A new review paper by Hoong Chuin Lau examines the intersection of AI and quantum computing for combinatorial optimization, categorizing research into three paradigms: AI-for-Quantum Optimization (AI-for-QO), Quantum-for-AI (Q-for-AI), and AI-Quantum Co-Optimization. The study, which analyzed 119 papers, concludes that AI-assisted quantum optimization shows promise, while quantum-assisted AI models are…
Researchers at RIKEN and collaborators have achieved high-fidelity simultaneous control of five silicon spin qubits, maintaining over 99.9% accuracy. They overcame crosstalk caused by AC-Stark shifts through a new calibration protocol, enabling the use of a single microwave control line. This breakthrough meets the fault-tolerant threshold for quantum error correction…
Researchers from Harvard, Anthropic, and QuEra Computing developed an AI framework that uses Large Language Models (LLMs) to discover and optimize fault-tolerant quantum circuits. This framework significantly reduces the resource costs of core computational primitives, achieving up to 9,100x lower costs compared to hand-crafted baselines. The LLMs achieved this by…
