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This paper investigates Distributed Hypothesis testing (DHT), in which a source $\mathbf{X}$ is encoded given that side information $\mathbf{Y}$ is available at the decoder only. Based on the received coded data, the receiver aims to decide…

Information Theory · Computer Science 2023-05-12 Ismaila Salihou Adamou , Elsa Dupraz , Tad Matsumoto

In this letter, we consider multiple statistical classification problem where a sequence of n independent and identically distributed observations, that are generated by one of M discrete sources, need to be classified. The source…

Information Theory · Computer Science 2021-08-31 Hüseyin Afşer

We analyze hypotheses tests using classical results on large deviations to compare two models, each one described by a different H\"older Gibbs probability measure. One main difference to the classical hypothesis tests in Decision Theory is…

Statistics Theory · Mathematics 2021-12-28 Hermes H. Ferreira , Artur O. Lopes , Silvia R. C. Lopes

Quantum non-Gaussian states represent an important class of highly non-classical states whose preparation requires quantum operations or measurements beyond the class of Gaussian operations and statistical mixing. Here we derive criteria…

Quantum Physics · Physics 2021-07-21 Jaromír Fiurášek , Lukáš Lachman , Radim Filip

We show that one single experiment can test simultaneously and independently both the nonclassicality of states and measurements by the violation or fulfillment of classical bounds on the statistics. Nonideal measurements affected by…

Quantum Physics · Physics 2011-03-28 Alfredo Luis , Ángel Rivas

This thesis aims to establish notions of symmetry for quantum states and channels as well as describe algorithms to test for these properties on quantum computers. Ideally, the work will serve as a self-contained overview of the subject. We…

Quantum Physics · Physics 2023-05-25 Margarite L. LaBorde

If the phase space-based Glauber-Sudarshan distribution, $P_{\rho}$, has negative values the quantum state,~$\rho$, it describes is nonclassical. Due to $P$'s singular behaviour this simple criterion is impractical to use. Recent work…

Quantum Physics · Physics 2026-03-04 Ole Steuernagel , Ray-Kuang Lee

Distribution testing can be described as follows: $q$ samples are being drawn from some unknown distribution $P$ over a known domain $[n]$. After the sampling process, a decision must be made about whether $P$ holds some property, or is far…

Distributed, Parallel, and Cluster Computing · Computer Science 2020-12-04 Uri Meir

In this work we study the phenomenon of self-testing from the first principles, aiming to place this versatile concept on a rigorous mathematical footing. Self-testing allows a classical verifier to infer a quantum mechanical description of…

We study the extent to which \psi-epistemic models for quantum measurement statistics---models where the quantum state does not have a real, ontic status---can explain the indistinguishability of nonorthogonal quantum states. This is done…

Quantum Physics · Physics 2014-07-14 Cyril Branciard

The task of binary quantum hypothesis testing is to determine the state of a quantum system via measurements on it, given the side information that it is in one of two possible states, say $\rho$ and $\sigma$. This task is generally studied…

Quantum Physics · Physics 2021-04-21 Robert Salzmann , Nilanjana Datta

The quantum analogue of the equality function, known as the quantum state identity problem, is the task of deciding whether $n$ unknown quantum states are equal or unequal, given the promise that all states are either pairwise orthogonal or…

Quantum Physics · Physics 2026-04-15 Harry Buhrman , Dmitry Grinko , Philip Verduyn Lunel , Jordi Weggemans

We investigate distribution testing with access to non-adaptive conditional samples. In the conditional sampling model, the algorithm is given the following access to a distribution: it submits a query set $S$ to an oracle, which returns a…

Data Structures and Algorithms · Computer Science 2018-11-06 Gautam Kamath , Christos Tzamos

A standard method to obtain information on a quantum state is to measure marginal distributions along many different axes in phase space, which forms a basis of quantum state tomography. We theoretically propose and experimentally…

We introduce a new discrepancy score between two distributions that gives an indication on their similarity. While much research has been done to determine if two samples come from exactly the same distribution, much less research…

Machine Learning · Computer Science 2012-10-16 Maayan Harel , Shie Mannor

We consider the problem of quantum state certification, where we are given the description of a mixed state $\sigma \in \mathbb{C}^{d \times d}$, $n$ copies of a mixed state $\rho \in \mathbb{C}^{d \times d}$, and $\varepsilon > 0$, and we…

Quantum Physics · Physics 2022-10-21 Sitan Chen , Brice Huang , Jerry Li , Allen Liu

We generalise a non-classicality test described by Kot et al. [Phys. Rev. Lett. 108, 233601 (2010)], which can be used to rule out any classical description of a physical system. The test is based on measurements of quadrature operators and…

Quantum Physics · Physics 2015-12-16 Luca Fresta , Johannes Borregaard , Anders S. Sørensen

We discuss an "operational" approach to testing convex composite hypotheses when the underlying distributions are heavy-tailed. It relies upon Euclidean separation of convex sets and can be seen as an extension of the approach to testing by…

Statistics Theory · Mathematics 2018-11-13 Vincent Guigues , Anatoli Juditsky , Arkadi Nemirovski

Given a fixed-sample-size test that controls the error probabilities under two specific, but arbitrary, distributions, a 3-stage and two 4-stage tests are proposed and analyzed. For each of them, a novel, concrete, non-asymptotic,…

Statistics Theory · Mathematics 2022-06-27 Yiming Xing , Georgios Fellouris

In this paper, we investigate the problem of deciding whether two random databases $\mathsf{X}\in\mathcal{X}^{n\times d}$ and $\mathsf{Y}\in\mathcal{Y}^{n\times d}$ are statistically dependent or not. This is formulated as a hypothesis…

Machine Learning · Computer Science 2023-11-13 Vered Paslev , Wasim Huleihel