iqm.iqm_client.models.DynamicQuantumArchitecture#
- class iqm.iqm_client.models.DynamicQuantumArchitecture(*, calibration_set_id, qubits, computational_resonators, gates)#
- 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 - A dictionary of computed field names and their corresponding ComputedFieldInfo objects. - Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict]. - Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects. - id of the calibration set from which this DQA was generated - qubits that appear in at least one gate locus in the calibration set - computational resonators that appear in at least one gate locus in the calibration set - 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 
 - computational_resonators: list[str]#
- computational resonators that appear in at least one gate locus in the calibration set 
 - 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]] = {'calibration_set_id': FieldInfo(annotation=UUID, required=True), 'computational_resonators': FieldInfo(annotation=list[str], required=True), 'gates': FieldInfo(annotation=dict[str, GateInfo], required=True), 'qubits': FieldInfo(annotation=list[str], required=True)}#
- Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects. - This replaces Model.__fields__ from Pydantic V1. 
 
