Samplers
Utility Samplers
Exact Sampler
QUBODrivers.ExactSampler.Optimizer — TypeExactSampler.Optimizer{T}This sampler performs an exhaustive search over all $2^{n}$ possible states.
Due to the exponetially large amount of visited states, it is not possible to use this sampler for problems any larger than $20$ variables big.
Random Sampler
QUBODrivers.RandomSampler.Optimizer — TypeRandomSampler.Optimizer{T}Attributes
RandomSeed,"seed": Random seed to initialize the random number generator.NumberOfReads,"num_reads": Number of random states sampled per run.RandomGenerator,"rng": Random Number Generator instance.
Identity Sampler
QUBODrivers.IdentitySampler.Optimizer — TypeIdentitySampler.Optimizer{T}This sampler selects precisely the state vector provided as warm-start.
Showcase
Before explaining in detail how to use this package, it's good to list a few examples for the reader to grasp. Below, there are links to the files containing the actual interface implementations. These are mostly thin wrappers interfacing with common algorithms and heuristics written in Python, Julia or C/C++.
| Project | Source Code |
|---|---|
| DWave.jl | DWave |
| DWaveNeal.jl | DWaveNeal |
| IsingSolvers.jl | GreedyDescent |
| ILP | |
| MCMCRandom | |
| QuantumAnnealingInterface.jl | QuantumAnnealingInterface |
| CIMOptimizer.jl | CIMOptimizer |