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Shuttling Compiler for Trapped-Ion Quantum Computers Based on Large Language Models
[Submitted on 19 Dec 2025 (v1), last revised 12 Jun 2026 (this v · 2026-06-15 · via cs.LG updates on arXiv.org

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Abstract:We present the first shuttling compiler based on large language models (LLMs) for trapped-ion quantum computers, where qubits are shuttled between segments for gate execution and qubit storage. We fine-tune pre-trained LLMs on examples from linear and branched one-dimensional shuttling architectures. Thus, we obtain a layout-independent compilation strategy that learns the required shuttling operations directly from data. Using benchmark circuits with up to 16 qubits, such fine-tuned LLMs can now generate valid schedules for shuttling architectures. Notably, we also obtain a valid schedule for a previously unseen four-way junction layout. This demonstrates that trained LLMs can generalize to layouts not encountered during training. For various architectures, LLM-based schedules improve upon state-of-the-art baseline compiler results, reducing the shuttling effort by up to 15%.

Submission history

From: Fabian Kreppel [view email]
[v1] Fri, 19 Dec 2025 19:29:09 UTC (329 KB)
[v2] Tue, 20 Jan 2026 12:52:08 UTC (324 KB)
[v3] Fri, 12 Jun 2026 16:29:39 UTC (324 KB)

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