mqt.qudits.compiler.onedit.mapping_aware_transpilation¶

Submodules¶

Package Contents¶

class PhyAdaptiveDecomposition(gate: Gate, graph_orig: LevelGraph, cost_limit: tuple[float, float] | None = (0, 0), dimension: int | None = -1, z_prop: bool | None = False, max_nodes: int = 1000)[source]¶

max_nodes = 1000¶

circuit: QuantumCircuit¶

U: numpy.typing.NDArray[numpy.complex128]¶

qudit_index: int¶

graph: LevelGraph¶

cost_limit: tuple[float, float] = (0, 0)¶

dimension: int = -1¶

phase_propagation: bool = False¶

TREE: NAryTree¶

execute() → tuple[list[Gate], tuple[float, float], LevelGraph][source]¶

z_extraction(decomposition: list[Node], placement: LevelGraph, phase_propagation: bool) → tuple[list[Gate], LevelGraph][source]¶

dfs(current_root: Node) → None[source]¶

class PhyLocAdaPass(backend: Backend, vrz_prop: bool = False)[source]¶

Bases: mqt.qudits.compiler.CompilerPass

Helper class that provides a standard way to create an ABC using inheritance.

vrz_prop = False¶

transpile_gate(gate: Gate) → list[Gate][source]¶

transpile(circuit: QuantumCircuit) → QuantumCircuit[source]¶

class PhyLocQRPass(backend: Backend)[source]¶

Bases: mqt.qudits.compiler.CompilerPass

Helper class that provides a standard way to create an ABC using inheritance.

transpile_gate(gate: Gate) → list[Gate][source]¶

transpile(circuit: QuantumCircuit) → QuantumCircuit[source]¶

class PhyQrDecomp(gate: Gate, graph_orig: LevelGraph, z_prop: bool = False, not_stand_alone: bool = True)[source]¶

gate: Gate¶

circuit: QuantumCircuit¶

dimension: int¶

qudit_index: int¶

U: numpy.typing.NDArray[numpy.complex128]¶

graph: LevelGraph¶

phase_propagation: bool = False¶

not_stand_alone: bool = True¶

execute() → tuple[list[Gate], float, float][source]¶