Auto

Automatic scripts for qubit measurements.

🔵BaseAuto

a = quick.auto.BaseAuto(var, silent=False, data_path=None, soccfg=None, soc=None)

General base class for other auto scripts.

Parameters:

var experimental variables. It will NOT be modified.
silent=False (bool) whether to avoid any printing.
data_path=None (str) directory to save data. If not provided, data will not be saved to file.
soccfg=None QICK board socket config object. If not provided, the last connected one will be used by calling quick.getSoc().
soc=None QICK board socket object.

- BaseAuto.var

a.var

The experiment variable dictionary used in the experiment.

- BaseAuto.data

a.data

Data measured or loaded. Will be transposed from the raw data.

The Mercator instance created by the experiment.

- BaseAuto.load_data

a.load_data(*paths)

Load and transpose data using quick.load_data.

Parameters:

*paths (str) arbitrary number of data paths can be passed in. Multiple data will be combined.

- BaseAuto.update

a.update(v)

Update relevant variables in external dictionary.

Parameters:

v (dict) experiment variable to be updated. Will be modified!

🟢Resonator

a = quick.auto.Resonator(**kwargs)

Determine the readout power and readout frequency from PowerSpectroscopy.

- Resonator.calibrate

var, fig = a.calibrate(**kwargs)

Calibrate the experiment variables from data. Use quick.experiment to acquire data when data is not available.

Return:

var (dict|bool) self.var if succeeded. False if failed.
fig generated plot

🟢ReadoutLength

a = quick.auto.ReadoutLength(**kwargs)

Determine the readout length from coupling quality factor, using high readout power. r_length will be set to min(10, Qc / f).

- ReadoutLength.calibrate

var, fig = a.calibrate(**kwargs)

Calibrate the experiment variables from data. Use quick.experiment to acquire data when data is not available.

Return:

var (dict|bool) self.var if succeeded. False if failed.
fig generated plot

🟢QubitFreq

a = quick.auto.QubitFreq(**kwargs)

Determine the qubit frequency from QubitSpectroscopy.

- QubitFreq.calibrate

var, fig = a.calibrate(q_freq_min=3000, q_freq_max=5000, q_gain=0.5, **kwargs)

Run the calibration.

Parameters:

q_freq_min=3000 (float) [MHz] mininum qubit frequency.
q_freq_max=5000 (float) [MHz] maximum qubit frequency.
q_gain=0.5 (float) [0, 1] initial gain for qubit pulse.

Return:

var (dict|bool) self.var if succeeded. False if failed.
fig generated plot

🟢PiPulseLength

a = quick.auto.PiPulseLength(**kwargs)

Determine the qubit pulse length from Rabi, sweeping pi pulse length and fit the result.

- PiPulseLength.calibrate

var, fig = a.calibrate(q_length_max=0.5, cycles=[], tol=0.5, **kwargs)

Run the calibration.

Parameters:

q_length_max=0.5 (float) [us] maximum qubit pulse length.
cycles=[] (list) extra cycles in Rabi. Cycle 0 (one pi pulse) will always be included.
tol=0.5 (float) the threshold on fitting R-squared to accept the result.

Return:

var (dict|bool) self.var if succeeded. False if failed.
fig generated plot

🟢PiPulseFreq

a = quick.auto.PiPulseFreq(**kwargs)

Determine the qubit pulse frequency from Rabi, sweeping pi pulse frequency and find symmetry center.

- PiPulseFreq.calibrate

var, fig = a.calibrate(cycles=[], **kwargs)

Run the calibration.

Parameters:

cycles=[] (list) extra cycles in Rabi. Cycle 0 (one pi pulse) will always be included.

Return:

var (dict|bool) self.var if succeeded. False if failed.
fig generated plot

🟢ReadoutFreq

a = quick.auto.ReadoutFreq(**kwargs)

Determine the readout frequency from DispersiveSpectroscopy, maximizing the S21 separation.

- ReadoutFreq.calibrate

var, fig = a.calibrate(r=2, **kwargs)

Run the calibration.

Parameters:

r=2 (float) [MHz] single-side frequency range, centered by current r_freq.

Return:

var (dict|bool) self.var if succeeded. False if failed.
fig generated plot

🟢ReadoutState

a = quick.auto.ReadoutState(**kwargs)

Calibrate r_phase and r_threshold for state distinguish.

- ReadoutState.calibrate

var, fig = a.calibrate(tol=0.1, **kwargs)

Run the calibration.

Parameters:

tol=0.1 (float) tolerance of visibility, below which the result will be rejected.

Return:

var (dict|bool) self.var if succeeded. False if failed.
fig generated plot

🟢Ramsey

a = quick.auto.Ramsey(**kwargs)

Fine tune the qubit frequency by T2Ramsey.

- Ramsey.calibrate

var, fig = a.calibrate(fringe_freq=10, **kwargs)

Run the calibration.

Parameters:

fringe_freq=100 (float) [MHz] fringe frequency used in T2Ramsey

Return:

var (dict|bool) self.var if succeeded. False if failed.
fig generated plot

🟢Readout

a = quick.auto.Readout(**kwargs)

Use Nelder-Mead to optimize r_power and r_length

- Readout.calibrate

var, fig = a.calibrate()

Run the calibration.

Return:

var (dict|bool) self.var if succeeded. False if failed.
fig generated plot

🟢Relax

a = quick.auto.Relax(**kwargs)

Estimate qubit relax time by T1. The scan will go to 0.8 * r_relax. r_relax will be set as 5 times of measured T1.

- Relax.calibrate

var, fig = a.calibrate(**kwargs)

Run the calibration.

Return:

var (dict|bool) self.var if succeeded. False if failed.
fig generated plot

🟢run

res = quick.auto.run(path, soccfg=None, soc=None, data_path=None)

Run an auto task for one step. To run the auto task till end, put this in a while loop.

Parameters:

path (string) path to the auto task config file. The fill WILL be modified. See tutorial for details.
soccfg=None QICK board connection config object. If None, the last connection will be used.
soc=None QICK board connection socket object. If None, the last connection will be used.
data_path=None (string) the data directory path. If None, data will not be saved.

Returns:

res (bool) False for task completion, True for task incompletion.

Examples:

To run the auto task till end:

while quick.auto.run("task.yml"):
    pass
    # clear_output() # clear output in Jupyter to avoid super long output
    # plt.show() # plot the figure from the auto steps.