iqm.iqm_client.models.QuantumArchitectureSpecification

class iqm.iqm_client.models.QuantumArchitectureSpecification(*, name: str, operations: dict[str, list[list[str]]], qubits: list[str], qubit_connectivity: list[list[str]])

Bases: BaseModel

Quantum architecture specification.

Attributes

model_config	Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].
name	Name of the quantum architecture.
operations	Operations supported by this quantum architecture, mapped to the allowed loci.
qubits	List of qubits of this quantum architecture.
qubit_connectivity	Qubit connectivity of this quantum architecture.

Methods

compare_operations(ops1, ops2)	Compares the given operation sets.
has_equivalent_operations(other)	Compares the given operation sets defined by the quantum architecture against another architecture specification.

Parameters:

• name (str) –

• operations (dict[str, list[list[str]]]) –

• qubits (list[str]) –

• qubit_connectivity (list[list[str]]) –

name: str

Name of the quantum architecture.

qubits: list[str]

List of qubits of this quantum architecture.

qubit_connectivity: list[list[str]]

Qubit connectivity of this quantum architecture.

operations: dict[str, list[list[str]]]

Operations supported by this quantum architecture, mapped to the allowed loci.

has_equivalent_operations(other: QuantumArchitectureSpecification) → bool

Compares the given operation sets defined by the quantum architecture against another architecture specification.

Returns:

True if the operation and the loci are equivalent.

Parameters:

other (QuantumArchitectureSpecification) –

Return type:

bool

static compare_operations(ops1: dict[str, list[list[str]]], ops2: dict[str, list[list[str]]]) → bool

Compares the given operation sets.

Returns:

True if the operation and the loci are equivalent.

Parameters:

• ops1 (dict[str, list[list[str]]]) –

• ops2 (dict[str, list[list[str]]]) –

Return type:

bool

model_config: ClassVar[ConfigDict] = {}

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