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Let Alice and Bob be able to make local quantum measurements and communicate classically. The set of mathematically consistent joint probability assignments (``states'') for such measurements is properly larger than the set of…

Quantum Physics · Physics 2007-05-23 Howard Barnum , Christopher A. Fuchs , Joseph M. Renes , Alexander Wilce

Quantum state verification provides an efficient approach to characterize the reliability of quantum devices for generating certain target states. The figure of merit of a specific strategy is the estimated infidelity $\epsilon$ of the…

We present Bell-type tests of nonclassicality and non-Gaussianity for single-mode fields employing a generalized quasiprobability function. Our nonclassicality tests are based on the observation that two orthogonal quadratures in phase…

Quantum Physics · Physics 2016-01-05 Jiyong Park , Hyunchul Nha

Our purpose, is to put forward a change in the paradigm of testing by generalizing a very natural idea exposed by Morris DeGroot (1975) aiming to an approach that is attractive to all schools of statistics, in a procedure better suited for…

Methodology · Statistics 2013-10-02 Luis Pericchi , Carlos Pereira

We investigate the statistical task of closeness (or equivalence) testing for multidimensional distributions. Specifically, given sample access to two unknown distributions $\mathbf p, \mathbf q$ on $\mathbb R^d$, we want to distinguish…

Data Structures and Algorithms · Computer Science 2023-11-23 Ilias Diakonikolas , Daniel M. Kane , Sihan Liu

Efficient verification of entangled states is crucial to many applications in quantum information processing. However, the effectiveness of standard quantum state verification (QSV) is based on the condition of independent and identical…

Quantum Physics · Physics 2025-06-13 Wen-Hao Zhang , Zihao Li , Gong-Chu Li , Xu-Song Hong , Huangjun Zhu , Geng Chen , Chuan-Feng Li , Guang-Can Guo

Universal hypothesis testing refers to the problem of deciding whether samples come from a nominal distribution or an unknown distribution that is different from the nominal distribution. Hoeffding's test, whose test statistic is equivalent…

Information Theory · Computer Science 2017-11-15 Pengfei Yang , Biao Chen

We study the problem of efficiently detecting Out-of-Distribution (OOD) samples at test time in supervised and unsupervised learning contexts. While ML models are typically trained under the assumption that training and test data stem from…

Machine Learning · Computer Science 2024-05-13 Alberto Caron , Chris Hicks , Vasilios Mavroudis

We study how to unambiguously identify a given quantum pure state with one of the two reference pure states when no classical knowledge on the reference states is given but a certain number of copies of each reference quantum state are…

Quantum Physics · Physics 2009-11-11 A. Hayashi , M. Horibe , T. Hashimoto

Given a finite-valued sample $X_1,...,X_n$ we wish to test whether it was generated by a stationary ergodic process belonging to a family $H_0$, or it was generated by a stationary ergodic process outside $H_0$. We require the Type I error…

Statistics Theory · Mathematics 2014-12-30 Daniil Ryabko

Given samples from an unknown distribution $p$, is it possible to distinguish whether $p$ belongs to some class of distributions $\mathcal{C}$ versus $p$ being far from every distribution in $\mathcal{C}$? This fundamental question has…

Data Structures and Algorithms · Computer Science 2015-12-09 Jayadev Acharya , Constantinos Daskalakis , Gautam Kamath

We revisit the problem of tolerant distribution testing. That is, given samples from an unknown distribution $p$ over $\{1, \dots, n\}$, is it $\varepsilon_1$-close to or $\varepsilon_2$-far from a reference distribution $q$ (in total…

Data Structures and Algorithms · Computer Science 2021-11-10 Clément L. Canonne , Ayush Jain , Gautam Kamath , Jerry Li

We introduce two novel non-parametric statistical hypothesis tests. The first test, called the relative test of dependency, enables us to determine whether one source variable is significantly more dependent on a first target variable or a…

Artificial Intelligence · Computer Science 2016-11-18 Wacha Bounliphone , Eugene Belilovsky , Arthur Tenenhaus , Ioannis Antonoglou , Arthur Gretton , Matthew B. Blashcko

Self-testing is a method to certify devices from the result of a Bell test. Although examples of noise tolerant self-testing are known, it is not clear how to deal efficiently with a finite number of experimental trials to certify the…

Quantum Physics · Physics 2021-03-03 Jean-Daniel Bancal , Kai Redeker , Pavel Sekatski , Wenjamin Rosenfeld , Nicolas Sangouard

Sampling algorithms play a pivotal role in probabilistic AI. However, verifying if a sampler program indeed samples from the claimed distribution is a notoriously hard problem. Provably correct testers like Barbarik, Teq, Flash, CubeProbe…

Data Structures and Algorithms · Computer Science 2025-12-09 Rishiraj Bhattacharyya , Sourav Chakraborty , Yash Pote , Uddalok Sarkar , Sayantan Sen

Hypothesis testing plays a central role in statistical inference, and is used in many settings where privacy concerns are paramount. This work answers a basic question about privately testing simple hypotheses: given two distributions $P$…

Data Structures and Algorithms · Computer Science 2019-04-04 Clément L. Canonne , Gautam Kamath , Audra McMillan , Adam Smith , Jonathan Ullman

We study the problem of communication over a compound quantum channel in the presence of entanglement. Classically such channels are modeled as a collection of conditional probability distributions wherein neither the sender nor the…

Quantum Physics · Physics 2019-03-19 Anurag Anshu , Rahul Jain , Naqueeb Ahmad Warsi

Consider a binary statistical hypothesis testing problem, where $n$ independent and identically distributed random variables $Z^n$ are either distributed according to the null hypothesis $P$ or the alternative hypothesis $Q$, and only $P$…

Information Theory · Computer Science 2024-04-15 K. V. Harsha , Jithin Ravi , Tobias Koch

We present a general framework for hypothesis testing on distributions of sets of individual examples. Sets may represent many common data sources such as groups of observations in time series, collections of words in text or a batch of…

Methodology · Statistics 2021-02-03 Alexis Bellot , Mihaela van der Schaar

Consider the problem of binary hypothesis testing. Given $Z$ coming from either $\mathbb P^{\otimes m}$ or $\mathbb Q^{\otimes m}$, to decide between the two with small probability of error it is sufficient, and in many cases necessary, to…

Statistics Theory · Mathematics 2024-03-11 Patrik Róbert Gerber , Yury Polyanskiy
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