YingYe Huang

Large-scale multimode entangling-gate synthesis in trapped-ion systems

YingYe Huang, Wentao Chen, Guoyu Zou, Xuan Fan, Jing-Ning Zhang, Kihwan Kim

Abstract

Trapped-ion systems have emerged as a leading platform for scalable quantum information processing owing to their high-fidelity operations and long-range entangling capabilities. As the number of ions in a trap increases, the growing density of collective motional modes makes the synthesis of multimode entangling gates increasingly challenging. Designing large-scale gates requires simultaneously realizing the desired spin-spin interactions, suppressing residual spin-motion entanglement, and limiting experimental control resources, leading to a high-dimensional non-convex optimization problem. Here we develop a numerical framework for multi-tone gate synthesis that directly searches for control fields satisfying these competing requirements. By employing an alternating-minimization strategy, the framework improves numerical stability and remains effective for large systems with many motional modes and target interactions. As representative demonstrations, we synthesize gates implementing all-to-all and nearest-neighbor interaction patterns in ion chains of up to N = 1000, using only global laser control. Across the parameter regimes explored here, the control resources required to maintain high-fidelity interactions do not exhibit rapid growth with system size. We extend the framework to individual addressing using a structured qLDPC target at N = 512 as an example. These results identify multimode gate synthesis as a viable route toward programmable interaction engineering in large-scale trapped-ion quantum processors.

A Single-Ion Information Engine for Charging Quantum Battery

Jialiang Zhang [1], Pengfei Wang [2], Wentao Chen [2], Zhengyang Cai [1], Mu Qiao [1], Riling Li [3], Yingye Huang [1], Haonan Tian [1], Henchao Tu [1], Kaifeng Cui [4], Leilei Yan [4], Junhua Zhang [5,6], Jingning Zhang [2], Manhong Yung [5,6], Kihwan Kim [1,2,7,8]

Abstract

Information engines produce mechanical work through measurement and adaptive control. For information engines, the principal challenge lies in how to store the generated work for subsequent utilization. Here, we report an experimental demonstration where quantized mechanical motion serves as a quantum battery and gets charged in repeated cycles by a single trapped-ion information engine. This is enabled by a key technological advancement in rapid state discrimination, allowing us to suppress measurement-induced disturbances. Consequently, we were able to obtain a charging efficiency over 50\% of the theoretical limit at the optimal temperature. The experimental results substantiate that this approach can render trapped ions a promising platform for microscopic information engines with potential applications in the future upon scaling up.