CNOTDihedralRBFitter
class CNOTDihedralRBFitter(cnotdihedral_Z_result, cnotdihedral_X_result, elmnts_lengths, rb_pattern=None)
Bases: qiskit.ignis.verification.randomized_benchmarking.fitters.RBFitterBase
Class for fitters for non-Clifford CNOT-Dihedral RB.
Derived from RBFitterBase class. Contains two RBFitter objects.
Parameters
- cnotdihedral_Z_result (qiskit.Result) – list of results of the RB sequence that measures the ground state.
- cnotdihedral_X_result (qiskit.Result) – list of results of the RB sequence that measures the state.
- elmnts_lengths (list) – the group elements lengths, 2D list i x j where i is the number of patterns, j is the number of elements lengths.
- rb_pattern (list) – the pattern for the RB sequences.
Methods
add_data
CNOTDihedralRBFitter.add_data(new_cnotdihedral_Z_result, new_cnotdihedral_X_result, rerun_fit=True)
Add a new result.
Parameters
- new_cnotdihedral_Z_result (list) – list of rb results of the cnot-dihedral Z circuits.
- new_cnotdihedral_X_result (list) – list of rb results of the cnot-dihedral X 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
CNOTDihedralRBFitter.calc_data()
Retrieve probabilities of success from execution results. Outputs results into an internal variable: _raw_data .
calc_statistics
CNOTDihedralRBFitter.calc_statistics()
Extract averages and std dev. Outputs results into an internal variable: _ydata .
fit_data
CNOTDihedralRBFitter.fit_data()
Fit the non-Clifford cnot-dihedral RB results.
Fit each of the patterns. According to the paper:
Scalable randomized benchmarking of non-Clifford gates
Returns
A list of dictionaries where each dictionary corresponds to a pattern and has fields:
alpha- alpha parameter of the non-Clifford cnot-dihedral RB.'alpha_err- the error of the alpha parameter of the non-Clifford cnot-dihedral RB.epg_est- the estimated error per a CNOT-dihedral element.epg_est_error- the estimated error derived from the params_err.
Return type
list
fit_data_pattern
CNOTDihedralRBFitter.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 pattern to fit.
- fit_guess (list) – guess values for the fit.
- fit_index (int) – 0 fit the standard data, 1 fit the interleaved data.
plot_rb_data
CNOTDihedralRBFitter.plot_rb_data(pattern_index=0, ax=None, add_label=True, show_plt=True)
Plot non-Clifford cnot-dihedral 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 EPG label.
- show_plt (bool) – display the plot.
Raises
ImportError – if matplotlib is not installed.
Attributes
cliff_lengths
Return group elements lengths.
fit
Return fit as a 2 element list.
fit_cnotdihedral
Return cnotdihedral fit parameters.
raw_data
Return raw_data as 2 element list.
rb_fit_fun
Return the fit function rb_fit_fun.
rbfit_X
Return the cnotdihedral X fitter.
rbfit_Z
Return the cnotdihedral Z 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.