T1Fitter¶

class T1Fitter(backend_result, xdata, qubits, fit_p0, fit_bounds, time_unit='micro-seconds')[source]¶

Estimate T₁, based on experiments outcomes,

The experiments were created by t1_circuits, and executed on the device.

The probabilities of measuring 1 is assumed to be of the form

\[f(t) = A\mathrm{e}^{-t/T_1}+B,\]

for unknown parameters A, B, and T₁.

Parameters

backend_result (Result) – result of execution of t1_circuits on the backend.
xdata (Union[List[float], array]) – delay times of the T₁ circuits.
qubits (List[int]) – indices of the qubits whose T₁‘s are to be measured.
fit_p0 (List[float]) – initial values to the fit parameters, where the order is \((A, T_1, B)\).
fit_bounds (Tuple[List[float], List[float]]) – bounds on the parameters to fit. The first tuple is the lower bounds, in the order \((A, T_1, B)\). The second tuple is the upper bounds.
time_unit (str) – unit of delay times in xdata.

Attributes

`T1Fitter.backend_result`	Return the execution results
`T1Fitter.description`	Return the fitter’s purpose, e.g.
`T1Fitter.fit_fun`	Return the function used in the fit, e.g.
`T1Fitter.measured_qubits`	Return the indices of the qubits to be characterized
`T1Fitter.params`	Return the fit function parameters that were calculated by curve_fit
`T1Fitter.params_err`	Return the error of the fit function parameters
`T1Fitter.series`	Return the list of series for the data
`T1Fitter.xdata`	Return the data points on the x-axis, the independenet parameter which is fit against
`T1Fitter.ydata`	Return the data points on the y-axis

Methods

`T1Fitter.add_data`(results[, recalc, refit])	Add new execution results to previous execution results
`T1Fitter.fit_data`([qid, p0, bounds, series])	Fit the curve.
`T1Fitter.plot`(qind[, series, ax, show_plot])	Plot coherence data.
`T1Fitter.time`([qid, series])	Return the characteristic time for the given qubit and series
`T1Fitter.time_err`([qid, series])	Return the error of characteristic time for the given qubit and series