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We consider the asymmetric formulation of quantum hypothesis testing, where two quantum hypotheses have different associated costs. In this problem, the aim is to minimize the probability of false negatives and the optimal performance is…

Quantum Physics · Physics 2015-09-04 Gaetana Spedalieri , Samuel L. Braunstein

We study quantum hypothesis testing between orthogonal states under restricted local measurements in the many-copy scenario. For testing arbitrary multipartite entangled pure state against its orthogonal complement state via the local…

Quantum Physics · Physics 2024-09-25 Hao-Chung Cheng , Andreas Winter , Nengkun Yu

We consider the problem of unambiguous (error-free) discrimination of N linearly independent pure quantum states with prior probabilities, where the goal is to find a measurement that maximizes the average probability of success. We derive…

Quantum Physics · Physics 2015-06-19 Somshubhro Bandyopadhyay

In the simple quantum hypothesis testing problem, upper bound with asymmetric setting is shown by using a quite useful inequality by Audenaert et al, quant-ph/0610027, which was originally invented for symmetric setting. Using this upper…

Quantum Physics · Physics 2009-11-13 Masahito Hayashi

Determining the presence of a potential optical source in the interest region is important for an imaging system and can be achieved by using hypothesis testing. The previous studies assume that the potential source is completely…

Quantum Physics · Physics 2024-10-23 Jian-Dong Zhang , Kexin Zhang , Lili Hou , Shuai Wang

Finding quantitative aspects of quantum phenomena which cannot be explained by any classical model has foundational importance for understanding the boundary between classical and quantum theory. It also has practical significance for…

Quantum Physics · Physics 2018-02-06 David Schmid , Robert W. Spekkens

One of the most fundamental results in quantum information theory is that no measurement can perfectly discriminate between non-orthogonal quantum states. In this work, we investigate quantum advantages for discrimination tasks over…

Quantum Physics · Physics 2022-09-20 Kieran Flatt , Hanwool Lee , Carles Roch i Carceller , Jonatan Bohr Brask , Joonwoo Bae

In this paper, we develop a general approach for probabilistic estimation and optimization. An explicit formula and a computational approach are established for controlling the reliability of probabilistic estimation based on a mixed…

Statistics Theory · Mathematics 2012-12-06 Xinjia Chen

By combining the Minkowski inequality and the quantum Chernoff bound, we derive easy-to-compute upper bounds for the error probability affecting the optimal discrimination of Gaussian states. In particular, these bounds are useful when the…

Quantum Physics · Physics 2008-07-27 Stefano Pirandola , Seth Lloyd

Quantum key distribution (QKD) achieves information-theoretic security, without relying on computational assumptions, by distributing quantum states. To establish secret bits, two honest parties exploit key distillation protocols over…

Quantum Physics · Physics 2026-02-06 Rutvij Bhavsar , Junguk Moon , Joonwoo Bae

One of quantum theory's salient features is its apparent indeterminism, i.e. measurement outcomes are typically probabilistic. We formally define and address whether this uncertainty is unavoidable or whether post-quantum theories can offer…

Quantum Physics · Physics 2024-11-15 Johannes Fankhauser

We study an optimum measurement for quantum state discrimination, which maximizes the probability of correct results when the probability of inconclusive results is fixed at a given value. The measurement describes minimum-error…

Quantum Physics · Physics 2012-09-26 Ulrike Herzog

We consider the problem of testing multiple quantum hypotheses $\{\rho_1^{\otimes n},\ldots,\rho_r^{\otimes n}\}$, where an arbitrary prior distribution is given and each of the $r$ hypotheses is $n$ copies of a quantum state. It is known…

Quantum Physics · Physics 2016-07-20 Ke Li

Recently many simple principles have been proposed that can explain quantum limitations on possible sets of experimental probabilities in nonlocality and contextuality experiments. However, few implications between these principles are…

Quantum Physics · Physics 2015-06-10 Joe Henson

This paper investigates symmetric composite binary quantum hypothesis testing (QHT), where the goal is to determine which of two uncertainty sets contains an unknown quantum state. While asymptotic error exponents for this problem are…

Quantum Physics · Physics 2026-04-13 Jacob Paul Simpson , Efstratios Palias , Sharu Theresa Jose

Quantum state discrimination is a fundamental task that is meaningful in quantum information theory. In this manuscript, we consider a revised unambiguous discrimination of quantum resources. First, we present an upper bound of the success…

Quantum Physics · Physics 2024-10-08 Xian Shi

We extend the concept of probabilistic unambiguous discrimination of quantum states to quantum state estimation. We consider a scenario where the measurement device can output either an estimate of the unknown input state or an inconclusive…

Quantum Physics · Physics 2009-11-13 Jaromir Fiurasek

We study the discrimination of N mixed quantum states in an optimal measurement that maximizes the probability of correct results while the probability of inconclusive results is fixed at a given value. After considering the discrimination…

Quantum Physics · Physics 2015-06-11 Ulrike Herzog

Recall the classical hypothesis testing setting with two convex sets of probability distributions P and Q. One receives either n i.i.d. samples from a distribution p in P or from a distribution q in Q and wants to decide from which set the…

Information Theory · Computer Science 2020-07-20 Fernando G. S. L. Brandao , Aram W. Harrow , James R. Lee , Yuval Peres

We investigate the nonparametric, composite hypothesis testing problem for arbitrary unknown distributions in the asymptotic regime where both the sample size and the number of hypotheses grow exponentially large. Such asymptotic analysis…

Information Theory · Computer Science 2019-01-30 Qunwei Li , Tiexing Wang , Donald J. Bucci , Yingbin Liang , Biao Chen , Pramod K. Varshney