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It is a central fact in quantum mechanics that non-orthogonal states cannot be distinguished perfectly. This property ensures the security of quantum key distribution. It is therefore an important task in quantum communication to design and…

Quantum Physics · Physics 2023-11-27 Lorcan O. Conlon , Falk Eilenberger , Ping Koy Lam , Syed M. Assad

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 Physics · Physics 2024-11-14 Akio Fujiwara , Koichi Yamagata

We investigate the optimal estimation of quantum expectation value of a physical observable, which minimizes a mean error with respect to general measure of deviation, when a finite number of copies of a pure state are prepared. If pure…

Quantum Physics · Physics 2007-05-23 Minoru Horibe , Akihisa Hayashi , Takaaki Hashimoto

We give bounds on the average fidelity achievable by any quantum state estimator, which is arguably the most prominently used figure of merit in quantum state tomography. Moreover, these bounds can be computed online---that is, while the…

Quantum Physics · Physics 2015-12-16 Richard Kueng , Christopher Ferrie

In a unified viewpoint in quantum channel estimation, we compare the Cramer-Rao and the mini-max approaches, which gives the Bayesian bound in the group covariant model. For this purpose, we introduce the local asymptotic mini-max bound,…

Quantum Physics · Physics 2011-06-24 Masahito Hayashi

We consider multipartite quantum state discrimination and show that the minimum-error discrimination by separable measurements is closely related to the concept of entanglement witness. Based on the properties of entanglement witness, we…

Quantum Physics · Physics 2023-04-25 Donghoon Ha , Jeong San Kim

We consider the problem of estimating the predictive density of future observations from a non-parametric regression model. The density estimators are evaluated under Kullback--Leibler divergence and our focus is on establishing the exact…

Statistics Theory · Mathematics 2010-10-12 Xinyi Xu , Feng Liang

We obtain the optimal Bayesian minimax rate for the unconstrained large covariance matrix of multivariate normal sample with mean zero, when both the sample size, n, and the dimension, p, of the covariance matrix tend to infinity.…

Statistics Theory · Mathematics 2017-12-04 Kyoungjae Lee , Jaeyong Lee

We undertake a detailed study of the performance of maximum likelihood (ML) estimators of the density matrix of finite-dimensional quantum systems, in order to interrogate generic properties of frequentist quantum state estimation. Existing…

Quantum Physics · Physics 2011-11-16 Raj Chakrabarti , Anisha Ghosh

Predicting the outcomes of quantum measurements is a cornerstone of quantum information theory and a key resource for quantum technologies. Here, we introduce a comprehensive framework for quantifying the predictability of measurements on a…

Quantum Physics · Physics 2026-01-28 Dennis I. Martínez-Moreno , Miguel Castillo-Celeita , Diego G. Bussandri

In this thesis we study the problem of unambiguously discriminating two mixed quantum states. We first present reduction theorems for optimal unambiguous discrimination of two generic density matrices. We show that this problem can be…

Quantum Physics · Physics 2007-05-23 Philippe Raynal

We consider the problem of estimating the state of a large but finite number $N$ of identical quantum systems. In the limit of large $N$ the problem simplifies. In particular the only relevant measure of the quality of the estimation is the…

Quantum Physics · Physics 2008-12-18 R. D. Gill , S. Massar

We investigate the unambiguous comparison of quantum states in a scenario that is more general than the one that was originally suggested by Barnett et al. First, we find the optimal solution for the comparison of two states taken from a…

Quantum Physics · Physics 2007-05-23 M. Kleinmann , H. Kampermann , D. Bruss

This paper describes a minimax state estimation approach for linear Differential-Algebraic Equations (DAE) with uncertain parameters. The approach addresses continuous-time DAE with non-stationary rectangular matrices and uncertain bounded…

Optimization and Control · Mathematics 2011-02-28 Sergiy Zhuk

In the framework of noisy quantum homodyne tomography with efficiency parameter $0 < \eta \leq 1$, we propose two estimators of a quantum state whose density matrix elements $\rho_{m,n}$ decrease like $e^{-B(m+n)^{r/ 2}}$, for fixed known…

Statistics Theory · Mathematics 2009-11-13 Jean-Marie Aubry , Cristina Butucea , Katia Méziani

A recurring problem in quantum mechanics is to estimate either the state of a quantum system or the measurement operator applied to it. If we wish to estimate both, then the difficulty is that the state and the measurement always appear…

Quantum Physics · Physics 2020-06-12 I. D. Moore , S. J. van Enk

In nonparametric statistics an optimality criterion for estimation procedures is provided by the minimax rate of convergence. However this classical point of view is subject to controversy as it requires to look for the worst behaviour…

Statistics Theory · Mathematics 2009-02-20 A. Fraysse

We introduce a procedure based on quantum expectation values of measurement observables to characterize quantum coherence. Our measure allows one to quantify coherence without having to perform tomography of the quantum state, and can be…

We propose and analyze quantum state estimation (tomography) using continuous quantum measurements with resource limitations, allowing the global state of many qubits to be constructed from only measuring a few. We give a proof-of-principle…

Quantum Physics · Physics 2020-04-13 Areeya Chantasri , Shengshi Pang , Teerawat Chalermpusitarak , Andrew N. Jordan

Estimating Kullback-Leibler divergence from identical and independently distributed samples is an important problem in various domains. One simple and effective estimator is based on the k nearest neighbor distances between these samples.…

Information Theory · Computer Science 2020-02-27 Puning Zhao , Lifeng Lai