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.