# qiskit.ignis.verification.PurityRBFitter¶

class PurityRBFitter(purity_result, npurity, cliff_lengths, rb_pattern=None)[ソース]

Class for fitter for purity RB.

Derived from RBFitterBase class.

パラメータ
• purity_result (list) – list of results of the 3^n purity RB sequences per seed (qiskit.Result).

• npurity (int) – equals 3^n (where n is the dimension).

• 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__(purity_result, npurity, cliff_lengths, rb_pattern=None)[ソース]
パラメータ
• purity_result (list) – list of results of the 3^n purity RB sequences per seed (qiskit.Result).

• npurity (int) – equals 3^n (where n is the dimension).

• 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

 F234(n, a, b) Function than maps: 2^n x 3^n –> 4^n , namely: (a,b) –> c where a in 2^n, b in 3^n, c in 4^n __init__(purity_result, npurity, cliff_lengths) param purity_result list of results of the add_data(new_purity_result[, rerun_fit]) Add a new result. Creating all Z-correlators in order to compute the expectation values. Retrieve probabilities of success from execution results. Extract averages and std dev from the raw data (self._raw_data). Fit the Purity RB results to an exponential curve. 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 purity RB data of a single pattern.

Attributes

 cliff_lengths Return clifford lengths. fit Return the purity fit parameters. raw_data Return raw data. rb_fit_fun Return the fit function rb_fit_fun. rbfit_pur Return the purity RB fitter. results Return all the results. seeds Return the number of loaded seeds. ydata Return ydata (means and std devs).
static F234(n, a, b)[ソース]

Function than maps: 2^n x 3^n –> 4^n , namely: (a,b) –> c where a in 2^n, b in 3^n, c in 4^n

add_data(new_purity_result, rerun_fit=True)[ソース]

パラメータ
• new_purity_result (list) – list of RB results of the purity RB circuits.

• rerun_fit (bool) – re-calculate the means and fit the result.

Assumes that the executed 『result』 is the output of circuits generated by randomized_benchmarking_seq where is_purity = True.

add_zdict_ops()[ソース]

Creating all Z-correlators in order to compute the expectation values.

calc_data()[ソース]

Retrieve probabilities of success from execution results.

Measure the purity calculation into an internal variable _raw_data which is a 3-dimensional list, where item (i,j,k) is the purity of the set of qubits in pattern 「i」 for seed no. j and vector length self._cliff_lengths[i][k].

Assumes that the executed 『result』 is the output of circuits generated by randomized_benchmarking_seq,

calc_statistics()[ソース]

Extract averages and std dev from the raw data (self._raw_data).

Assumes that self._calc_data has been run. Output into internal _ydata variable. ydata is a list of dictionaries (length number of patterns):

Dictionary ydata[i]:

• ydata[i][『mean』] is a numpy_array of length n; entry j of this array contains the mean probability of success over seeds, for vector length self._cliff_lengths[i][j].

• ydata[i][『std』] is a numpy_array of length n; entry j of this array contains the std of the probability of success over seeds, for vector length self._cliff_lengths[i][j].

property cliff_lengths

Return clifford lengths.

property fit

Return the purity fit parameters.

fit_data()[ソース]

Fit the Purity RB results to an exponential curve.

Use the data to construct guess values for the fits.

Puts the results into a list of fit dictionaries where each dictionary corresponds to a pattern and has fields:

• params - three parameters of rb_fit_fun. The middle one is the exponent.

• err - the error limits of the parameters.

• epc - Error per Clifford.

• pepc - Purity Error per Clifford.

fit_data_pattern(patt_ind, fit_guess)[ソース]

Fit the RB results of a particular pattern to an exponential curve.

パラメータ
• patt_ind (int) – index of the subsystem to fit.

• fit_guess (list) – guess values for the fit.

Puts the results into a list of fit dictionaries where each dictionary corresponds to a pattern and has fields:

• params - three parameters of rb_fit_fun. The middle one is the exponent.

• err - the error limits of the parameters.

plot_rb_data(pattern_index=0, ax=None, add_label=True, show_plt=True)[ソース]

Plot purity RB data of a single pattern.

property raw_data

Return raw data.

property rb_fit_fun

Return the fit function rb_fit_fun.

property rbfit_pur

Return the purity RB fitter.

property results

Return all the results.

property seeds

Return the number of loaded seeds.

property ydata

Return ydata (means and std devs).