QAOA_FO

QAOA_FO is Q-CTRL's implementation of the Quantum Approximate Optimization Algorithm (QAOA) through their Fire Opal framework. It is a hybrid quantum-classical algorithm for solving combinatorial optimization problems with enhanced performance through Q-CTRL's error mitigation and control techniques.

The algorithm works by preparing a quantum state through alternating applications of problem-specific (cost) and mixing Hamiltonians, controlled by variational parameters that are optimized classically to maximize the probability of measuring the optimal solution.

QAOA_FO leverages Q-CTRL's expertise in quantum control to improve circuit fidelity and optimization performance. It is particularly suited for problems that can be encoded as quadratic unconstrained binary optimization (QUBO) or Ising models, such as MaxCut, TSP, and portfolio optimization.

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Compatible Backends

The QAOA_FO algorithm supports the following backends:

• Qctrl

By default, QAOA_FO uses the Qctrl backend.

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Initialization

The following section outlines the default configurations of QAOA_FO. You can also specify other compatible backends for the algorithm. When backend=None is specified, the default backend will be initialized automatically. In this case, if the backend requires a token, it will be taken from the environment variables.

Default Configuration

from luna_quantum.solve.parameters.algorithms import QAOA_FO

algorithm = QAOA_FO(
    backend=None
)

Parameter Details

For a complete overview of available parameters and their usage, see the QAOA_FO API Reference.

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Usage

from luna_quantum import LunaSolve

LunaSolve.authenticate("<YOUR_LUNA_API_KEY>")

# Define your model and algorithm
model = ...
algorithm = ...

solve_job = algorithm.run(model, name="my-solve-job")

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API Reference

Bases: LunaAlgorithm[Qctrl]

Quantum Approximate Optimization Algorithm via Fire Opal (QAOA_FO).

QAOA_FO is Q-CTRL's implementation of the Quantum Approximate Optimization Algorithm (QAOA) through their Fire Opal framework. It is a hybrid quantum-classical algorithm for solving combinatorial optimization problems with enhanced performance through Q-CTRL's error mitigation and control techniques. For more details, please refer to the Fire Opal QAOA documentation <https://docs.q-ctrl.com/fire-opal/execute/run-algorithms/solve-optimization-problems/fire-opals-qaoa-solver>_.

The algorithm works by preparing a quantum state through alternating applications of problem-specific (cost) and mixing Hamiltonians, controlled by variational parameters that are optimized classically to maximize the probability of measuring the optimal solution.

QAOA_FO leverages Q-CTRL's expertise in quantum control to improve circuit fidelity and optimization performance. It is particularly suited for problems that can be encoded as quadratic unconstrained binary optimization (QUBO) or Ising models, such as MaxCut, TSP, and portfolio optimization.

backend class-attribute instance-attribute

backend: BACKEND_TYPE | None = Field(default=None, exclude=True, repr=False)

model_config class-attribute instance-attribute

model_config = ConfigDict(
    arbitrary_types_allowed=True, extra="allow", validate_assignment=True
)

get_compatible_backends classmethod

get_compatible_backends() -> tuple[type[Qctrl]]

Check at runtime if the used backend is compatible with the solver.

Returns:

Type	Description
tuple[type[IBackend], ...]	True if the backend is compatible with the solver, False otherwise.

get_default_backend classmethod

get_default_backend() -> Qctrl

Return the default backend implementation.

This property must be implemented by subclasses to provide the default backend instance to use when no specific backend is specified.

Returns:

Type	Description
IBackend	An instance of a class implementing the IBackend interface that serves as the default backend.

run

run(
    model: Model | str,
    name: str | None = None,
    backend: BACKEND_TYPE | None = None,
    client: LunaSolve | str | None = None,
    *args: Any,
    **kwargs: Any,
) -> SolveJob

Run the configured solver.

Parameters:

Name	Type	Description	Default
model	Model or str	The model to be optimized or solved. It could be an Model instance or a string identifier representing the model id.	required
name	str | None	If provided, the name of the job. Defaults to None.	None
backend	BACKEND_TYPE | None	Backend to use for the solver. If not provided, the default backend is used.	None
client	LunaSolve or str	The client interface used to interact with the backend services. If not provided, a default client will be used.	None
*args	Any	Additional arguments that will be passed to the solver or client.	()
**kwargs	Any	Additional keyword parameters for configuration or customization.	{}

Returns:

Type	Description
SolveJob	The job object containing the information about the solve process.