Prof. Kihwan Kim's Group Has Made Progress in Trapped-ion Quantum Information Engine
2025/10/10
Information engines produce mechanical work through measurement and adaptive control. For information engines, the principal challenge lies in how to store the generated work to the external load. 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 an information-to-ergotropy conversion efficiency approaching 67% of the theoretical limit at the optimal temperature, along with a maximum information-to-work conversion efficiency of 70%. 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.
Paper link: https://journals.aps.org/prl/abstract/10.1103/g45c-ssfx
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