Modular trapped-ion (TI) architectures offer a scalable quantum computing (QC) platform, with native transport behaviors that closely resemble the Single Instruction Multiple Data (SIMD) paradigm. We present FluxTrap, a SIMD-aware compiler framework that establishes a hardware-software co-design interface for TI systems. FluxTrap introduces a novel abstraction that unifies SIMD-style instructions -- including segmented intra-trap shift SIMD (S3) and global junction transfer SIMD (JT-SIMD) operations -- with a SIMD-enriched architectural graph, capturing key features such as transport synchronization, gate-zone locality, and topological constraints. It applies two passes -- SIMD aggregation and scheduling -- to coordinate grouped ion transport and gate execution within architectural constraints. On NISQ benchmarks, FluxTrap reduces execution time by up to 3.82× and improves fidelity by several orders of magnitude. It also scales to fault-tolerant workloads under diverse hardware configurations, providing feedback for future TI hardware design.
Cite
@article{arxiv.2504.17886,
title = {TrapSIMD: SIMD-Aware Compiler Optimization for 2D Trapped-Ion Quantum Machines},
author = {Jixuan Ruan and Hezi Zhang and Xiang Fang and Ang Li and Wesley C. Campbell and Eric Hudson and David Hayes and Hartmut Haeffner and Travis Humble and Jens Palsberg and Yufei Ding},
journal= {arXiv preprint arXiv:2504.17886},
year = {2025}
}