pygsti.extras.rpe

Robubst Phase Estimation Sub-package

Submodules

Package Contents

Classes

RPEconfig

Encapsulates a collection of settings for an RPE run. Provides full specifications,

Functions

create_parameterized_rpe_model(alpha_true, ...[, ...])

Make a model for simulating RPE, paramaterized by rotation angles. Note

create_rpe_angle_circuit_lists(k_list, angle_name, ...)

Make cosine and sine circuit lists. These operation sequences are used to estimate the angle specified

create_rpe_angle_circuits_dict(log2k_max_or_k_list, ...)

Generates a dictionary that contains operation sequences for all RPE cosine and

create_rpe_dataset(model_or_dataset, string_list_d, ...)

Generate a fake RPE DataSet using the probabilities obtained from a model.

extract_rotation_hat(xhat, yhat, k, nx, ny[, ...])

For a single germ generation (k value), estimate the angle of rotation

estimate_angles(dataset, angle_sin_strs, angle_cos_strs)

For a dataset containing sin and cos strings to estimate either alpha,

estimate_thetas(dataset, angle_sin_strs, ...[, ...])

For a dataset containing sin and cos strings to estimate theta,

extract_alpha(model, rpeconfig_inst)

For a given model, obtain the angle of rotation about the "fixed axis"

extract_epsilon(model, rpeconfig_inst)

For a given model, obtain the angle of rotation about the "loose axis"

extract_theta(model, rpeconfig_inst)

For a given model, obtain the angle between the estimated "loose axis" and

consistency_check(angle_k, angle_final, k)

Check internal consistency

analyze_rpe_data(input_dataset, true_or_target_model, ...)

Compute angle estimates and compare to true or target values for alpha, epsilon,
class pygsti.extras.rpe.RPEconfig(input_dict)

Encapsulates a collection of settings for an RPE run. Provides full specifications, including target gates, SPAM, sine and cosine strings for alpha, epsilon, and theta.

pygsti.extras.rpe.create_parameterized_rpe_model(alpha_true, epsilon_true, aux_rot, spam_depol, gate_depol=None, with_id=True, rpeconfig_inst=None)

Make a model for simulating RPE, paramaterized by rotation angles. Note that the output model also has thetaTrue, alpha_true, and epsilon_true added attributes.

Parameters

alpha_truefloat

Angle of rotation about “fixed axis”

epsilon_truefloat

Angle of rotation about “loose axis”

aux_rotfloat

Angle of rotation about the axis perpendicular to fixed and loose axes, that, by similarity transformation, changes loose axis.

spam_depolfloat

Amount to depolarize SPAM by.

gate_depolfloat, optional

Amount to depolarize gates by (defaults to None).

with_idbool, optional

Do we include (perfect) identity or no identity? (Defaults to False; should be False for RPE, True for GST)

rpeconfig_instRPEconfig object

Declares which model configuration RPE should be trying to fit; determines particular functions and values to be used.

Returns

Model

The desired model for RPE; model also has attributes thetaTrue, alpha_true, and epsilon_true, automatically extracted.

pygsti.extras.rpe.create_rpe_angle_circuit_lists(k_list, angle_name, rpeconfig_inst)

Make cosine and sine circuit lists. These operation sequences are used to estimate the angle specified by angle_name (‘alpha’, ‘epsilon’, or ‘theta’)

Parameters

k_listlist of ints

The list of “germ powers” to be used. Typically successive powers of two; e.g. [1,2,4,8,16].

angle_namestring

The angle to be deduced from these operation sequences. (Choices are ‘alpha’, ‘epsilon’, or ‘theta’)

rpeconfig_instRPEconfig object

Declares which model configuration RPE should be trying to fit; determines particular functions and values to be used.

Returns

cosStrListlist of Circuits

The list of “cosine strings” to be used for alpha estimation.

sinStrListlist of Circuits

The list of “sine strings” to be used for alpha estimation.

pygsti.extras.rpe.create_rpe_angle_circuits_dict(log2k_max_or_k_list, rpeconfig_inst)

Generates a dictionary that contains operation sequences for all RPE cosine and sine experiments for all three angles.

Parameters

log2k_max_or_k_listint or list

int - log2(Maximum number of times to repeat an RPE germ) list - List of maximum number of times to repeat an RPE germ

rpeconfig_instRPEconfig object

Declares which model configuration RPE should be trying to fit; determines particular functions and values to be used.

Returns

totalStrListDdict

A dictionary containing all operation sequences for all sine and cosine experiments for alpha, epsilon, and theta. The keys of the returned dictionary are:

  • ‘alpha’,’cos’ : List of operation sequences for cosine experiments used to determine alpha.

  • ‘alpha’,’sin’ : List of operation sequences for sine experiments used to determine alpha.

  • ‘epsilon’,’cos’List of operation sequences for cosine experiments used to

    determine epsilon.

  • ‘epsilon’,’sin’ : List of operation sequences for sine experiments used to determine epsilon.

  • ‘theta’,’cos’ : List of operation sequences for cosine experiments used to determine theta.

  • ‘theta’,’sin’ : List of operation sequences for sine experiments used to determine theta.

  • ‘totalStrList’ : All above operation sequences combined into one list; duplicates removed.

pygsti.extras.rpe.create_rpe_dataset(model_or_dataset, string_list_d, n_samples, sample_error='binomial', seed=None)

Generate a fake RPE DataSet using the probabilities obtained from a model. Is a thin wrapper for pygsti.data.simulate_data, changing default behavior of sample_error, and taking a dictionary of operation sequences as input.

Parameters

model_or_datasetModel or DataSet object

If a Model, the model whose probabilities generate the data. If a DataSet, the data set whose frequencies generate the data.

string_list_dDictionary of list of (tuples or Circuits)

Each tuple or Circuit contains operation labels and specifies a gate sequence whose counts are included in the returned DataSet. The dictionary must have the key ‘totalStrList’; easiest if this dictionary is generated by make_rpe_string_list_d.

n_samplesint or list of ints or None

The simulated number of samples for each operation sequence. This only has effect when sample_error == “binomial” or “multinomial”. If an integer, all operation sequences have this number of total samples. If a list, integer elements specify the number of samples for the corresponding operation sequence. If None, then model_or_dataset must be a DataSet, and total counts are taken from it (on a per-circuit basis).

sample_errorstring, optional

What type of sample error is included in the counts. Can be:

  • “none” - no sample error: counts are floating point numbers such that the exact probabilty can be found by the ratio of count / total.

  • “round” - same as “none”, except counts are rounded to the nearest integer.

  • “binomial” - the number of counts is taken from a binomial distribution. Distribution has parameters p = probability of the operation sequence and n = number of samples. This can only be used when there are exactly two outcome labels in model_or_dataset.

  • “multinomial” - counts are taken from a multinomial distribution. Distribution has parameters p_k = probability of the operation sequence using the k-th outcome label and n = number of samples. This should not be used for RPE.

seedint, optional

If not None, a seed for numpy’s random number generator, which is used to sample from the binomial or multinomial distribution.

Returns

DataSet

A static data set filled with counts for the specified operation sequences.

pygsti.extras.rpe.extract_rotation_hat(xhat, yhat, k, nx, ny, angle_name='epsilon', previous_angle=None, rpeconfig_inst=None)

For a single germ generation (k value), estimate the angle of rotation for either alpha, epsilon, or Phi. (Warning: Do not use for theta estimate without further processing!)

Parameters

xhatfloat

The number of 0 counts for the sin string being used.

yhatfloat

The number of 0 counts for the cos string being used.

kfloat

The generation of experiments that xhat and yhat come from.

nxfloat

The number of sin string clicks.

nyfloat

The number cos string clicks.

angle_name{ “alpha”, “epsilon”, “Phi” }, optional

The angle to be extracted

previous_anglefloat, optional

Angle estimate from previous generation; used to refine this generation’s estimate. Default is None (for estimation with no previous genereation’s data)

rpeconfig_instDeclares which model configuration RPE should be trying to fit;

determines particular functions and values to be used.

Returns

alpha_jfloat

The current angle estimate.

pygsti.extras.rpe.estimate_angles(dataset, angle_sin_strs, angle_cos_strs, angle_name='epsilon', length_list=None, rpeconfig_inst=None)

For a dataset containing sin and cos strings to estimate either alpha, epsilon, or Phi return a list of alpha, epsilon, or Phi estimates (one for each generation). Note: this assumes the dataset contains ‘0’ and ‘1’ SPAM labels.

Parameters

datasetDataSet

The dataset from which the angle estimates will be extracted.

angle_sin_strslist of Circuits

The list of sin strs that the estimator will use.

angle_cos_strslist of Circuits

The list of cos strs that the estimator will use.

angle_name{ “alpha”, “epsilon”, “Phi” }, optional

The angle to be extracted

length_listThe list of sequence lengths. Default is None;

If None is specified, then length_list becomes [1,2,4,…,2**(len(angle_sin_strs)-1)]

rpeconfig_instRPEconfig object

Declares which model configuration RPE should be trying to fit; determines particular functions and values to be used.

Returns

angleHatListlist of floats

A list of angle estimates, ordered by generation (k).

pygsti.extras.rpe.estimate_thetas(dataset, angle_sin_strs, angle_cos_strs, epsilon_list, return_phi_fun_list=False, rpeconfig_inst=None)

For a dataset containing sin and cos strings to estimate theta, along with already-made estimates of epsilon, return a list of theta (one for each generation).

Parameters

datasetDataSet

The dataset from which the theta estimates will be extracted.

angle_sin_strslist of Circuits

The list of sin strs that the estimator will use.

angle_cos_strslist of Circuits

The list of cos strs that the estimator will use.

epsilon_listlist of floats

List of epsilon estimates.

return_phi_fun_listbool, optional

Set to True to obtain measure of how well Eq. III.7 is satisfied. Default is False.

rpeconfig_instRPEconfig object

Declares which model configuration RPE should be trying to fit; determines particular functions and values to be used.

Returns

thetaHatListlist of floats

A list of theta estimates, ordered by generation (k).

PhiFunListlist of floats

A list of _sin_phi2 vals at optimal theta values. If not close to 0, constraints unsatisfiable. Only returned if return_phi_fun_list is set to True.

pygsti.extras.rpe.extract_alpha(model, rpeconfig_inst)

For a given model, obtain the angle of rotation about the “fixed axis”

WARNING: This is a gauge-covariant parameter! Gauge must be fixed prior to estimating.

Parameters

modelModel

The model whose angle of rotation about the fixed axis is to be calculated.

rpeconfig_instRPEconfig object

Declares which model configuration RPE should be trying to fit; determines particular functions and values to be used.

Returns

alphaValfloat

The value of alpha for the input model.

pygsti.extras.rpe.extract_epsilon(model, rpeconfig_inst)

For a given model, obtain the angle of rotation about the “loose axis”

WARNING: This is a gauge-covariant parameter! Gauge must be fixed prior to estimating.

Parameters

modelModel

The model whose angle of rotation about the “loose axis” is to be calculated.

rpeconfig_instRPEconfig object

Declares which model configuration RPE should be trying to fit; determines particular functions and values to be used.

Returns

epsilonValfloat

The value of epsilon for the input model.

pygsti.extras.rpe.extract_theta(model, rpeconfig_inst)

For a given model, obtain the angle between the estimated “loose axis” and the target “loose axis”.

WARNING: This is a gauge-covariant parameter! (I think!) Gauge must be fixed prior to estimating.

Parameters

modelModel

The model whose loose axis misalignment is to be calculated.

rpeconfig_instRPEconfig object

Declares which model configuration RPE should be trying to fit; determines particular functions and values to be used.

Returns

thetaValfloat

The value of theta for the input model.

pygsti.extras.rpe.consistency_check(angle_k, angle_final, k)

Check internal consistency

pygsti.extras.rpe.analyze_rpe_data(input_dataset, true_or_target_model, string_list_d, rpeconfig_inst, do_consistency_check=False, k_list=None)

Compute angle estimates and compare to true or target values for alpha, epsilon, and theta. (“True” will typically be used for simulated data, when the true angle values are known a priori; “target” will typically be used for experimental data, where we do not know the true angle values, and can only compare to our desired angles.)

Parameters

input_datasetDataSet

The dataset containing the RPE experiments.

true_or_target_modelModel

The model used to generate the RPE data OR the target model.

string_list_ddict

The dictionary of operation sequence lists used for the RPE experiments. This should be generated via make_rpe_string_list_d.

rpeconfig_instRPEconfig object

Declares which model configuration RPE should be trying to fit; determines particular functions and values to be used.

Returns

resultsDdict

A dictionary of the results. The keys of the dictionary are:

  • ‘alphaHatList’ : List (ordered by k) of alpha estimates.

  • ‘epsilonHatList’ : List (ordered by k) of epsilon estimates.

  • ‘thetaHatList’ : List (ordered by k) of theta estimates.

  • ‘alphaErrorList’ : List (ordered by k) of difference between true alpha and RPE estimate of alpha.

  • ‘epsilonErrorList’ : List (ordered by k) of difference between true epsilon and RPE estimate of epsilon.

  • ‘thetaErrorList’ : List (ordered by k) of difference between true theta and RPE estimate of theta.

  • ‘PhiFunErrorList’ : List (ordered by k) of _sin_phi2 values.