[ANN] Yao.jl 0.5: Extensible Efficient Quantum Algorithm Design for Humans

Yao.jl 0.5 has been released for a while. If you are interested now is the time to try it out! We hope this framework can ease your research in quantum information and please feel free to file us an issue and ask questions!

If you don’t remember what is this, Yao is a framework designed for quantum algorithm research with recent progress in variational quantum circuits in mind. You can also check our first announcement. Find more in our documentation: https://quantumbfs.github.io/Yao.jl/latest/

What’s new?

We refactored the whole package this year with:

  • new logo

Papers citing Yao

Two algorithm papers using Yao for their algorithms are now public on arxiv:

  • 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

There is also a review paper mentioned Yao:

Work in Progress

New Benchmarks

Benchmark with google/Cirq and qiskit default simulator is added. We thank Juan Gómez from IBM for advice on our benchmark on qiskit. Please feel free to point out if we miss anything in the benchmark: quantum-benchmarks, we don’t claim this benchmark is the final/canonical result since all the frameworks included are developed in a fast pace.

JuliaCon 2019

I will give a talk on JuliaCon 2019 about Yao: https://pretalx.com/juliacon2019/talk/8AM9JC/
the other core developer of Yao @1115 is also coming to JuliaCon 2019, please feel free to chat with us! Meet you in Baltimore!