论文标题
估计器的效率局部渐近量子统计模型
Efficiency of estimators for locally asymptotically normal quantum statistical models
论文作者
论文摘要
我们在这里为局部渐近正常量子统计模型建立了渐近表示定理。该定理使我们能够研究量子估计值的渐近效率，例如量子规则估计器和量子最小值估计器，从而导致i.i.d. i.i.d.假设。该公式补充了上一篇论文[Fujiwara and Yamagata，Bernoulli 26（2020）2105-2141]中量子相邻的理论，为弱量子局部渐近正态性理论提供了坚实的基础。
We herein establish an asymptotic representation theorem for locally asymptotically normal quantum statistical models. This theorem enables us to study the asymptotic efficiency of quantum estimators such as quantum regular estimators and quantum minimax estimators, leading to a universal tight lower bound beyond the i.i.d. assumption. This formulation complements the theory of quantum contiguity developed in the previous paper [Fujiwara and Yamagata, Bernoulli 26 (2020) 2105-2141], providing a solid foundation of the theory of weak quantum local asymptotic normality.
