English(EN) Aligning Quantum Operators with Large Language Models

LLM通过潜在空间映射学会推理量子算子

作者 PulseAugur 编辑部 · [2 个来源] · 2026-06-11 00:00

研究人员开发了一种方法，通过将酉矩阵映射到LLM的潜在空间，使大型语言模型（LLM）能够理解和推理量子算子。这种方法实现了量子和语言输入的统一建模，在Clifford+T电路合成方面取得了有竞争力的结果。该方法还支持语言条件合成，能够通过自然语言指定门约束，为量子感知基础模型铺平了道路。 AI

影响使LLM能够解释量子操作，可能加速量子编译和算法发现。

排序理由该集群描述了一篇在arXiv上发表的研究论文，详细介绍了一种将量子算子与大型语言模型对齐的新颖方法。

AI 生成摘要 · Google Gemini · 来自 2 个来源。我们如何撰写摘要 →

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arXiv cs.AI TIER_1 English(EN) · Rogerio Feris, Yunchao Liu, Pengyuan Li, Hang Hua, David Kremer · 2026-06-15 04:00

Aligning Quantum Operators with Large Language Models

arXiv:2606.13811v1 Announce Type: cross Abstract: Can Large Language Models (LLMs) understand and reason about quantum operators? Despite their remarkable capabilities in mathematics and symbolic reasoning, LLMs remain inherently blind to quantum representations such as unitary m…
Hugging Face Daily Papers TIER_1 English(EN) · 2026-06-11 00:00

Aligning Quantum Operators with Large Language Models

Large language models can be adapted to understand quantum operators by mapping unitary matrices into their latent space, enabling quantum circuit synthesis and language-conditioned gate constraint specification.