_type` is added. `xval_type` is either
`amplitude` or `frequency`. Experimentalist can directly specify the
target Stark shift by
```python
exp = StarkP1Spectroscopy((0,), backend=backend)
freqs = np.linspace(-70e6, 70e6, 31)
exp.set_experiment_options(
xvals=freqs,
xval_type="frequency",
)
```
Note that this requires pre-calibration of Stark shift coefficients with
`StarkRamseyXYAmpScan` experiment to convert specified frequencies into
tone amplitudes, and one must save the calibration results in the
experiment service. If the service is not available, one can also
directly provide these coefficients instead of providing a service
through the backend.
```python
exp.set_experiment_options(
xvals=test_freqs,
xval_type="frequency",
stark_coefficients=StarkCoefficients(...),
)
```
When the coefficients are already calibrated, one can estimate the
maximum Stark shift available within the power budget.
```python
min_freq, max_freq = util.find_min_max_frequency(-0.9, 0.9, coeffs)
```
---------
Co-authored-by: Will Shanks <[email protected]>
Co-authored-by: Will Shanks <[email protected]>
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