qiskit.ignis.verification.InterleavedRBFitter
class InterleavedRBFitter(original_result, interleaved_result, cliff_lengths, rb_pattern=None)
Class for fitters for interleaved RB, derived from RBFitterBase class.
Contains two RBFitter objects: the original RBFitter and the interleaved RBFitter.
Parameters
- original_result (list) – list of results of the original RB sequence (qiskit.Result).
- interleaved_result (list) – list of results of the interleaved RB sequence (qiskit.Result).
- cliff_lengths (list) – the Clifford lengths, 2D list i x j where i is the number of patterns, j is the number of cliffords lengths.
- rb_pattern (list) – the pattern for the RB sequences.
__init__
__init__(original_result, interleaved_result, cliff_lengths, rb_pattern=None)
Parameters
- original_result (list) – list of results of the original RB sequence (qiskit.Result).
- interleaved_result (list) – list of results of the interleaved RB sequence (qiskit.Result).
- cliff_lengths (list) – the Clifford lengths, 2D list i x j where i is the number of patterns, j is the number of cliffords lengths.
- rb_pattern (list) – the pattern for the RB sequences.
Methods
__init__(original_result, …[, rb_pattern]) | param original_resultlist of results of the |
add_data(new_original_result, …[, rerun_fit]) | Add a new result. |
calc_data() | Retrieve probabilities of success from execution results. |
calc_statistics() | Extract averages and std dev. |
fit_data() | Fit the interleaved RB results. |
fit_data_pattern(patt_ind, fit_guess[, …]) | Fit the RB results of a particular pattern to an exponential curve. |
plot_rb_data([pattern_index, ax, add_label, …]) | Plot interleaved randomized benchmarking data of a single pattern. |
Attributes
cliff_lengths | Return clifford lengths. |
fit | Return fit as a 2 element list. |
fit_int | Return interleaved fit parameters. |
raw_data | Return raw_data as a 2 element list. |
rb_fit_fun | Return the fit function rb_fit_fun. |
rbfit_int | Return the interleaved RB fitter. |
rbfit_std | Return the original RB fitter. |
results | Return all the results as a 2 element list. |
seeds | Return the number of loaded seeds as a 2 element list. |
ydata | Return ydata (means and std devs) as a 2 element list. |
add_data
add_data(new_original_result, new_interleaved_result, rerun_fit=True)
Add a new result.
Parameters
- new_original_result (list) – list of RB results of the original circuits.
- new_interleaved_result (list) – list of RB results of the interleaved circuits.
- rerun_fit (bool) – re-calculate the means and fit the result.
Additional information:
Assumes that the executed ‘result’ is the output of circuits generated by randomized_benchmarking_seq.
calc_data
calc_data()
Retrieve probabilities of success from execution results.
Outputs results into an internal variables: _raw_original_data and _raw_interleaved_data
calc_statistics
calc_statistics()
Extract averages and std dev.
Output [ydata_original, ydata_interleaved]
cliff_lengths
Return clifford lengths.
fit
Return fit as a 2 element list.
fit_data
fit_data()
Fit the interleaved RB results. Fit each of the patterns.
According to the paper: “Efficient measurement of quantum gate error by interleaved randomized benchmarking” (arXiv:1203.4550) - Equations (4) and (5).
Puts the results into a list of fit dictionaries: where each dictionary corresponds to a pattern and has fields:
- ‘epc_est’ - the estimated error per the interleaved Clifford.
- ‘epc_est_error’ - the estimated error derived from the params_err.
- ‘systematic_err’ - systematic error bound of epc_est.
- ‘systematic_err_L’ = epc_est - systematic_err (left error bound).
- ‘systematic_err_R’ = epc_est + systematic_err (right error bound).
fit_data_pattern
fit_data_pattern(patt_ind, fit_guess, fit_index=0)
Fit the RB results of a particular pattern to an exponential curve.
Parameters
- patt_ind (int) – index of the data to fit.
- fit_guess (list) – guess values for the fit.
- fit_index (int) – 0 fit the standard data, 1 fit the interleaved data.
fit_int
Return interleaved fit parameters.
plot_rb_data
plot_rb_data(pattern_index=0, ax=None, add_label=True, show_plt=True)
Plot interleaved randomized benchmarking data of a single pattern.
Parameters
- pattern_index (int) – which RB pattern to plot.
- ax (Axes) – plot axis (if passed in).
- add_label (bool) – Add an EPC label.
- show_plt (bool) – display the plot.
Raises
ImportError – if matplotlib is not installed.
raw_data
Return raw_data as a 2 element list.
rb_fit_fun
Return the fit function rb_fit_fun.
rbfit_int
Return the interleaved RB fitter.
rbfit_std
Return the original RB fitter.
results
Return all the results as a 2 element list.
seeds
Return the number of loaded seeds as a 2 element list.
ydata
Return ydata (means and std devs) as a 2 element list.