具有多个程序和数据拷贝的可编程未知量子态鉴别器：Jordan基方法
Programmable unknown quantum-state discriminators with multiple copies of program and data: A Jordan basis approach
摘要：
对任意一对未知量子态的鉴别是由处理三部分输入的设备来执行的：我们要鉴别的一对未知态的副本分别存储在两个程序系统中，而数据的副本则存储在第三个系统中，该数据被保证是未知态之一。我们研究了这样的可编程器件的效率与输入准备与$n$和$m$副本的未知量子位用作程序和数据，分别。通过找到一个对称的平均输入，我们应用约旦基方法来获得他们的最佳明确的歧视和最小误差的歧视计划。最优解的平均输入状态的先验概率的依赖性也被证明。
英文摘要：
The discrimination of any pair of unknown quantum states is performed by devices processing three parts of inputs: copies of the pair of unknown states we want to discriminate are respectively stored in two program systems and copies of data, which is guaranteed to be one of the unknown states, in a third system. We study the efficiency of such programmable devices with the inputs prepared with $n$ and $m$ copies of unknown qubits used as programs and data, respectively. By finding a symmetry in the average inputs, we apply the Jordan basis method to derive their optimal unambiguous discrimination and the minimum-error discrimination schemes. The dependence of the optimal solutions on the a prior probabilities of the mean input states is also demonstrated.
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