quara.qcircuit.experiment module¶

class Experiment(states, povms, gates, schedules, seed=None)[source]¶

Bases: object

Class to manage experiment settings This class is not limited to tomography, but deals with general quantum circuits.

Parameters

states (List[quara.objects.state.State]) –
povms (List[quara.objects.povm.Povm]) –
gates (List[quara.objects.gate.Gate]) –
schedules (List[List[Tuple[str, int]]]) –
seed (int) –

Return type

None

calc_prob_dist(schedule_index)[source]¶

Calculate the probability distributionthe by running the specified schedule.

Parameters: schedule_index (int) – Index of the schedule
Returns: Probability distribution
Return type: np.ndarray
Raises: ValueError – If the object referenced in the schedule, such as State, POVM, Gate, or Mprocess, is None.

calc_prob_dists()[source]¶

Caluclate probability distributions for all schedules.

Returns: Probability distributions for all schedules
Return type: List[np.ndarray]

copy()[source]¶

returns copied Experiment.

Returns: copied Experiment.
Return type: Experiment

property gates: List[quara.objects.gate.Gate]¶

generate_data(schedule_index, data_num)[source]¶

Runs the specified schedule to caluclate the probability distribution and generate random data.

Parameters

schedule_index (int) – Index of the schedule.
data_num (int) – Length of the data.

Returns

Generated data.

Return type

List[int]

Raises

TypeError – [description]
ValueError – [description]
IndexError – [description]

generate_dataset(data_nums)[source]¶

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

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]]

generate_empi_dist_sequence(schedule_index, num_sums)[source]¶

Generate an empirical distribution using the data generated from the probability distribution of a specified schedule.

Uses generated data from 0-th to num_sums[index]-th to calculate empirical distributions.

Parameters

schedule_index (int) – Index of schedule.
num_sums (List[int]) – List of the number of data to caluclate the experience distribution

Returns

A list of the numbers of data and empirical distribution.

Return type

List[Tuple[int, np.ndarray]]

generate_empi_dists_sequence(list_num_sums)[source]¶

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

Parameters: list_num_sums (List[List[int]]) – A list of the number of data to use to calculate the experience distribution for each schedule.
Returns: A list of tuples for the number of data and experience distribution for each schedules.
Return type: List[List[Tuple[int, np.ndarray]]]

property povms: List[quara.objects.povm.Povm]¶

reset_seed(seed)[source]¶

reset new seed.

Parameters: seed (int) – new seed.
Return type: None

property schedules: List[List[Tuple[str, int]]]¶

property seed: int¶

property states: List[quara.objects.state.State]¶

exception QuaraScheduleItemError[source]¶

Bases: Exception

Raised when an element of the schedule is incorrect.

Parameters: Exception ([type]) – [description]

exception QuaraScheduleOrderError[source]¶

Bases: Exception

Raised when the order of the schedule is incorrect.

Parameters: Exception ([type]) – [description]