analysis
Classes:
| Name | Description |
|---|---|
BaseT2QubitAnalysis |
Base class for T2 qubit analysis. |
T2EchoNodeAnalysis |
Node analysis for T2 Echo measurements. |
T2EchoQubitAnalysis |
Class for T2 Echo qubit analysis. |
T2Model |
Generate a cosine model that can be fit to Rabi oscillation data. |
T2NodeAnalysis |
Node analysis for T2 measurements. |
T2QubitAnalysis |
Class for T2 qubit analysis. |
Functions:
| Name | Description |
|---|---|
cos_func |
Generate a cosine function with exponential decay. |
Bases: BaseQubitAnalysis, ABC
Base class for T2 qubit analysis. This class provides the structure for analyzing T2 times for a single qubit. It should be subclassed to implement specific fitting models and extraction methods.
Methods:
| Name | Description |
|---|---|
analyse_qubit |
Run the actual analysis function |
analyse_t2_times |
Perform the analysis of T2 times for the qubit. |
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 |
abstractmethod
analyse_qubit() -> QOI
Run the actual analysis function
Returns:
| Type | Description |
|---|---|
QOI
|
The quantity of interest as QOI wrapped object |
Perform the analysis of T2 times for the qubit. This method identifies the coordinates for delays and repetitions, extracts the magnitudes for each repetition, fits the model, and calculates the average T2 time and its error.
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(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
Bases: BaseAllQubitsAnalysis
Node analysis for T2 Echo measurements. This class performs T2 Echo analysis for multiple qubits and uses the T2EchoQubitAnalysis class for individual qubit analysis.
Methods:
| Name | Description |
|---|---|
analyze_node |
Analyze the node and save the results to redis. |
open_dataset |
Open the dataset for the analysis. |
Analyze the node and save the results to redis. Args: data_path: Path to the dataset index: Index of the dataset to be analyzed
Returns:
| Name | Type | Description |
|---|---|---|
analysis_results |
QOI
|
Dictionary with the analysis results for each qubit |
Bases: BaseT2QubitAnalysis
Class for T2 Echo qubit analysis. This class implements the analysis of T2 Echo times for a single qubit using an exponential decay model. It fits the model to the data and extracts the T2 Echo time.
Methods:
| Name | Description |
|---|---|
analyse_t2_times |
Perform the analysis of T2 times for the qubit. |
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 |
Perform the analysis of T2 times for the qubit. This method identifies the coordinates for delays and repetitions, extracts the magnitudes for each repetition, fits the model, and calculates the average T2 time and its error.
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(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
Bases: Model
Generate a cosine model that can be fit to Rabi oscillation data.
Bases: BaseAllQubitsAnalysis
Node analysis for T2 measurements. This class performs T2 analysis for multiple qubits and uses the T2QubitAnalysis class for individual qubit analysis.
Methods:
| Name | Description |
|---|---|
analyze_node |
Analyze the node and save the results to redis. |
open_dataset |
Open the dataset for the analysis. |
Analyze the node and save the results to redis. Args: data_path: Path to the dataset index: Index of the dataset to be analyzed
Returns:
| Name | Type | Description |
|---|---|---|
analysis_results |
QOI
|
Dictionary with the analysis results for each qubit |
Bases: BaseT2QubitAnalysis
Class for T2 qubit analysis. This class implements the analysis of T2 times for a single qubit using a cosine model with exponential decay. It fits the model to the data and extracts the T2 time.
Methods:
| Name | Description |
|---|---|
analyse_t2_times |
Perform the analysis of T2 times for the qubit. |
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 |
Perform the analysis of T2 times for the qubit. This method identifies the coordinates for delays and repetitions, extracts the magnitudes for each repetition, fits the model, and calculates the average T2 time and its error.
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(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
cos_func(x: float, frequency: float, amplitude: float, offset: float, x0: float, phase: float = 0) -> float
Generate a cosine function with exponential decay. Args: x (float): The input value. frequency (float): The frequency of the cosine wave. amplitude (float): The amplitude of the cosine wave. offset (float): The offset to be added to the cosine wave. x0 (float): The decay constant for the exponential decay. phase (float, optional): The phase shift of the cosine wave. Defaults to 0. Returns: float: The value of the cosine function with exponential decay at x.