arXivDaily arXiv每日学术速递 周一至周五更新
arXiv 1012.3525quant-ph
收藏

多拷贝状态歧视：全球思考，局部行动

Multiple-copy state discrimination: Thinking globally, acting locally

B. L. Higgins, A. C. Doherty, S. D. Bartlett, G. J. Pryde, H. M. Wiseman

备注：
11 pages, 14 figures
发表信息：
Phys. Rev. A 83, 052314 (2011)
阅读 PDF
arXiv 页面 ↗HTML 原文 ↗

摘要：

我们从理论上研究了区分两个非正交量子态的方案。我们考虑了一些国家歧视计划，适用于非正交，混合状态的量子比特。特别是，我们研究的差异，局部和全局优化的局部测量，使获得一个错误的结果的概率，在制度的有限数量的副本$N$，并在渐近极限为$N \rightarrow \infty$。考虑了五种方案：在所有副本上的最佳集体测量、在固定单量子比特测量基础上的局部最佳局部测量、全局最佳固定局部测量、局部最佳自适应局部测量和全局最佳自适应局部测量。这里，自适应测量是测量基础可以依赖于先前测量结果的那些测量。对于这些测量方案中的每一个，我们确定的概率错误（有限$N$）和缩放的渐近极限中的这个错误。在渐近极限，自适应计划没有优势的最佳固定的本地计划，除了小于2%的混合状态，最天真的计划（本地最佳固定的本地测量）是任何非集体计划一样好。对于有限的$N$，然而，最复杂的本地计划（全球最佳自适应本地测量）是优于任何其他非集体计划，任何程度的混合。

英文摘要：

We theoretically investigate schemes to discriminate between two nonorthogonal quantum states given multiple copies. We consider a number of state discrimination schemes as applied to nonorthogonal, mixed states of a qubit. In particular, we examine the difference that local and global optimization of local measurements makes to the probability of obtaining an erroneous result, in the regime of finite numbers of copies $N$, and in the asymptotic limit as $N \rightarrow \infty$. Five schemes are considered: optimal collective measurements over all copies, locally optimal local measurements in a fixed single-qubit measurement basis, globally optimal fixed local measurements, locally optimal adaptive local measurements, and globally optimal adaptive local measurements. Here, adaptive measurements are those for which the measurement basis can depend on prior measurement results. For each of these measurement schemes we determine the probability of error (for finite $N$) and scaling of this error in the asymptotic limit. In the asymptotic limit, adaptive schemes have no advantage over the optimal fixed local scheme, and except for states with less than 2% mixture, the most naive scheme (locally optimal fixed local measurements) is as good as any noncollective scheme. For finite $N$, however, the most sophisticated local scheme (globally optimal adaptive local measurements) is better than any other noncollective scheme, for any degree of mixture.

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。

↑