Wen-Han Png

Drive-Through Quantum Gate: Non-Stop Entangling a Mobile Ion Qubit with a Stationary One

Ting Hsu [1,2,5], Wen-Han Png [3], Kuan-Ting Lin [5], Ming-Shien Chang [4], Guin-Dar Lin [1,2,5]

Abstract

Towards the scalable realization of a quantum computer, a quantum charge-coupled device (QCCD) based on ion shuttling has been considered a promising approach. However, the processes of detaching an ion from an array, reintegrating it, and driving non-uniform motion introduce severe heating, requiring significant time and laser power for re-cooling and stabilization. To mitigate these challenges, we propose a novel entangling scheme between a stationary ion qubit and a continuously transported mobile ion, which remains in uniform motion and minimizes motional heating. We theoretically demonstrate a gate error on the order of 0.01%, within reach of current technology. This approach enables resource-efficient quantum operations and facilitates long-distance entanglement distribution, where stationary trapped-ion arrays serve as memory units and mobile ions act as communication qubits passing beside them. Our results pave the way for an alternative trapped-ion architecture beyond the QCCD paradigm.

Petz recovery maps of single-qubit decoherence channels in an ion trap quantum processor

Wen-Han Png [1], Valerio Scarani [1,2]

Abstract

The Petz recovery map provides a near-optimal reversal of quantum noise, yet proposals for its implementation are only recent. We propose a physical realization of the exact state-specific Petz map in an ion trap for qubit decoherence channels. Our circuit constructions require at most $1 (2)$ ancilla qubits and $3 (20)$ CNOT gates for channels with Kraus rank $2 (>2)$. We analyze typical ion trap errors and construct corresponding Petz maps, simulating their performance under realistic noise modeled by residual spin-motion coupling. Quantum circuits are provided for depolarizing, dephasing, and amplitude damping channels. Focusing on single-shot recovery, suited for present-day devices, we also quantify the precision of prior knowledge required to achieve a recovery error below 0.01 across varying decoherence levels and state purities.