Yao.jl: Extensible, Efficient Framework for Quantum Algorithm Design

Xiu-Zhe Luo1,2,3,4, Jin-Guo Liu1, Pan Zhang2, and Lei Wang1,5

1Institute of Physics, Chinese Academy of Sciences, Beijing 100190, China
2Institute of Theoretical Physics, Chinese Academy of Sciences, Beijing 100190, China
3Department of Physics and Astronomy, University of Waterloo, Waterloo N2L 3G1, Canada
4Perimeter Institute for Theoretical Physics, Waterloo, Ontario N2L 2Y5, Canada
5Songshan Lake Materials Laboratory, Dongguan, Guangdong 523808, China

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Abstract

We introduce $\texttt{Yao}$, an extensible, efficient open-source framework for quantum algorithm design. $\texttt{Yao}$ features generic and differentiable programming of quantum circuits. It achieves state-of-the-art performance in simulating small to intermediate-sized quantum circuits that are relevant to near-term applications. We introduce the design principles and critical techniques behind $\texttt{Yao}$. These include the quantum block intermediate representation of quantum circuits, a builtin automatic differentiation engine optimized for reversible computing, and batched quantum registers with GPU acceleration. The extensibility and efficiency of $\texttt{Yao}$ help boost innovation in quantum algorithm design.

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The above citations are from Crossref's cited-by service (last updated successfully 2026-07-15 06:23:52) and SAO/NASA ADS (last updated successfully 2026-07-14 16:35:27). The list may be incomplete as not all publishers provide suitable and complete citation data.

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