Author FZJ-PGI-12
6 Stars
Updated Last
1 Year Ago
Started In
January 2023



This package implements the Quantum Approximate Optimization Algorithm and the Mean-Field Approximate Optimization Algorithm.


To install, use Julia's built-in package manager

julia> ] add QAOA

Documentation & Examples

Our docs can be found here. Examples showcasing the use of QAOA.jl are also presented in our examples folder.


QAOA.jl also supports gradient optimization via automatic differentiation. Below is a comparison of run times between PennyLane [@PennyLane] and QAOA.jl on an Apple M1 processor. The benchmarks are retrieved by performing 128 steps with the respective gradient optimizer on the same instance of size $N$ of the minimum vertex-cover problem.


If you are using code from this repository, please cite our work:

  doi = {10.48550/ARXIV.2303.00329},
  url = {},
  author = {Misra-Spieldenner, Aditi and Bode, Tim and Schuhmacher, Peter K. and Stollenwerk, Tobias and Bagrets, Dmitry and Wilhelm, Frank K.},
  keywords = {Quantum Physics (quant-ph), Disordered Systems and Neural Networks (cond-mat.dis-nn), FOS: Physical sciences, FOS: Physical sciences},
  title = {Mean-Field Approximate Optimization Algorithm},
  publisher = {arXiv},
  year = {2023},
  copyright = { perpetual, non-exclusive license}