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

$$\begin{array}{rl} \text{QUBO}:~ \displaystyle \min_{\vec{x}} & \displaystyle \alpha \left[{ \vec{x}' Q \vec{x} \beta }\right] \\ \text{s.t.} & \displaystyle \vec{x} \in S \cong \mathbb{B}^{n} \end{array}$$

where $Q \in \mathbb{R}^{n \times n}$ is a symmetric matrix. Maximization is automatically converted to minimization in a transparent fashion during runtime.

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

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;

PSR Quantum Optimization Toolchain