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University of Waterloo
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Entangling $t$ quantum copies during measurement improves state tomography efficiency by at most a factor of $\sqrt{t}$, showing that reaching optimal collective sample rates strictly requires entangling $\Omega(r^2)$ samples regardless of classical adaptivity.
Current LLM agents are woefully inadequate for real-world clinical tasks, achieving only 46% success on a new benchmark that demands long-horizon reasoning and verifiable execution within electronic health records.
