qamomile.optimization.converter

Overview¶

Classes¶

MathematicalProblemConverter [source]¶

class MathematicalProblemConverter(abc.ABC)

Constructor¶

def __init__(self, instance: ommx.v1.Instance | BinaryModel) -> None

Attributes¶

• instance

• original_vartype

• spin_model

Methods¶

decode¶

def decode(self, samples: SampleResult[list[int]]) -> BinarySampleSet

Decode quantum measurement results.

Returns results in the original vartype (BINARY or SPIN) that was provided when constructing the converter.

get_cost_hamiltonian¶

def get_cost_hamiltonian(self) -> qm_o.Hamiltonian

Construct the cost Hamiltonian.

Subclasses must implement this method to build the appropriate Hamiltonian for their specific algorithm (e.g., Pauli-Z for QAOA, QRAC-encoded for QRAO).

Returns:

qm_o.Hamiltonian — qm_o.Hamiltonian: The cost Hamiltonian.

SampleResult [source]¶

class SampleResult(Generic[T])

Result of a sample() execution.

Contains results as a list of (value, count) tuples.

Example:

result.results  # [(0.25, 500), (0.75, 500)]

Constructor¶

def __init__(self, results: list[tuple[T, int]], shots: int) -> None

Attributes¶

• results: list[tuple[T, int]] List of (value, count) tuples.

• shots: int Total number of shots executed.

Methods¶

most_common¶

def most_common(self, n: int = 1) -> list[tuple[T, int]]

Return the n most common results.

Parameters:

Returns:

list[tuple[T, int]] — List of (result, count) tuples sorted by count descending.

probabilities¶

def probabilities(self) -> list[tuple[T, float]]

Return probability distribution over results.

Returns:

list[tuple[T, float]] — List of (value, probability) tuples.