qiskit.ignis.measurement.DiscriminationFilter

class DiscriminationFilter(discriminator, base=None)

Implements a filter based on a discriminator that takes level 1 data to level 2 data.

Usage:

my_filter = DiscriminationFilter(my_discriminator) new_result = filter.apply(level_1_data)

Parâmetros

• discriminator (BaseDiscriminationFitter) – a discriminator that maps level 1 data to level 2 data. - Level 1 data may correspond to, e. g., IQ data. - Level 2 data is the state counts.

• base (Optional[int]) – the base of the expected states. If it is not given the base is inferred from the expected_state instance of discriminator.

__init__(discriminator, base=None)

Parâmetros

• discriminator (BaseDiscriminationFitter) – a discriminator that maps level 1 data to level 2 data. - Level 1 data may correspond to, e. g., IQ data. - Level 2 data is the state counts.

• base (Optional[int]) – the base of the expected states. If it is not given the base is inferred from the expected_state instance of discriminator.

Methods

__init__(discriminator[, base])	type discriminator BaseDiscriminationFitter
apply(raw_data)	Create a new result from the raw_data by converting level 1 data to level 2 data.
count(y_data)	Converts discriminated results into raw counts.
get_base(expected_states)	Returns the base inferred from expected_states.

apply(raw_data)

Create a new result from the raw_data by converting level 1 data to level 2 data.

Parâmetros

raw_data (Result) – list of qiskit.Result or qiskit.Result.

Tipo de retorno

Result

Retorna

A list of qiskit.Result or qiskit.Result.

count(y_data)

Converts discriminated results into raw counts.

Parâmetros

y_data (List[str]) – result of a discrimination.

Tipo de retorno

dict

Retorna

A dict of raw counts.

static get_base(expected_states)

Returns the base inferred from expected_states.

The intent is to allow users to discriminate states higher than 0/1.

DiscriminationFilter infers the basis from the expected states to allow users to discriminate states outside of the computational sub-space. For example, if the discriminated states are 00, 01, 02, 10, 11, …, 22 the basis will be 3.

With this implementation the basis can be at most 10.

Parâmetros

expected_states (dict) –

Retorna

the base inferred from the expected states

Tipo de retorno

int

Levanta

QiskitError – if there is an invalid input in the expected states