loom.executor.eka_to_pennylane_converter

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class loom.executor.eka_to_pennylane_converter.EkaToPennylaneConverter(**data)[source]

Bases: Converter[str, dict[str, Any]]

Convert Eka InterpretationStep to PennyLane.

Here’s a simple example of how to use this method to execute Eka experiment with PennyLane:

from loom.executor import EkaToPennylaneConverter

pl_converter = EkaToPennylaneConverter(is_catalyst=False)
pl_program, q_register, c_register = pl_converter.convert(interpreted_eka)
n_qubits = len(q_register)

# Indent the program body so it fits inside a function
indented_program = "\n    ".join(pl_program.splitlines())

# Construct the Python program string
s_prog = f"""
import pennylane as qml

def circuit():
    {indented_program}
    return {{k:qml.sample(measurements[k]) for k in measurements.keys()}}

# Use a PennyLane device
dev = qml.device("lightning.qubit", wires=n_qubits, shots=5)
circ = qml.QNode(circuit, dev)

results = circ()
"""
local_ns = {}
exec(s_prog, globals(), local_ns)

results = local_ns["results"]

parsed_outcome = pl_converter.parse_target_run_outcome(results)
Parameters:

  • is_catalyst (bool) – Whether the PennyLane program is intended to run on Catalyst.

  • import_prefix (str) – The import alias for PennyLane defaults to “qml.”.

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

ALLOW_ERROR_MODELS: bool
SUPPORTED_OPERATIONS: frozenset[OpSignature]
convert_circuit(input_circuit)[source]

Convert an Eka Circuit to PennyLane code string along with quantum and classical channel maps.

Return type:

tuple[str, dict[str, int], dict[str, str]]

Returns:

A tuple containing:

  • The PennyLane code string representing the circuit.

  • A dictionary mapping Eka quantum channel IDs to PennyLane wire indices.

  • A dictionary mapping Eka classical channel IDs to PennyLane measurement keys.

emit_init_instructions(circuit)[source]

Provide a mapping from eka channel label to initialized PennyLane wire index.

Return type:

tuple[str, dict[str, int], dict[str, str]]

emit_leaf_circuit_instruction(circuit, quantum_channel_map, classical_channel_map)[source]

Provide the python code (as a string) to emit an Eka instruction in the target language.

Return type:

str

import_prefix: str
is_catalyst: bool
model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'frozen': True}

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

model_fields: ClassVar[Dict[str, FieldInfo]] = {'ALLOW_ERROR_MODELS': FieldInfo(annotation=bool, required=False, default=False, frozen=True, init=False), 'SUPPORTED_OPERATIONS': FieldInfo(annotation=frozenset[OpSignature], required=False, default=frozenset({OpSignature(name='measure_z', op_type=<OpType.MEASUREMENT: 'measurement'>, quantum_input=1, classical_input=1, is_clifford=True, description=''), OpSignature(name='reset_0', op_type=<OpType.RESET: 'reset'>, quantum_input=1, classical_input=0, is_clifford=True, description=''), OpSignature(name='reset_1', op_type=<OpType.RESET: 'reset'>, quantum_input=1, classical_input=0, is_clifford=True, description=''), OpSignature(name='measure_y', op_type=<OpType.MEASUREMENT: 'measurement'>, quantum_input=1, classical_input=1, is_clifford=True, description=''), OpSignature(name='z', op_type=<OpType.SINGLE_QUBIT: 'single_qubit'>, quantum_input=1, classical_input=0, is_clifford=True, description=''), OpSignature(name='phaseinv', op_type=<OpType.SINGLE_QUBIT: 'single_qubit'>, quantum_input=1, classical_input=0, is_clifford=True, description=''), OpSignature(name='cy', op_type=<OpType.TWO_QUBIT: 'two_qubit'>, quantum_input=2, classical_input=0, is_clifford=True, description=''), OpSignature(name='reset_+', op_type=<OpType.RESET: 'reset'>, quantum_input=1, classical_input=0, is_clifford=True, description=''), OpSignature(name='cx', op_type=<OpType.TWO_QUBIT: 'two_qubit'>, quantum_input=2, classical_input=0, is_clifford=True, description=''), OpSignature(name='reset_-', op_type=<OpType.RESET: 'reset'>, quantum_input=1, classical_input=0, is_clifford=True, description=''), OpSignature(name='reset_+i', op_type=<OpType.RESET: 'reset'>, quantum_input=1, classical_input=0, is_clifford=True, description=''), OpSignature(name='y', op_type=<OpType.SINGLE_QUBIT: 'single_qubit'>, quantum_input=1, classical_input=0, is_clifford=True, description=''), OpSignature(name='reset_-i', op_type=<OpType.RESET: 'reset'>, quantum_input=1, classical_input=0, is_clifford=True, description=''), OpSignature(name='cz', op_type=<OpType.TWO_QUBIT: 'two_qubit'>, quantum_input=2, classical_input=0, is_clifford=True, description=''), OpSignature(name='phase', op_type=<OpType.SINGLE_QUBIT: 'single_qubit'>, quantum_input=1, classical_input=0, is_clifford=True, description=''), OpSignature(name='h', op_type=<OpType.SINGLE_QUBIT: 'single_qubit'>, quantum_input=1, classical_input=0, is_clifford=True, description=''), OpSignature(name='measurement', op_type=<OpType.MEASUREMENT: 'measurement'>, quantum_input=1, classical_input=1, is_clifford=True, description=''), OpSignature(name='cnot', op_type=<OpType.TWO_QUBIT: 'two_qubit'>, quantum_input=2, classical_input=0, is_clifford=True, description=''), OpSignature(name='measure_x', op_type=<OpType.MEASUREMENT: 'measurement'>, quantum_input=1, classical_input=1, is_clifford=True, description=''), OpSignature(name='i', op_type=<OpType.SINGLE_QUBIT: 'single_qubit'>, quantum_input=1, classical_input=0, is_clifford=True, description=''), OpSignature(name='reset', op_type=<OpType.RESET: 'reset'>, quantum_input=1, classical_input=0, is_clifford=True, description=''), OpSignature(name='x', op_type=<OpType.SINGLE_QUBIT: 'single_qubit'>, quantum_input=1, classical_input=0, is_clifford=True, description=''), OpSignature(name='swap', op_type=<OpType.TWO_QUBIT: 'two_qubit'>, quantum_input=2, classical_input=0, is_clifford=True, description='')})), 'import_prefix': FieldInfo(annotation=str, required=False, default='qml.', description='The import alias for PennyLane.', frozen=True, init=True), 'is_catalyst': FieldInfo(annotation=bool, required=False, default=False, frozen=True, init=True), 'separator_for_else_in_condition': FieldInfo(annotation=str, required=False, default=', is_else=', description='The separator string used in the description for else conditions.', frozen=True, init=False)}

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.

property operations_map: dict[str, Callable[[list[str], list[str], str | None], str]]

Map Eka operations to PennyLane instructions. The map return a sequence of PennyLane instructions, which are specified by name, wires, classical register label, and whether it is a measurement or classically controlled operation.

static parse_target_run_outcome(outcome)[source]

Parse the PennyLane/catalyst run outcome into a dictionary mapping the Eka classical channels labels to the measurement outcomes.

Return type:

dict[str, list[int]]

classmethod validate_import_prefix(v)[source]

Ensure the import prefix ends with a dot if not empty.

Return type:

str