Automated near-term quantum algorithm discovery for molecular ground states
Quantinuum；Hiverge
Fabian Finger, Frederic Rapp, Pranav Kalidindi, Kerry He, Kante Yin, Alexander Koziell-Pipe, David Zsolt Manrique, Gabriel Greene-Diniz, Stephen Clark, Hamza Fa… 展开作者
Fabian Finger, Frederic Rapp, Pranav Kalidindi, Kerry He, Kante Yin, Alexander Koziell-Pipe, David Zsolt Manrique, Gabriel Greene-Diniz, Stephen Clark, Hamza Fawzi, Bernardino Romera-Paredes, Alhussein Fawzi, Konstantinos Meichanetzidis
设计量子算法是一项复杂且反直觉的任务，因此成为AI驱动算法发现的理想候选。为此，我们采用Hive，一个用于程序合成的AI平台，利用大语言模型驱动高度分布的进化过程以发现新算法。我们聚焦于量子化学中的基态问题，并发现能够解决LiH、H2O和F2分子基态的高效量子启发式算法，同时在量子资源使用上显著优于现有近term量子算法。进一步，我们对发现的算法进行了可解释性研究，并识别出导致效率提升的关键功能。最后，我们在Quantinuum System Model H2量子计算机上对Hive发现的电路进行了基准测试，并确定了实现化学精度所需的最小系统要求。我们设想这种新的量子算法发现方法不仅适用于其他领域，也适用于设计容错量子计算机的算法。
英文摘要：
Designing quantum algorithms is a complex and counterintuitive task, making it an ideal candidate for AI-driven algorithm discovery. To this end, we employ the Hive, an AI platform for program synthesis, which utilises large language models to drive a highly distributed evolutionary process for discovering new algorithms. We focus on the ground state problem in quantum chemistry, and discover efficient quantum heuristic algorithms that solve it for molecules LiH, H2O, and F2 while exhibiting significant reductions in quantum resources relative to state-of-the-art near-term quantum algorithms. Further, we perform an interpretability study on the discovered algorithms and identify the key functions responsible for the efficiency gains. Finally, we benchmark the Hive-discovered circuits on the Quantinuum System Model H2 quantum computer and identify minimum system requirements for chemical precision. We envision that this novel approach to quantum algorithm discovery applies to other domains beyond chemistry, as well as to designing quantum algorithms for fault-tolerant quantum computers.
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International Centre for Theoretical Physics Asia-Pacific（国际理论物理中心亚太中心）；University of Chinese Academy of Sciences（中国科学院大学）；Taiji Laboratory for Gravitational Wave Universe（引力波宇宙Taiji实验室）；Tsinghua University（清华大学）
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Institute of Information Engineering, Chinese Academy of Sciences（中国科学院信息工程研究所）；School of Cyber Security, University of Chinese Academy of Sciences（中国科学院大学网络安全学院）
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University of Illinois Urbana-Champaign（伊利诺伊大学厄巴纳-香槟分校）；University of California Los Angeles（加利福尼亚大学洛杉矶分校）；California Institute of Technology（加州理工学院）；Harvard University（哈佛大学）
CAMO: An Agentic Framework for Automated Causal Discovery from Micro Behaviors to Macro Emergence in LLM Agent Simulations
College of Intelligence and Computing, Tianjin University（天津大学智能计算学院）；Tianjin Key Laboratory of Healthy Habitat and Smart Technology（天津健康人居环境与智能技术重点实验室）；Laboratory of Computation and Analytics of Complex Management Systems, Tianjin University（复杂管理系统计算与分析实验室）
esQueranto: Differentiable Structured Quantum Light for Automated Scientific Discovery
University of Tübingen（蒂宾根大学）；Feyer, Tübingen, Germany（Feyer）；Nexus for Quantum Technologies, University of Ottawa, Canada（渥太华大学量子技术中心）；Friedrich-Schiller-Universität Jena（耶拿弗里德里希·席勒大学）
