Xue Shichuan, Wang Yizhi, Zhan Junwei, Wang Yaxuan, Zeng Ru, Ding Jiangfang, Shi Weixu, Liu Yong, Liu Yingwen, Huang Anqi, Huang Guangyao, Yu Chunlin, Wang Dongyang, Fu Xiang, Qiang Xiaogang, Xu Ping, Deng Mingtang, Yang Xuejun, Wu Junjie
Institute for Quantum Information & State Key Laboratory of High Performance Computing, College of Computer Science and Technology, National University of Defense Technology, Changsha 410073, China.
China Greatwall Research Institute, China Greatwall Technology Group CO., LTD., Shenzhen 518057, China.
Phys Rev Lett. 2022 Sep 23;129(13):133601. doi: 10.1103/PhysRevLett.129.133601.
Quantum process tomography is a pivotal technique in fully characterizing quantum dynamics. However, exponential scaling of the Hilbert space with the increasing system size extremely restrains its experimental implementations. Here, we put forward a more efficient, flexible, and error-mitigated method: variational entanglement-assisted quantum process tomography with arbitrary ancillary qubits. Numerically, we simulate up to eight-qubit quantum processes and show that this tomography with m ancillary qubits (0≤m≤n) alleviates the exponential costs on state preparation (from 4^{n} to 2^{n-m}), measurement settings (at least a 1 order of magnitude reduction), and data postprocessing (efficient and robust parameter optimization). Experimentally, we first demonstrate our method on a silicon photonic chip by rebuilding randomly generated one-qubit and two-qubit unitary quantum processes. Further using the error mitigation method, two-qubit quantum processes can be rebuilt with average gate fidelity enhanced from 92.38% to 95.56%. Our Letter provides an efficient and practical approach to process tomography on the noisy quantum computing platforms.
量子过程层析成像技术是全面表征量子动力学的关键技术。然而，随着系统规模的增加，希尔伯特空间的指数增长极大地限制了其实验实现。在此，我们提出了一种更高效、灵活且误差缓解的方法：具有任意辅助量子比特的变分纠缠辅助量子过程层析成像。在数值上，我们模拟了多达八个量子比特的量子过程，并表明这种具有m个辅助量子比特（0≤m≤n）的层析成像减轻了态制备（从4ⁿ降至2ⁿ⁻ᵐ）、测量设置（至少降低一个数量级）和数据后处理（高效且稳健的参数优化）方面的指数成本。在实验上，我们首先通过重建随机生成的单量子比特和双量子比特酉量子过程，在硅光子芯片上演示了我们的方法。进一步使用误差缓解方法，双量子比特量子过程可以被重建，平均门保真度从92.38%提高到95.56%。我们的论文为在有噪声的量子计算平台上进行过程层析成像提供了一种高效且实用的方法。
