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:
We are in an early-release beta. Expect some adventures and rough edges.
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)
For stable release
pkg> add Yao
For current master
pkg> add Yao#master
If you have problem to install the package, please file us an issue.
For CUDA support, see CuYao.jl.
Some quantum algorithms are implemented with Yao in QuAlgorithmZoo.
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.
3 days ago