QUBODrivers.jl Documentation

Introduction

QUBODrivers.jl provides a common MathOptInterface-compatible API for QUBO samplers and annealing backends.

The package includes:

• utility samplers for exact enumeration, random sampling, and warm-start identity sampling;
• a macro for declaring sampler optimizers and user-facing attributes;
• MOI and QUBOTools plumbing for model conversion and result access;
• a reusable test suite for sampler implementations.

If you want to solve a model, start with Solving QUBO. If you want to implement a new sampler wrapper, start with Sampler Setup and Implementing a Sampler.

Quick Start

Installation

QUBODrivers.jl is registered in Julia's General Registry and is available for download using the standard package manager.

julia> import Pkg

julia> Pkg.add("QUBODrivers")

Example

using JuMP
using QUBODrivers

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

Precompiling packages...
  28908.8 ms  ✓ JuMP
  1 dependency successfully precompiled in 29 seconds. 43 already precompiled.
f([0.0, 1.0, 0.0]) = -1.0
f([1.0, 0.0, 0.0]) = -1.0
f([0.0, 0.0, 1.0]) = -1.0
f([0.0, 0.0, 0.0]) = 0.0
f([1.0, 0.0, 1.0]) = 2.0
f([1.0, 1.0, 0.0]) = 2.0
f([0.0, 1.0, 1.0]) = 2.0
f([1.0, 1.0, 1.0]) = 9.0

<!– ## Citing QUBODrivers.jl

@software{QUBODrivers.jl:2023,
  author    = {Pedro Xavier and Pedro Ripper and Tiago Andrade and Joaquim Garcia and David Bernal Neira},
  title     = {QUBODrivers.jl},
  month     = {apr},
  year      = {2023},
  publisher = {Zenodo},
  version   = {v0.3.4},
  doi       = {10.5281/zenodo.13840948},
  url       = {https://doi.org/10.5281/zenodo.13840948}
}

–>