Efficient Implementation of Arbitrary Two-Qubit Gates via Unified Control
Abstract
The native gate set is fundamental to the performance of quantum devices, as it governs the accuracy of basic quantum operations and dictates the complexity of implementing quantum algorithms. Traditional approaches to extending gate sets often require accessing multiple transitions within an extended Hilbert space, leading to increased control complexity while offering only a limited set of gates. Here, we experimentally demonstrate a unified and highly versatile gate scheme capable of natively generating arbitrary two-qubit gates using only exchange interaction and qubit driving on a superconducting quantum processor, achieving maximum expressivity. Using a state-of-the-art transmon-coupler-transmon architecture, we achieve high fidelities averaging across a wide range of commonly used two-qubit unitaries. This outstanding performance, combined with reduced complexity, enables precise multipartite entangled state preparation, as demonstrated. To further enhance its applicability, we also show the high-fidelity realization of the unique B gate, which efficiently synthesizes the entire family of two-qubit gates. Our results highlight that fully exploiting the capabilities of a single interaction can yield a comprehensive and highly accurate gate set. With maximum expressivity, gate-time optimality, demonstrated high fidelity, and easy adaptability to other quantum platforms, our unified control scheme paves the way for optimal performance in quantum devices, offering exciting prospects for advancing quantum hardware and algorithm development.
Cite
@article{arxiv.2502.03612,
title = {Efficient Implementation of Arbitrary Two-Qubit Gates via Unified Control},
author = {Zhen Chen and Weiyang Liu and Yanjun Ma and Weijie Sun and Ruixia Wang and He Wang and Huikai Xu and Guangming Xue and Haisheng Yan and Zhen Yang and Jiayu Ding and Yang Gao and Feiyu Li and Yujia Zhang and Zikang Zhang and Yirong Jin and Haifeng Yu and Jianxin Chen and Fei Yan},
journal= {arXiv preprint arXiv:2502.03612},
year = {2025}
}