:py:mod:`pygsti.extras.rpe.rpeconstruction` =========================================== .. py:module:: pygsti.extras.rpe.rpeconstruction .. autoapi-nested-parse:: Functions for creating RPE Models and Circuit lists Module Contents --------------- Functions ~~~~~~~~~ .. autoapisummary:: pygsti.extras.rpe.rpeconstruction.create_parameterized_rpe_model pygsti.extras.rpe.rpeconstruction.create_rpe_angle_circuit_lists pygsti.extras.rpe.rpeconstruction.create_rpe_angle_circuits_dict pygsti.extras.rpe.rpeconstruction.create_rpe_dataset .. py:function:: 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_true : float Angle of rotation about "fixed axis" epsilon_true : float Angle of rotation about "loose axis" aux_rot : float Angle of rotation about the axis perpendicular to fixed and loose axes, that, by similarity transformation, changes loose axis. spam_depol : float Amount to depolarize SPAM by. gate_depol : float, optional Amount to depolarize gates by (defaults to None). with_id : bool, optional Do we include (perfect) identity or no identity? (Defaults to False; should be False for RPE, True for GST) rpeconfig_inst : RPEconfig 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. .. py:function:: 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_list : list of ints The list of "germ powers" to be used. Typically successive powers of two; e.g. [1,2,4,8,16]. angle_name : string The angle to be deduced from these operation sequences. (Choices are 'alpha', 'epsilon', or 'theta') rpeconfig_inst : RPEconfig object Declares which model configuration RPE should be trying to fit; determines particular functions and values to be used. Returns ------- cosStrList : list of Circuits The list of "cosine strings" to be used for alpha estimation. sinStrList : list of Circuits The list of "sine strings" to be used for alpha estimation. .. py:function:: 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_list : int 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_inst : RPEconfig object Declares which model configuration RPE should be trying to fit; determines particular functions and values to be used. Returns ------- totalStrListD : dict 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. .. py:function:: 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_dataset : Model 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_d : Dictionary 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_samples : int 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_error : string, 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. seed : int, 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.