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In the realm of quantum information processing, the efficient characterization of entangled states poses an overwhelming challenge, rendering the traditional methods including quantum tomography unfeasible and impractical. To tackle this…

Quantum Physics · Physics 2025-12-09 Ye-Chao Liu , Jiangwei Shang

A popular approach for testing if two univariate random variables are statistically independent consists of partitioning the sample space into bins, and evaluating a test statistic on the binned data. The partition size matters, and the…

Methodology · Statistics 2016-04-28 Ruth Heller , Yair Heller , Shachar Kaufman , Barak Brill , Malka Gorfine

We study a hypothesis testing problem in which data is compressed distributively and sent to a detector that seeks to decide between two possible distributions for the data. The aim is to characterize all achievable encoding rates and…

Information Theory · Computer Science 2011-02-01 Md. Saifur Rahman , Aaron B. Wagner

We study a new framework for property testing of probability distributions, by considering distribution testing algorithms that have access to a conditional sampling oracle.* This is an oracle that takes as input a subset $S \subseteq [N]$…

Data Structures and Algorithms · Computer Science 2015-01-19 Clement Canonne , Dana Ron , Rocco A. Servedio

Recently, there has been significant work studying distribution testing under the Conditional Sampling model. In this model, a query specifies a subset $S$ of the domain, and the output received is a sample drawn from the distribution…

Data Structures and Algorithms · Computer Science 2020-11-05 Shyam Narayanan

We investigate sampling procedures that certify that an arbitrary quantum state on $n$ subsystems is close to an ideal mixed state $\varphi^{\otimes n}$ for a given reference state $\varphi$, up to errors on a few positions. This task makes…

Quantum Physics · Physics 2018-04-16 Frédéric Dupuis , Serge Fehr , Philippe Lamontagne , Louis Salvail

We consider the problem of closeness testing for two discrete distributions in the practically relevant setting of \emph{unequal} sized samples drawn from each of them. Specifically, given a target error parameter $\varepsilon > 0$, $m_1$…

Machine Learning · Computer Science 2015-04-20 Bhaswar B. Bhattacharya , Gregory Valiant

This is the documentation for generating random samples from the quantum state space in accordance with a specified distribution, associated with this webpage: http://tinyurl.com/QSampling . Ready-made samples (each with at least a million…

There has been much interest in quantum key distribution. Experimentally, quantum key distribution over 150 km of commercial Telecom fibers has been successfully performed. The crucial issue in quantum key distribution is its security.…

Quantum Physics · Physics 2009-11-10 Hoi-Kwong Lo , Xiongfeng Ma , Kai Chen

Characterizing large quantum systems with minimal assumptions is a central challenge in quantum information science. Self-testing provides the strongest form of certification by identifying the underlying quantum state solely from observed…

Quantum Physics · Physics 2026-05-15 Jinchang Liu , Elias X. Huber , Zhenyu Du , Xingjian Zhang , Xiongfeng Ma

We develop a theory of the algorithmic information in bits contained in an individual pure quantum state. This extends classical Kolmogorov complexity to the quantum domain retaining classical descriptions. Quantum Kolmogorov complexity…

Quantum Physics · Physics 2016-11-17 Paul M. B. Vitanyi

In the absence of any efficient classical schemes for verifying a universal quantum computer, the importance of limiting the required quantum resources for this task has been highlighted recently. Currently, most of efficient quantum…

Quantum Physics · Physics 2015-06-24 Theodoros Kapourniotis , Vedran Dunjko , Elham Kashefi

We study the problem of testing the covariance matrix of a high-dimensional Gaussian in a robust setting, where the input distribution has been corrupted in Huber's contamination model. Specifically, we are given i.i.d. samples from a…

Machine Learning · Computer Science 2021-01-01 Ilias Diakonikolas , Daniel M. Kane

High-quality random samples of quantum states are needed for a variety of tasks in quantum information and quantum computation. Searching the high-dimensional quantum state space for a global maximum of an objective function with many local…

Quantum Physics · Physics 2015-04-28 Jiangwei Shang , Yi-Lin Seah , Hui Khoon Ng , David John Nott , Berthold-Georg Englert

The paper tackles the issue of $\textit{checking}$ that all copies of a large data set replicated at several nodes of a network are identical. The fact that the replicas may be located at distant nodes prevents the system from verifying…

Distributed, Parallel, and Cluster Computing · Computer Science 2021-10-05 Pierre Fraigniaud , François Le Gall , Harumichi Nishimura , Ami Paz

Determining whether an unknown distribution matches a known reference is a cornerstone problem in distributional analysis. While classical results establish a rigorous framework in the case of distributions over finite domains, real-world…

Formal Languages and Automata Theory · Computer Science 2025-08-07 Smayan Agarwal , Shobhit Singh , Aalok Thakkar

We address the problem of distinguishing among a finite collection of quantum states, when the states are not entirely known. For completely specified states, necessary and sufficient conditions on a quantum measurement minimizing the…

Quantum Physics · Physics 2009-11-11 Noam Elron , Yonina C. Eldar

We show that any classical two-way communication protocol with shared randomness that can approximately simulate the result of applying an arbitrary measurement (held by one party) to a quantum state of $n$ qubits (held by another), up to…

Quantum Physics · Physics 2019-07-03 Ashley Montanaro

What advantage do \emph{sequential} procedures provide over batch algorithms for testing properties of unknown distributions? Focusing on the problem of testing whether two distributions $\mathcal{D}_1$ and $\mathcal{D}_2$ on $\{1,\dots,…

Data Structures and Algorithms · Computer Science 2022-05-13 Omar Fawzi , Nicolas Flammarion , Aurélien Garivier , Aadil Oufkir

Motivated by the question of data quantization and "binning," we revisit the problem of identity testing of discrete probability distributions. Identity testing (a.k.a. one-sample testing), a fundamental and by now well-understood problem…

Data Structures and Algorithms · Computer Science 2020-04-28 Clément L. Canonne , Karl Wimmer
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