iqm.iqm_client.models.RunResult

class iqm.iqm_client.models.RunResult(*, status, measurements=None, message=None, metadata, warnings=None)

Bases: BaseModel

Results of the quantum circuit execution job. If the job succeeded, measurements contains the output of the batch of circuits, consisting of the results of the measurement operations in each circuit. It is a list of dictionaries, where each dict maps each measurement key to a 2D array of measurement results, represented as a nested list. RunResult.measurements[circuit_index][key][shot][qubit_index] is the result of measuring the qubit_index’th qubit in measurement operation key in the shot shot in the circuit_index’th circuit of the batch. measurements is present iff the status is 'ready'. message carries additional information for the 'failed' status. If the status is 'pending compilation' or 'pending execution', measurements and message are None.

The results are non-negative integers representing the computational basis state (for qubits, 0 or 1) that was the measurement outcome.

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Attributes

model_computed_fields	A dictionary of computed field names and their corresponding ComputedFieldInfo objects.
model_config	Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].
model_fields	Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo].
status	current status of the job, in {'pending compilation', 'pending execution', 'ready', 'failed', 'aborted'}
measurements	if the job has finished successfully, the measurement results for the circuit(s)
message	if the job failed, an error message
metadata	metadata about the job
warnings	list of warning messages

Methods

from_dict(inp)

Parses the result from a dict.

Parameters:

• status (Status) –

• measurements (list[dict[str, list[list[int]]]] | None) –

• message (str | None) –

• metadata (Metadata) –

• warnings (list[str] | None) –

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[dict[str, FieldInfo]] = {'measurements': FieldInfo(annotation=Union[list[dict[str, list[list[int]]]], NoneType], required=False, default=None), 'message': FieldInfo(annotation=Union[str, NoneType], required=False, default=None), 'metadata': FieldInfo(annotation=Metadata, required=True), 'status': FieldInfo(annotation=Status, required=True), 'warnings': FieldInfo(annotation=Union[list[str], NoneType], required=False, default=None)}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo].

This replaces Model.__fields__ from Pydantic V1.

status: Status

current status of the job, in {'pending compilation', 'pending execution', 'ready', 'failed', 'aborted'}

measurements: CircuitMeasurementResultsBatch | None

if the job has finished successfully, the measurement results for the circuit(s)

message: str | None

if the job failed, an error message

metadata: Metadata

metadata about the job

warnings: list[str] | None

list of warning messages

static from_dict(inp)

Parses the result from a dict.

Parameters:

inp (dict[str, str | dict]) – value to parse, has to map to RunResult

Returns:

parsed job result

Return type:

RunResult