analysis

tergite_autocalibration.lib.nodes.qubit_control.spectroscopy.analysis

Module containing classes that model, fit and plot data from a qubit (two tone) spectroscopy experiment.

Classes:

Name	Description
QubitSpectroscopyAnalysis	Analysis that fits a Lorentzian function to qubit spectroscopy data.
QubitSpectroscopyMaxThresholdQubitAnalysis	Analysis that finds the maximum value in qubit spectroscopy data.
QubitSpectroscopyMultidimAnalysis	Analysis that fits a Lorentzian function to qubit spectroscopy data.

QubitSpectroscopyAnalysis

QubitSpectroscopyAnalysis(name, redis_fields)

Bases: BaseQubitAnalysis

Analysis that fits a Lorentzian function to qubit spectroscopy data. The resulting fit can be analyzed to determine if a peak was found or not.

Methods:

Name	Description
plot	Plot the fitted values from the analysis
process_qubit	Setup the qubit data and analyze it.
rotate_to_probability_axis	Rotates the S21 IQ points to the real - normalized axis

plot

plot(primary_axis)

Plot the fitted values from the analysis Args: primary_axis: The axis object from matplotlib to be plotted Returns: None, will just plot the fitted values

process_qubit

process_qubit(dataset, qubit_element) -> QOI

Setup the qubit data and analyze it. Args: dataset: xarray dataset with the qubit data qubit_element: name of the qubit element Returns: QOI: Quantity of interest as QOI wrapped object

rotate_to_probability_axis

rotate_to_probability_axis(complex_measurement_data)

Rotates the S21 IQ points to the real - normalized axis that describes the |0> - |1> axis. !!! It Assumes that complex_measurement_data[-2] corresponds to the |0> and complex_measurement_data[-1] corresponds to the |1>

QubitSpectroscopyMaxThresholdQubitAnalysis

QubitSpectroscopyMaxThresholdQubitAnalysis(name, redis_fields, current)

Bases: BaseQubitAnalysis

Analysis that finds the maximum value in qubit spectroscopy data.

Methods:

Name	Description
plot	Plot the fitted values from the analysis
process_qubit	Setup the qubit data and analyze it.
rotate_to_probability_axis	Rotates the S21 IQ points to the real - normalized axis

plot

plot(primary_axis)

Plot the fitted values from the analysis Args: primary_axis: The axis object from matplotlib to be plotted Returns: None, will just plot the fitted values

process_qubit

process_qubit(dataset, qubit_element) -> QOI

Setup the qubit data and analyze it. Args: dataset: xarray dataset with the qubit data qubit_element: name of the qubit element Returns: QOI: Quantity of interest as QOI wrapped object

rotate_to_probability_axis

rotate_to_probability_axis(complex_measurement_data)

Rotates the S21 IQ points to the real - normalized axis that describes the |0> - |1> axis. !!! It Assumes that complex_measurement_data[-2] corresponds to the |0> and complex_measurement_data[-1] corresponds to the |1>

QubitSpectroscopyMultidimAnalysis

QubitSpectroscopyMultidimAnalysis(name, redis_fields)

Bases: BaseQubitAnalysis

Analysis that fits a Lorentzian function to qubit spectroscopy data. The resulting fit can be analyzed to determine if a peak was found or not.

Methods:

Name	Description
plot	Plot the fitted values from the analysis
process_qubit	Setup the qubit data and analyze it.
rotate_to_probability_axis	Rotates the S21 IQ points to the real - normalized axis

plot

plot(primary_axis)

Plot the fitted values from the analysis Args: primary_axis: The axis object from matplotlib to be plotted Returns: None, will just plot the fitted values

process_qubit

process_qubit(dataset, qubit_element) -> QOI

Setup the qubit data and analyze it. Args: dataset: xarray dataset with the qubit data qubit_element: name of the qubit element Returns: QOI: Quantity of interest as QOI wrapped object

rotate_to_probability_axis

rotate_to_probability_axis(complex_measurement_data)

Rotates the S21 IQ points to the real - normalized axis that describes the |0> - |1> axis. !!! It Assumes that complex_measurement_data[-2] corresponds to the |0> and complex_measurement_data[-1] corresponds to the |1>