QCIOpt.jl

Quantum Computing Inc. Optimization Wrapper for JuMP

Installation

julia> import Pkg

julia> Pkg.add(url="https://github.com/SECQUOIA/QCIOpt.jl")

Basic Usage

using JuMP
using QCIOpt

model = Model(QCIOpt.Optimizer)

Q = [
   -1  2  2
    2 -1  2
    2  2 -1
]

@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

Updating optimization parameters

set_attribute(model, QCIOpt.NumberOfReads(), 10) # Number of samples

Changing the backend device

set_attribute(model, QCIOpt.DeviceType(), "dirac-1")

API Token

To access QCI's devices, it is necessary to create an account at QCI to obtain an API Token and define

set_attribute(model, QCIOpt.APIToken(), "your_token_here")

Another option is to set the QCI_TOKEN environment variable before loading QCIOpt.jl:

$ export QCI_TOKEN="your_token_here"

$ julia

julia> using QCIOpt

Disclaimer: The QCI Optimization Wrapper for Julia is not officially supported by Quantum Computing Inc. If you are a commercial customer interested in official support for Julia from QCI, let them know!

Note: If you are using QCIOpt.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.