--- title: Entanglement-enhanced learning of quantum processes at scale description: A research paper introducing error-mitigated entanglement-enhanced learning for characterizing quantum noise processes at scale. The authors demonstrate that... canonical: https://daily.dev/posts/entanglement-enhanced-learning-of-quantum-processes-at-scale-r3occgydg twitter:card: summary_large_image twitter:site: @dailydotdev og:type: website og:site_name: daily.dev og:title: Entanglement-enhanced learning of quantum processes at scale | daily.dev og:description: A research paper introducing error-mitigated entanglement-enhanced learning for characterizing quantum noise processes at scale. The authors demonstrate that... og:url: https://daily.dev/posts/entanglement-enhanced-learning-of-quantum-processes-at-scale-r3occgydg og:image: https://api.daily.dev/og/posts/R3occGYdG.png og:image:alt: Entanglement-enhanced learning of quantum processes at scale og:image:width: 1200 og:image:height: 630 og:locale: en --- > ## Documentation Index > Fetch the complete documentation index at: https://daily.dev/llms.txt > Use this file to discover all available pages before exploring further. # Entanglement-enhanced learning of quantum processes at scale **[Nature](https://daily.dev/sources/nature)** · 3 min read · 0 upvotes · 0 comments ## Summary A research paper introducing error-mitigated entanglement-enhanced learning for characterizing quantum noise processes at scale. The authors demonstrate that noisy quantum memory can still provide a learning advantage over entanglement-free approaches, with an experimental overhead of 1.33 ± 0.05 per qubit — below the no-entanglement lower bound of 2. Experiments were conducted on a superconducting processor using up to 64 qubits for hypothesis testing and up to 16 qubits for learning intrinsic noise in parallel-gate layers. ## Full article daily.dev links to this article rather than hosting it. 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