2025/04/22 by Keyi Yin, Xiang Fang, Yin, Keyi +23 · 3 citations
Chemistry · Engineering · Neuroscience · #Electrochemical Analysis and Applications #Microfluidic and Capillary Electrophoresis Applications #Neuroscience and Neural Engineering
paper · pdf · doi:10.1145/3779212.3790177
Recent advances in quantum hardware and error correction have paved the way for early fault-tolerant (EFT) quantum computing. We propose iSwitch, a hybrid system architecture for trapped-ion quantum computers (TIQC) that exploits ultra-high-fidelity single-qubit gates and efficient logical CNOTs enabled by ion shuttling. iSwitch employs bare qubits for single-qubit operations and QEC-encoded logical qubits for two-qubit gates, avoiding full logical encoding, gate synthesis, and magic state distillation. To enable this selective encoding, we develop a low-noise conversion protocol between bare and logical qubits, a hybrid instruction set tailored to 2D TIQC layouts, and a compiler that minimizes conversion overhead and optimizes scheduling. Evaluations on variational quantum algorithm benchmarks show that iSwitch achieves comparable fidelity to conventional QEC methods, while reducing qubit and operation counts by roughly 33–50%, offering a practical, resource-efficient path toward EFT quantum computing on trapped-ion platforms.