Problem
Research questions and friction points this paper is trying to address.
strong converse exponent
quantum state merging
entanglement cost
conditional Rényi entropies
Strong Converse Exponent of Quantum State Merging
🤖 AI Summary
本文解决了量子态合并的纠缠成本强逆向指数问题，通过使用优化的α-z条件Rényi熵方法来表征，并探讨了其与部分平滑条件下最小熵的关系。
📝 Abstract
We determine the strong converse exponent for the entanglement cost of quantum state merging, showing that it is characterized by the optimized $α$-$z$ conditional Rényi entropies with $z=α/2\in[1/2,1]$. This contrasts with the sandwiched conditional Rényi entropies that typically govern strong converse exponents in quantum information theory. As a consequence, we derive the strong converse exponent of the partially smoothed conditional min-entropy in purified distance. This exponent is governed by club-sandwiched conditional entropies, whereas global smoothing leads to a sandwiched expression.
Innovation
Methods, ideas, or system contributions that make the work stand out.
optimized α-z conditional Rényi entropies
strong converse exponent
quantum state merging
partially smoothed conditional min-entropy
purified distance
🔎 Similar Papers
No similar papers found.
💼 Related Jobs
No related jobs found.
