Shuttling Compiler for Trapped-Ion Quantum Computers Based on Fine-Tuned Large Language Models

The paper reports on shuttling compilers for trapped‑ion quantum computers that are built using five large language models (LLMs) fine‑tuned on hand‑crafted shuttling schedules for linear and branched one‑dimensional trap architectures. For circuits up to 16 qubits, the fine‑tuned LLMs produce valid schedules on the training architectures, and in 12% of compilations the best of ten runs achieves up to 21% fewer operations than heuristic baselines after rule‑based post‑processing. A single run of one LLM also generates a valid schedule for a previously unseen four‑way branched architecture, providing preliminary evidence of cross‑architecture generalization, though no LLM succeeded on two other unseen architectures.

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• llms
• fine-tuning