quara.protocol.qtomography.qtomography module¶

class QTomography(experiment, set_qoperations)[source]¶

Bases: object

initialize quantum tomography class.

To inherit from this class, set the following instance variables in the constructor of the subclass.

_num_variables: sum of the number of all variables.

Parameters

experiment (Experiment) – Experiment class used in quantum tomography.
set_qoperations (SetQOperations) – SetQOperations class used in quantum tomography.

abstract calc_prob_dist(qope, schedule_index)[source]¶

calculates a probability distribution.

this function must be implemented in the subclass.

Parameters

qope (QOperation) – QOperation to calculate a probability distribution.
schedule_index (int) – schedule index.

Returns

a probability distribution.

Return type

List[np.ndarray]

Raises

NotImplementedError – this function does not be implemented in the subclass.

abstract calc_prob_dists(qope)[source]¶

calculates probability distributions.

this function must be implemented in the subclass.

Parameters: qope (QOperation) – QOperation to calculate probability distributions.
Returns: probability distributions.
Return type: List[List[np.ndarray]]
Raises: NotImplementedError – this function does not be implemented in the subclass.

abstract func_prob_dist()[source]¶

abstract func_prob_dists()[source]¶

abstract generate_dataset(data_nums)[source]¶

Run all the schedules to caluclate the probability distribution and generate random data.

this function must be implemented in the subclass.

Parameters: data_nums (List[int]) – A list of the number of data to be generated in each schedule. This parameter should be a list of non-negative integers.
Returns: Generated dataset.
Return type: List[List[np.ndarray]]
Raises: NotImplementedError – this function does not be implemented in the subclass.

abstract generate_empi_dists(qoperation, num_sum)[source]¶

Generate empirical distributions using the data generated from probability distributions of all schedules.

this function must be implemented in the subclass.

Parameters

qoperation (QOperation) – QOperation to use to generate the experience distributions.
num_sum (int) – the number of data to use to generate the experience distributions for each schedule.

Returns

A list of tuples for the number of data and experience distributions for each schedules.

Return type

List[Tuple[int, np.ndarray]]

Raises

NotImplementedError – this function does not be implemented in the subclass.

abstract is_valid_experiment()[source]¶

returns whether the experiment is valid.

this function must be implemented in the subclass.

Returns: whether the experiment is valid.
Return type: bool
Raises: NotImplementedError – this function does not be implemented in the subclass.

property num_schedules: int¶

returns number of schedules.

Returns: number of schedules.
Return type: int

property num_variables: int¶

returns sum of the number of all variables.

Returns: sum of the number of all variables.
Return type: int

reset_seed(seed=None)[source]¶

reset new seed.

if seed is None, reset by seed which Experiment already has.

Parameters: seed (int, optional) – new seed, None by default.
Return type: None