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arXiv 2501.09712quant-phcs.ITmath-phmath.ITmath.MP
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量子假设排除的逆界:一种散度半径方法

Converse bounds for quantum hypothesis exclusion: A divergence-radius approach

Cornell University(康奈尔大学);Indian Institute of Technology (Indian School of Mines)(印度理工学院(印度矿业学院));HUN-REN Alfréd Rényi Institute of Mathematics(匈牙利研究与教育网络阿尔弗雷德·雷尼数学研究所);Budapest University of Technology and Economics(布达佩斯技术与经济大学)

Kaiyuan Ji, Hemant K. Mishra, Milán Mosonyi, Mark M. Wilde

AI总结:

本文通过散度半径方法,为量子态和量子信道排除任务的渐近错误指数提供了另一种证明,得到了与先前工作相同的上界。

摘要:

假设排除是一项信息论任务,实验者旨在从有限个已知候选假设中排除一个错误假设,当且仅当被排除的假设是真实情况时发生错误。对于量子态排除和量子信道排除任务——其中假设分别由量子态和量子信道表示——当前作者在最近的工作[Ji et al., arXiv:2407.13728 (2024)]中建立了渐近错误指数的可计算上界,其推导基于非渐近分析。在本篇作为先前工作姊妹篇的论文中,我们为量子态和信道排除的渐近错误指数提供了相同的上界,但使用了与先前工作不同的概念性方法。具体地,我们将非对称二元假设检验的强逆结果应用于区分任意一个“虚拟”假设与每个相关候选假设。通过几何启发式论证,这导致了以散度半径表示的所需上界。

英文摘要:

Hypothesis exclusion is an information-theoretic task in which an experimenter aims at ruling out a false hypothesis from a finite set of known candidates, and an error occurs if and only if the hypothesis being ruled out is the ground truth. For the tasks of quantum state exclusion and quantum channel exclusion -- where hypotheses are represented by quantum states and quantum channels, respectively -- efficiently computable upper bounds on the asymptotic error exponents were established in a recent work of the current authors [Ji et al., arXiv:2407.13728 (2024)], where the derivation was based on nonasymptotic analysis. In this companion paper of our previous work, we provide alternative proofs for the same upper bounds on the asymptotic error exponents of quantum state and channel exclusion, but using a conceptually different approach from the one adopted in the previous work. Specifically, we apply strong converse results for asymmetric binary hypothesis testing to distinguishing an arbitrary ``dummy'' hypothesis from each of the concerned candidates. This leads to the desired upper bounds in terms of divergence radii via a geometrically inspired argument.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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