iqm.iqm_client.models.DynamicQuantumArchitecture#

class iqm.iqm_client.models.DynamicQuantumArchitecture(*, calibration_set_id: UUID, qubits: list[str], computational_resonators: list[str], gates: dict[str, GateInfo])#

Bases: BaseModel

Dynamic quantum architecture as returned by server.

The dynamic quantum architecture (DQA) describes gates/operations for which calibration data exists in the calibration set.

Attributes

components

Returns all locus components (qubits and computational resonators) sorted.

model_config

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

calibration_set_id

id of the calibration set from which this DQA was generated

qubits

qubits that appear in at least one gate locus in the calibration set

computational_resonators

computational resonators that appear in at least one gate locus in the calibration set

gates

mapping of gate names to information about the gates

Methods

Parameters:
calibration_set_id: UUID#

id of the calibration set from which this DQA was generated

qubits: list[str]#

qubits that appear in at least one gate locus in the calibration set

computational_resonators: list[str]#

computational resonators that appear in at least one gate locus in the calibration set

gates: dict[str, GateInfo]#

mapping of gate names to information about the gates

property components: tuple[str, ...]#

Returns all locus components (qubits and computational resonators) sorted.

The components are first sorted alphabetically based on their non-numeric part, and then components with the same non-numeric part are sorted numerically. An example of components sorted this way would be: (‘COMPR1’, ‘COMPR2’, ‘QB1’, ‘QB2’, ‘QB3’, ‘QB10’, ‘QB11’, ‘QB20’).

model_config: ClassVar[ConfigDict] = {}#

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