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https://github.com/juliaqubo/dwave.jl
🌊 D-Wave Quantum Annealing Interface for JuMP
https://github.com/juliaqubo/dwave.jl
julia jump optimization quantum-computing
Last synced: 20 days ago
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🌊 D-Wave Quantum Annealing Interface for JuMP
- Host: GitHub
- URL: https://github.com/juliaqubo/dwave.jl
- Owner: JuliaQUBO
- License: mit
- Created: 2022-10-07T18:53:23.000Z (about 2 years ago)
- Default Branch: master
- Last Pushed: 2024-05-29T02:40:27.000Z (6 months ago)
- Last Synced: 2024-09-24T22:09:46.058Z (about 2 months ago)
- Topics: julia, jump, optimization, quantum-computing
- Language: Julia
- Homepage:
- Size: 45.9 KB
- Stars: 12
- Watchers: 4
- Forks: 3
- Open Issues: 1
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# DWave.jl
[](https://github.com/psrenergy/QUBODrivers.jl)
D-Wave Quantum Annealing Interface for JuMP
## Installation
```julia
julia> import Pkg
julia> Pkg.add("DWave.jl")
```
## Basic Usage
```julia
using JuMP
using QUBO
using DWave
model = Model(DWave.Neal.Optimizer)
h = [-1, -1, -1]
J = [0 2 2; 0 0 2; 0 0 0]
@variable(model, s[1:3], Spin)
@objective(model, Min, h's + s'J * s)
optimize!(model)
for i = 1:result_count(model)
si = value.(s; result=i)
yi = objective_value(model; result=i)
println("H($si) = $yi")
end
```
## API Token
To use D-Wave's QPU it is necessary to obtain an API Token from [Leap](https://cloud.dwavesys.com/leap/).
**Disclaimer:** _The D-Wave wrapper for Julia is not officially supported by D-Wave Systems. If you are a commercial customer interested in official support for Julia from D-Wave, let them know!_
**Note**: _If you are using [DWave.jl](https://github.com/psrenergy/DWave.jl) in your project, we recommend you to include the `.CondaPkg` entry in your `.gitignore` file. The PythonCall module will place a lot of files in this folder when building its Python environment._