Architecting Scalable Trapped Ion Quantum Computers using Surface Codes

2025-10-27

AI Summary

Practical quantum error correction (QEC) in quantum charge-coupled device (QCCD) ion-trap systems suffers from low surface-code execution efficiency and poor hardware adaptability. Method: We propose a topology-aware compilation framework that jointly optimizes logical gate scheduling, trap capacity, ion connectivity, and electrode routing. Contribution/Results: Contrary to conventional design wisdom, our analysis reveals that miniaturized traps—containing only two ions—outperform large-scale traps in both logical clock speed and hardware resource efficiency. This paradigm shift enables an average 3.8× acceleration in surface-code logical clock rate. Moreover, the framework establishes scalable hardware design principles tailored to QCCD architectures. By bridging the orders-of-magnitude gap between near-term device fidelities (error rates ∼10⁻³–10⁻⁴) and the fault-tolerance threshold (<10⁻⁹), our approach provides a viable pathway toward scalable, hardware-efficient quantum error correction.

Technology Category

• Machine Learning: Hardware-aware ML
• Constraint Satisfaction and Optimization: Distributed CSP/Optimization
• Planning, Routing, and Scheduling: Optimization of Spatio-temporal Systems

Application Category

• Security and Privacy: Large-scale security measurements
• Economics, Online Markets and Human Computation: Incentives in network design for Web infrastructures and ecosystems
• Systems and Infrastructure for Web, Mobile and WoT: Sustainability and carbon-aware systems for Web, mobile, and WoT

Abstract

Trapped ion (TI) qubits are a leading quantum computing platform. Current TI systems have less than 60 qubits, but a modular architecture known as the Quantum Charge-Coupled Device (QCCD) is a promising path to scale up devices. There is a large gap between the error rates of near-term systems ($10^{-3}$ to $10^{-4}$) and the requirements of practical applications (below $10^{-9}$). To bridge this gap, we require Quantum Error Correction (QEC) to build emph{logical qubits} that are composed of multiple physical qubits. While logical qubits have been demonstrated on TI qubits, these demonstrations are restricted to small codes and systems. There is no clarity on how QCCD systems should be designed to implement practical-scale QEC. This paper studies how surface codes, a standard QEC scheme, can be implemented efficiently on QCCD-based systems. To examine how architectural parameters of a QCCD system can be tuned for surface codes, we develop a near-optimal topology-aware compilation method that outperforms existing QCCD compilers by an average of 3.8X in terms of logical clock speed. We use this compiler to examine how hardware trap capacity, connectivity and electrode wiring choices can be optimised for surface code implementation. In particular, we demonstrate that small traps of two ions are surprisingly ideal from both a performance-optimal and hardware-efficiency standpoint. This result runs counter to prior intuition that larger traps (20-30 ions) would be preferable, and has the potential to inform design choices for upcoming systems.

Problem

• Implementing surface code quantum error correction on QCCD trapped ion systems
• Bridging the gap between current error rates and practical application requirements
• Optimizing QCCD architectural parameters for efficient surface code implementation

Innovation

• Using surface codes for scalable trapped ion quantum computing
• Developing topology-aware compilation method for QCCD systems
• Optimizing hardware with small two-ion traps for efficiency