论文标题
多参数估计超出量子渔民信息
Multi-parameter estimation beyond Quantum Fisher Information
论文作者
论文摘要
这篇评论旨在收集最相关的量子多参数估计方法，这些估计方法超出了量子Fisher信息概念的直接使用。我们详细讨论了HolevoCramér-Rao Bound，量子局部渐近正态性方法以及贝叶斯方法。尽管该领域的基本概念已在四十多年前提出，但最近出现了许多重要的结果。此外，由于实用量子计量的建议和实现的进步，该领域最近引起了人们的关注，这些建议通常涉及同时估算多个参数。由于这些主题是在文献中传播的，并且经常以一种非常正式的数学语言服务，因此本评论的主要目标之一是提供一项很大程度上具有独立的作品，使读者能够遵循大多数派生，并使用一组涉及Qubit和Gaussian Shift Models的简单典型示例对不同概念之间的相互关系进行直观的理解。
This review aims at gathering the most relevant quantum multi-parameter estimation methods that go beyond the direct use of the Quantum Fisher Information concept. We discuss in detail the Holevo Cramér-Rao bound, the Quantum Local Asymptotic Normality approach as well as Bayesian methods. Even though the fundamental concepts in the field have been laid out more than forty years ago, a number of important results have appeared much more recently. Moreover, the field drew increased attention recently thanks to advances in practical quantum metrology proposals and implementations that often involve estimation of multiple parameters simultaneously. Since these topics are spread in the literature and often served in a very formal mathematical language, one of the main goals of this review is to provide a largely self-contained work that allows the reader to follow most of the derivations and get an intuitive understanding of the interrelations between different concepts using a set of simple yet representative examples involving qubit and Gaussian shift models.
