qiskit.ignis.characterization.BaseCoherenceFitter

class BaseCoherenceFitter(description, backend_result, xdata, qubits, fit_fun, fit_p0, fit_bounds, circuit_names, series=None, expected_state='0', time_index=0, time_unit='micro-seconds')

Base class for fitters of characteristic times

Parâmetros

• description (str) – description of the fitter’s purpose, e.g. ‘T1’.

• backend_result (Union[Result, List[Result]]) – result of execution on the backend.

• xdata (Union[List[float], array]) – delay times of the circuits.

• qubits (List[int]) – the qubits to be characterized.

• fit_fun (Callable[…, float]) – equivalent to parameter f of scipy.curve_fit.

• fit_p0 (List[float]) – equivalent to parameter p0 of scipy.curve_fit.

• fit_bounds (Tuple[List[float], List[float]]) – equivalent to parameter bounds of scipy.curve_fit.

• circuit_names (List[str]) – names of the circuits, should be the same length as xdata. Full circuit name will be these plus the series name.

• series (Optional[List[str]]) – list of circuit name tags

• expected_state (str) – is the circuit supposed to end up in ‘0’ or ‘1’?

• time_index (int) – among parameters of fit_fun, which one is the characteristic time.

• time_unit (str) – unit of delay times in xdata.

__init__(description, backend_result, xdata, qubits, fit_fun, fit_p0, fit_bounds, circuit_names, series=None, expected_state='0', time_index=0, time_unit='micro-seconds')

Initialize self. See help(type(self)) for accurate signature.

Methods

__init__(description, backend_result, xdata, …)	Initialize self.
add_data(results[, recalc, refit])	Add new execution results to previous execution results
fit_data([qid, p0, bounds, series])	Fit the curve.
plot(qind, series[, ax, show_plot])	Plot coherence data.
time([qid, series])	Return the characteristic time for the given qubit and series
time_err([qid, series])	Return the error of characteristic time for the given qubit and series

Attributes

backend_result	Return the execution results
description	Return the fitter’s purpose, e.g.
fit_fun	Return the function used in the fit, e.g.
measured_qubits	Return the indices of the qubits to be characterized
params	Return the fit function parameters that were calculated by curve_fit
params_err	Return the error of the fit function parameters
series	Return the list of series for the data
xdata	Return the data points on the x-axis, the independenet parameter which is fit against
ydata	Return the data points on the y-axis

add_data(results, recalc=True, refit=True)

Add new execution results to previous execution results

Parâmetros

• results (Union[Result, List[Result]]) – new execution results

• recalc (bool) – whether tp recalculate the data

• refit (bool) – whether to refit the data

property backend_result

Return the execution results

Tipo de retorno

Union[Result, List[Result]]

property description

Return the fitter’s purpose, e.g. ‘T1’

Tipo de retorno

str

fit_data(qid=- 1, p0=None, bounds=None, series=None)

Fit the curve.

Compute self._params and self._params_err

Parâmetros

• qid (int) – qubit for fitting. If -1 fit for all the qubits

• p0 (Optional[List[float]]) – initial guess, equivalent to p0 in scipy.optimize

• bounds (Optional[Tuple[List[float], List[float]]]) – bounds, equivalent to bounds in scipy.optimize

• series (Optional[str]) – series to fit (if None fit all)

property fit_fun

Return the function used in the fit, e.g. BaseFitter._exp_fit_fun

Tipo de retorno

Callable

property measured_qubits

Return the indices of the qubits to be characterized

Tipo de retorno

List[int]

property params

Return the fit function parameters that were calculated by curve_fit

Tipo de retorno

List[float]

property params_err

Return the error of the fit function parameters

Tipo de retorno

List[float]

plot(qind, series, ax=None, show_plot=True)

Plot coherence data.

Parâmetros

• qind (int) – qubit index to plot

• series (str) – which series to plot (if list then plot multiple)

• ax (Optional[Any]) – plot axes

• show_plot (bool) – whether to call plt.show()

Retorna

The axes object

Tipo de retorno

Axes

Levanta

ImportError – if matplotlib is not installed

property series

Return the list of series for the data

Tipo de retorno

Optional[List[str]]

time(qid=- 1, series='0')

Return the characteristic time for the given qubit and series

Parâmetros

• qid (int) – the qubit index (or all qubits if -1)

• series (str) – the series to get

Tipo de retorno

Union[float, List[float]]

Retorna

The characteristic time of the qubit, or all qubits

time_err(qid=- 1, series='0')

Return the error of characteristic time for the given qubit and series

Parâmetros

• qid (int) – the qubit index (or all qubits if -1)

• series (str) – the series to get

Tipo de retorno

Union[float, List[float]]

Retorna

The error of the characteristic time of the qubit, or all qubits

property xdata

Return the data points on the x-axis, the independenet parameter which is fit against

Tipo de retorno

Union[List[float], array]

property ydata

Return the data points on the y-axis

The data points are returning in the form of a list of dictionaries:

• ydata[i][‘mean’] is a list, where item

  no. j is the probability of success of qubit i for a circuit that lasts xdata[j].

• ydata[i][‘std’] is a list, where ydata[‘std’][j] is the

  standard deviation of the success of qubit i.

Tipo de retorno

List[Dict]