Extensible, Efficient Quantum Algorithm Design for Humans.
Yao is an open source framework that aims to empower quantum information research with software tools. It is designed with following in mind:
- quantum algorithm design;
- quantum software 2.0;
- quantum computation education.
We are in an early-release beta. Expect some adventures and rough edges.
A 3 line Quantum Fourier Transformation with Quantum Blocks:
A(i, j) = control(i, j=>shift(2π/(1<<(i-j+1))))
B(n, k) = chain(n, j==k ? put(k=>H) : A(j, k) for j in k:n)
qft(n) = chain(B(n, k) for k in 1:n)Yao is a julia language package. To install Yao, please open Julia's interactive session (known as REPL) and type ] in the REPL to use the package mode, then type this command:
For stable release
pkg> add YaoFor current master
pkg> add Yao#masterIf you have problem to install the package, please file us an issue.
For CUDA support, see CuYao.jl.
Examples: understand Yao's code for quantum algorithms
Some quantum algorithms are implemented with Yao in QuAlgorithmZoo.
- STABLE — most recently tagged version of the documentation.
- LATEST — in-development version of the documentation.
- Github issues: Please feel free to ask questions and report bugs, feature request in issues
- slack: you can join julia's slack channel and ask Yao related questions in
#yao-devchannel. - Julia discourse: You can also ask questions on julia discourse or the Chinese discourse
Please read our contribution guide.
This project is an effort of QuantumBFS, an open source organization for quantum science. Yao is currently maintained by Xiuzhe (Roger) luo and Jin-guo Liu with contributions from open source community. All the contributors are listed in the contributors.
Variational Quantum Eigensolver with Fewer Qubits, Jin-Guo Liu, Yi-Hong Zhang, Yuan Wan, Lei Wang, https://arxiv.org/abs/1902.02663
Learning and inference on generative adversarial quantum circuits, Jinfeng Zeng, Yufeng Wu, Jin-Guo Liu, Lei Wang, and Jiangping Hu, Phys. Rev. A 99, 052306 – Published 6 May 2019
Parameterized quantum circuits as machine learning models, Marcello Benedetti, Erika Lloyd, and Stefan Sack https://arxiv.org/pdf/1906.07682.pdf
Yao is released under the Apache 2 license.