QBSolvLikeQpu¶
The QBSolv-like QPU is a specialized solver designed to tackle complex problems by decomposing them into smaller, manageable subproblems. It then solves these individual parts using a Quantum Processing Unit (QPU).
This particular implementation achieves its QBSolv-like behavior by utilizing the hybrid.QPUSubproblemAutoEmbeddingSampler from the D-Wave Ocean SDK as the core sampler for these subproblems. This approach allows for efficient handling of large-scale problems by breaking them down and leveraging the strengths of quantum computation for the subcomponents.
Note
This solver is only available for commercial and academic licenses.
Compatible Backends¶
The QBSolvLikeQpu algorithm supports the following backends:
By default, QBSolvLikeQpu uses the DWaveQpu backend.
Initialization¶
The following section outlines the default configurations of QBSolvLikeQpu. 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.
from luna_quantum.solve.parameters.algorithms import QBSolvLikeQpu
from luna_quantum.solve.parameters.algorithms.base_params import (
Decomposer,
QuantumAnnealingParams
)
algorithm = QBSolvLikeQpu(
backend=None,
decomposer_size=50,
rolling=True,
rolling_history=0.15,
max_iter=100,
max_time=5,
convergence=3,
target=None,
rtol=1e-05,
atol=1e-08,
num_reads=100,
num_retries=0,
quantum_annealing_params=QuantumAnnealingParams(
anneal_offsets=None,
anneal_schedule=None,
annealing_time=None,
auto_scale=None,
fast_anneal=False,
flux_biases=None,
flux_drift_compensation=True,
h_gain_schedule=None,
initial_state=None,
max_answers=None,
num_reads=1,
programming_thermalization=None,
readout_thermalization=None,
reduce_intersample_correlation=False,
reinitialize_state=None
),
decomposer=Decomposer(
size=10,
min_gain=None,
rolling=True,
rolling_history=1.0,
silent_rewind=True,
traversal='energy'
)
)
Parameter Details
For a complete overview of available parameters and their usage, see the QBSolvLikeQpu API Reference.
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")
API Reference¶
Bases: QBSolvLikeMixin, LunaAlgorithm[DWaveQpu]
QBSolv-like algorithm for QPU.
QBSolv QPU splits the problem into parts and solves them using the Tabu Search algorithm. For this purpose, the DWaveSampler is used.
Attributes:
| Name | Type | Description |
|---|---|---|
decomposer_size |
int
|
Size for the decomposer. Determines the maximum subproblem size to be sent to the quantum processor, with larger values potentially improving solution quality at the cost of increased processing time. |
rolling |
bool
|
Whether to use rolling for the solver. When enabled, this allows for smoother transitions between subproblems during the decomposition process. |
rolling_history |
float
|
Rolling history parameter for the solver. Controls how much previous iteration information is considered when solving subsequent subproblems. |
max_iter |
int | None
|
Maximum number of iterations. Limits the total number of decomposition and solving cycles performed by the algorithm. |
max_time |
int
|
Time in seconds after which the algorithm will stop. Provides a time-based stopping criterion regardless of convergence status. |
convergence |
int
|
Number of iterations with unchanged output to terminate algorithm. Higher values ensure more stable solutions but may increase computation time. |
target |
float | None
|
Energy level that the algorithm tries to reach. If this target energy is achieved, the algorithm will terminate early. |
rtol |
float
|
Relative tolerance for convergence. Used when comparing energy values between iterations to determine if convergence has been reached. |
atol |
float
|
Absolute tolerance for convergence. Used alongside rtol when comparing energy values to determine convergence. |
num_reads |
int
|
Number of reads for the solver. |
num_retries |
int
|
Number of retries for the solver. |
quantum_annealing_params |
QuantumAnnealingParams
|
Quantum annealing parameters. |
decomposer |
Decomposer
|
Decomposer: Breaks down problems into subproblems of manageable size Default is a Decomposer instance with default settings. |
backend
class-attribute
instance-attribute
¶
decomposer
class-attribute
instance-attribute
¶
decomposer: Decomposer = Field(default_factory=Decomposer)
model_config
class-attribute
instance-attribute
¶
quantum_annealing_params
class-attribute
instance-attribute
¶
quantum_annealing_params: QuantumAnnealingParams = Field(
default_factory=QuantumAnnealingParams
)
get_compatible_backends
classmethod
¶
get_compatible_backends() -> tuple[type[DWaveQpu], ...]
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() -> DWaveQpu
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. |