create_backend_from_properties

create_backend_from_properties(properties, n_qubits=None, default_date=None)[source]

Create a populated GenericBackendV2 from a BackendProperties dictionary.

This function handles the complete workflow:

  • Normalizes the properties dictionary (fills in missing fields).

  • Infers the number of qubits from the properties if not provided.

  • Creates a GenericBackendV2 backend whose target reflects the supplied calibration values (T1/T2, frequency, gate errors, gate durations, readout errors).

The returned backend’s target is the source of truth for downstream qiskit consumers — the transpiler reads gate durations and errors from it, and qiskit_aer.noise.NoiseModel.from_backend derives device noise from the same target.

Parameters:

  • properties (dict[str, Any]) – BackendProperties dictionary. Missing fields will be filled automatically.

  • n_qubits (int | None) – Optional number of qubits. If None, will be inferred from the length of the “qubits” list in the properties dictionary.

  • default_date (datetime | None) – Optional datetime to use for missing date fields. If None, uses current time.

Return type:

GenericBackendV2

Returns:

GenericBackendV2 backend whose target carries the supplied calibration values.

Raises:

ValueError – If n_qubits is not provided and cannot be inferred from properties (i.e., qubits list is empty or missing), or if n_qubits is less than 1.

Example

>>> props = {
...     "backend_name": "test",
...     "qubits": [[{"name": "T1", "value": 100.0}]],  # 1 qubit
...     "gates": [{"gate": "sx", "qubits": [0], "parameters": []}]
... }
>>> # Infer qubit count from properties (will be 1)
>>> backend = create_backend_from_properties(props)
>>> backend.num_qubits
1
>>> # Override qubit count if needed
>>> backend_large = create_backend_from_properties(props, n_qubits=120)
>>> backend_large.num_qubits
120