Warning This package was archived. Consider using QUBODrivers instead.
This package aims to provide a common MOI-compliant API for QUBO Sampling & Annealing machines. It also contains a few testing tools, including utility samplers for performance comparison and sanity checks, and some basic analysis features.
Problems assigned to solvers defined within Anneal.jl's interface are given by
where
julia> ]add Anneal
or
julia> import Pkg; Pkg.add("Anneal")
using JuMP
using Anneal
model = Model(ExactSampler.Optimizer)
Q = [
-1.0 2.0 2.0
2.0 -1.0 2.0
2.0 2.0 -1.0
]
@variable(model, x[1:3], Bin)
@objective(model, Min, x' * Q * x)
optimize!(model)
for i = 1:result_count(model)
xᵢ = value.(x; result=i)
yᵢ = objective_value(model; result=i)
println("f($xᵢ) = $yᵢ")
end
Module Name | Descripition | Package |
---|---|---|
ExactSampler |
Sequentially samples all possible states by exaustive enumeration. Finds the global optimum but can't be used for models with much more than 20 variables. | Anneal.jl |
IdentitySampler |
Samples the exact same state defined as warm start. | Anneal.jl |
RandomSampler |
Randomly samples states by regular or biased coin tossing. It is commonly used to compare new solving methods to a random guessing baseline. | Anneal.jl |
Module Name | Descripition | Package |
---|---|---|
DWave |
Wrapper for D-Wave's Quantum Annealing API. | DWave.jl |
DWaveNeal |
Wrapper for D-Wave's open-source Simulated Annealing sampler. | DWaveNeal.jl |
QuantumAnnealingInterface |
Wrapper for LANL's Quantum Annealing simulator | QuantumAnnealingInterface.jl |
Module Name | Descripition | Package |
---|---|---|
GreedyDescent |
Stochastic greedy descent algorithm. | IsingSolvers.jl |
ILP |
Integer Linear Programming apporach using a regular MIP solver chosen by the user. | IsingSolvers.jl |
MCMCRandom |
Monte Carlo Markov Chain Random sampler | IsingSolvers.jl |
If you implemented your own sampler interface using Anneal.jl, consider opening an issue or submiting a pull request to add it to the list.
There are two options to consider when using Anneal.jl, namely AbstractSampler
and AutomaticSampler
.
As the diagram below indicates, the automatic type is a subtype of the general, abstract one.
flowchart TB;
OPTIMIZER(["<code>MOI.AbstractOptimizer</code>"]);
ABSTRACT(["<code>AbstractSampler</code>"]);
AUTOMATIC(["<code>AutomaticSampler</code>"]);
OPTIMIZER --> ABSTRACT --> AUTOMATIC;
subgraph UTILITY [Utility]
direction LR
EXACT["<code>ExactSampler</code>"];
IDENTITY["<code>IdentiySampler</code>"];
RANDOM["<code>RandomSampler</code>"];
end
subgraph HEURISTICS [Heuristics]
direction LR
GREEDY["<code>IsingSolvers.GreedyDescent</code>"];
ILP["<code>IsingSolvers.ILP</code>"];
MCMC["<code>IsingSolvers.MCMCRandom</code>"];
end
subgraph INTERFACES [Interfaces]
direction LR
DWAVE["<code>DWave</code>"];
DWAVENEAL["<code>DWaveNeal</code>"];
QUANTUMANNEALING["<code>QuantumAnnealingInterface</code>"];
end
AUTOMATIC --> UTILITY;
AUTOMATIC --> INTERFACES;
AUTOMATIC --> HEURISTICS;